to primary users (pus), ... very important example is ieee 802.22 wireless regional ... several...

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Peer-to-Peer Networking andApplications ISSN 1936-6442 Peer-to-Peer Netw. Appl.DOI 10.1007/s12083-016-0465-0

An overview of medium access controlstrategies for opportunistic spectrum accessin cognitive radio networks

Ajmery Sultana, Xavier Fernando & LianZhao

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Peer-to-Peer Netw. Appl.DOI 10.1007/s12083-016-0465-0

An overview of medium access control strategiesfor opportunistic spectrum access in cognitive radionetworks

Ajmery Sultana1 · Xavier Fernando1 · Lian Zhao1

Received: 25 January 2016 / Accepted: 25 April 2016© Springer Science+Business Media New York 2016

Abstract Cognitive radio (CR) is a promising wirelesstechnology that provides efficient spectral usage. MediumAccess Control (MAC) has an important role in several cog-nitive radio functions such as sensing, spectrum mobility,resource allocation and spectrum sharing. We focus on theopportunistic spectrum access (OSA) functionality of theCR network MAC layer by which the secondary users (SUs)access licensed spectrum in space and time with no harmfulinterference to primary users (PUs), without prior infor-mation on spectral usage. To achieve this, the unlicensedusers should have the ability to adaptively and dynami-cally seek and exploit opportunities in licensed spectrum intime, polarization and frequency domains. There have beenseveral OSA MAC schemes proposed for CR networks.This article presents a detailed review of such state-of-the-art schemes. First the differences between the conventionalMAC protocols and OSA based MAC protocols are dis-cussed. Existing OSAMAC protocols are classified accord-ing to their key attributes and their performances. Finally,future research directions are discussed.

Keywords Cognitive radio · Opportunistic spectrumaccess · MAC layer · Dynamic spectrum sharing

� Lian [email protected]

1 Department of Electrical and Computer Engineering, RyersonUniversity, Toronto, Canada

1 introduction

Ever increasing service demand poses two major challengesin the next generation wireless communication paradigm.One is the spectrum scarcity and the other is the demand ofhigh data rates, upto few Gbps. While there is a need fornew spectrum bands, it is observed that currently licensedspectrum is significantly underutilized [1]. Cognitive radio(CR), first coined by Joseph Mitola [2], has been proposedas a solution for efficiently utilizing the radio resources.CR is typically built using software-defined radio (SDR)technology, in which the transmitter operating parameters,such as the frequency range, modulation type and trans-mission power can be dynamically adjusted by software [3,4]. CRs, with its ability to smartly interact with the sur-rounding environment, are amenable to allow the coexis-tence licensed (primary) users and unlicensed (secondary)users sharing the same bandwidth opportunistically withoutcausing harmful interference to each other.

Cognitive radio network (CRN) has distinctive charac-teristics from a traditional wireless network where it intel-ligently recognizes the status of the radio environment andadjusts its functional parameters accordingly [4, 5]. Mostcritical part of CRN is allowing CR users to share thelicensed spectrum with PUs without degrading their perfor-mance [6]. This imposes new challenges and open researchissues.

Regulation and standardization efforts have already beencarried out to envision some of the applications of CRN. Avery important example is IEEE 802.22 Wireless RegionalArea Network (WRAN) standard [7]. It provides specifica-tions for broadband wireless access using CR technology

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and spectrum sharing policies and procedures for opera-tion in the white space TV bands. IEEE 802.11af standardand its amendments [8] enable geo-location database accessin the white space radio frequency (RF) spectrum. IEEE1900.x series of standards [9] provide next generation radioand advanced spectrum management. IEEE 802.19 stan-dard [10] enables the family of IEEE 802 wireless stan-dards to most effectively use TV white space by providingstandard coexistence methods among dissimilar or indepen-dently operated IEEE 802 networks and devices. It is alsouseful for non IEEE 802 networks and TV band devises. Thefirst set of standardization study towards licensed sharedaccess for long term evaluation (LTE) is reported in [11]that were successfully trialed in a live LTE network in the2.4-2.5 MHz frequency band [12]. In most recent times,IEEE has engaged the 802.15.4m task group [13] to char-acterize cognitive radio-aware PHY and MAC layers forcognitive machine-to-machine networks. These examplesshow standardization process for CR is well underway.

1.1 Medium access control layer

Medium access control (MAC) layer is responsible forthe control and coordination of communication over wire-less channels, several cognitive radio functions like channelsensing, spectrum sharing, resource allocation and spectrummobility need to be included in the design of MAC proto-col for CRN. In the rapidly changing radio environment, theCRN MAC protocol shall make number of decisions in realtime. This makes the design of CRN very challenging com-pared to conventional MAC protocols, that work under thecurrent static spectrum policies.

In recent decades, the concept of opportunistic spectrumaccess (OSA) has emerged to significantly increase spec-trum utilization. Efficient sensing and dynamic spectrumaccess are the key challenges of an OSA MAC protocol.For this, the SUs should have the ability of dynamicallysearch and utilize opportunities in the licensed spectrumalong in different dimensions like time, frequency or evencode. Thus an OSA MAC should integrate both sensing andchannel access functionalities. In essence, spectrum sens-ing, allocation and access, spectrum sharing and spectrummobility, are the key elements for efficient OSA MAC pro-tocol design. Figure 1 shows the basic elements of OSAMAC protocol in CRNs. Figure 2 points out the OSA MACprotocol functional requirements.

1.2 Related work and positioning of this survey

There are several burgeoning research efforts to providegeneral classification, analysis and comprehensive overviewregarding MAC paradigm in CRNs. Extensive research andeffort have been conducted to construct several surveys

Fig. 1 Basic elements of OSA MAC protocol

that are presented in [14–25] in order to focus on differentMAC strategies in CRNs. In [14] the authors provide gen-eral classification and overview of MAC protocols whereC-MAC cycle is constructed to incorporate several impor-tant aspects in CRN context; however, they did not includemulti-hop environment into the classification. Also [14]falls short in addressing the challenges in designing MACfor CRNs. The authors discussed several research issuesand challenges in [15], gave an overview of MAC protocolsand presented many classifications with their advantagesand disadvantages. However, a well rounded integrationof most recent research endeavors was missing. In [16],the challenges in the design and implementation of dis-tributed dynamic spectrum access (DSA) protocols are

Fig. 2 OSA MAC protocol functionalities



addressed, existing distributed DSA protocols are catego-rized and described to offer a detail overview. An extensivediscussion on different MAC approaches based on clas-sification, are presented in [17–19]. The authors in [20]mainly focus on open research areas and several MACprotocols for distributed architecture. The authors in [21–25] mainly concentrate on multi-channel specific aspects inCRNs and proposed approaches [26–29] reveal the state-of-the-art research exertions in OSA MAC framework. To thisend, we present a comprehensive and up-to-date overviewof OSA MAC schemes with recent research trends and, anin-depth investigation and future research directions. Com-pared to previous surveys, this article provides the followingcontributions:

• It identifies basic elements and pointed out functionalrequirements for OSA MAC protocol.

• It provides classification incorporating most of the char-acteristics in CR MAC context.

• It presents a comprehensive analysis and evolutionaryview of OSA MAC strategies in CRNs with recentresearch progresses.

• It provides comparison based on different objectivesand their solution approaches as well as on severalcharacteristic features.

• It points out potential exertions based on recent researchtrends as well as several active and open issues that getlittle attention so far.

Table 1 highlights the major contributions of differentexisting surveys and clarify the positioning of this survey.

1.3 Organization of the article

The rest of this article is organized as follows. Section 2provides taxonomy of MAC protocols for CRNs. Section 3depicts taxonomy based on different objectives, solutionapproaches and performance metrics, in-depth analysis andcomparison. Section 4 describes standardization endeavorregarding CR-MAC engineering. Section 5 presents discus-sions and future research roadmap. Section 6 concludes thepaper.

2 Taxonomy of MAC protocols for CRNs

During the past decade, a large number of MAC protocolfor CRNs have been explored. The design of newMAC pro-tocol can be classified based on different criteria that areenvisioned in Fig. 3.

2.1 Network architectures

In the context of MAC network architectures, the spec-trum sharing/access technique can either be centralized ordistributed. Centralized architecture is typically used forinfrastructure based CRNs, for example IEEE 802.22 [30].These strategies typically enable simple hardware and soft-ware capabilities for CR nodes, but impose spatio-temporalspectrum sensing and active synchronization among allnodes. Due to the ease of deployment, the distributed archi-tectures draw the attention for more future applications. The

Table 1 Comparison of related surveys in the literature

[14], 2014 [15], 2014 [25], 2013 [16], 2012 [17], 2012 [28], 2009 Our work

Basic element identification and Extensive N/A N/A N/A N/A Limited Extensive

functional requirements

Classification based on characteristic Extensive Moderate Extensive Extensive Extensive Extensive Extensive

features

Comparison based on characteristic Moderate Extensive Extensive Extensive Moderate Moderate Extensive

features

Generic OSA MAC design parameter Moderate Limited Limited Limited Limited Limited Extensive

Taxonomy based on different N/A N/A N/A N/A N/A N/A Extensive

objectives

Comprehensive analysis Extensive Moderate Extensive Extensive Extensive Extensive Extensive

Integration of recent research trends Moderate Limited Moderate Moderate Moderate Moderate Extensive

Comparison of different objectives, N/A N/A N/A N/A N/A N/A Extensive

solution approaches and

performance metrics

Future research roadmap Extensive Moderate Moderate Extensive Extensive Extensive Extensive



Fig. 3 Classification of CRMAC protocol

centralized solutions may not be a proper choice due to thedistributed and self-organized nature of OSA CRNs. There-fore, the focus of this article is on the distributed OSAMACs.

2.2 Channel usage strategies

According to the channel usage strategy, MAC schemescan be classified into single channel or multi-channelMAC protocol. Simpler architecture of single channel based

protocol makes it attractive; however, network throughputis low due to lower data transmission rate. In addition, thewell known hidden terminal problem, shadowing, multipathfading and receiver noise/interference uncertainty issuesmay cause severe impact on network performance in sin-gle channel scenario. On the contrary, multi-channel MACprotocol performs better than single channel protocol in sev-eral aspects such as 1) increased network throughput due tomultiple simultaneous data transmissions, 2) reduced inter-ference among SU nodes and, 3) reduced number of SU



nodes affected by sudden PU activity [31]. However, com-plex design architecture and high deployment cost are themajor drawbacks for this approach.

2.3 Spectrum sharing schemes

In CRNs, spectrum sharing between PUs and SUs can bedefined as the real time spectrum management that allowsSUs to access licensed spectrum with little or no interfer-ence to the PUs [32]. This leads to a few possible spectrumsharing scenarios. These are: 1) interweave (no space, time,frequency, polarization or angular overlapping transmissionbetween the PU and SU [33], 2) underlay (controlled andmanaged interference between the PU and SU), and 3) over-lay (the SU assists the PU) scenarios [34]. The interweaveapproach is ideal, but offers minimal CR throughput. In theinterweave or OSA scheme, the SU first performs spectrumsensing, discovers white spaces or spectrum holes and thenuses those vacant frequency bands for transmission [35].The focus of this paper is OSA (interweave) MACs.

2.4 Spectrum access methods

Based on the nature of channel access, CRN-MAC pro-tocol can be classified as random access/contention-based protocols, time slotted protocols and hybrid proto-cols [36]. Contention-based MAC protocols mainly workon carrier sense multiple access and collision avoidance(CSMA/CA) principle. Synchronization between SU nodesis not required in this scheme. Contention based protocolsattract researchers attention due to their simple architec-ture. However, inefficient spectrum utilization and datapacket collisions are the major drawbacks which degradenetwork performance. Time slotted protocols, where timeis split into slots to be used for both control and datatransmission, global synchronization between SU nodes isrequired. Hence, slot allocation and synchronization com-plexity can affect the system throughput. Hybrid protocolsare presumed to be a combination of contention basedand time slotted schemes i.e., channels are partially slot-ted and access to these channels is done in random fashion.Therefore, this approach has the benefit of both the aboveapproaches.

2.5 Channel allocation behaviors

The channel allocation behavior in CRNs can either becooperative or non-cooperative [4]. In the cooperativescheme, SU nodes consider the existence of other SU nodesand their information during spectrum allocation. Thisscheme can be treated as a collaborative approach to spec-trum allocation. On the other hand, in the non-cooperativescheme, SU nodes do not exchange any information, and

hence often considered as a selfish approach. Here, the SUnodes access the channel independently according to bothlocal monitoring and statistics, and use pre-programmedregimes, thus reducing communication overhead.

2.6 Spectrum sensing strategies

Spectrum sensing can be either local or cooperative. In localspectrum sensing based MAC protocol, only local sensingoutcomes are utilized for OSA whereas in cooperative spec-trum sensing basedMAC protocol, SU nodes exchange theirlocal sensing outcomes and combine results from variousmeasurements to make more accurate decision. The coop-erative spectrum sensing based protocol is an attractive andeffective strategy to combat multipath fading, shadowingand mitigate the receiver uncertainty problem [3]. How-ever, cooperative spectrum sensing based protocol designand architecture are more complex than the local spectrumsensing based protocol.

2.7 Control channel (CC) mechanism

Control channel (CC) mechanism is a crucial functional-ity in OSA MAC design. It should provide coordination,cooperation and collaboration between all network entitiesand spectrum sensing and access process. CC based MACprotocols can be classified into two broad categories: Dedi-cated (Common) CC (DCC) and non-dedicated CC (NDCC)based MAC protocols. In DCC, two transceivers are usedwhere one is dedicated for control message transmission andthe other for negotiated data transmission for the remain-ing channels. Since one radio is always available for controlmessage exchange, there is no chance to miss the con-trol information even during data transmission. Therefore,multi-channel hidden terminal problem is also solved. How-ever, the case when only one transceiver is used, controland data transmissions occur alternately in time based onthe demand, hence the protocol operation becomes morecomplex and less synchronized.

Another dedicated approach is split phase (SPCC) whichutilizes only one transceiver but the time is divided into twophases, namely control phase and data transmission phase.This approach together with power saving mode (PSM) ofIEEE 802.11, attracts researcher attention to design energyefficient OSA MAC protocols. In addition, SPCC mitigateshidden terminal issues. However, precise time synchroniza-tion requirement and control channel saturation problem arestill drawbacks of this approach.

The DCC can either be global, local ordynamic/configurable depending on the network coverage.In global DCC (GDCC), an unlicensed band (e. g., ISMband) can be globally used for control signaling by allSUs in the CRN. In particular, the GDCC provides high



level of network coordination and global coverage [37].However, it exhibits some drawbacks such as no trafficdifferentiation, control channel saturation problem, wastageof resource and security issues i.e., denial of service (DoS)attack [38, 39]. In local DCC (LDCC), all SUs in theCRN exchange control information over DCC channelsthat are selected locally and free from PU interference.LDCC mechanism can be achieved by node grouping [40]or node clustering [41–43]. Dynamic/configurable DCCsare similar to the LDCCs except that control channel isnot presumed to exist. The participating SUs configure ordynamically select an available channel temporarily controlchannel. Also there are no cluster-heads or group leadersfor controlling spectrum access in implementing such achannel [44].

The NDCC mechanism alleviates the shortcomings ofthe DCC mechanism since it does not require the controlchannels solely responsible for control message exchangeand to be PU free. The NDCC mechanism can be estab-lished by frequency hopping, rendezvous or ultra-widebandchannels. In frequency hopping DCC (FHDCC), all CRnodes hop across all channels following a deterministicpattern which is usually static in nature and is generatedfrom pseudo-random generator [45]. This scheme has theadvantage of utilizing all the channels for control and datatransmission. This feature makes this scheme to be free fromPU interruption and overcome control channel saturationproblem. In addition, it utilizes only one transceiver. How-ever, hidden terminal issue, high channel switching delay,strong hardware dependency and tight synchronizationrequirement between CR nodes make this approach morechallenging.

In rendezvous approach (RNDCC), multiple SU nodescan exchange control message in different channels at thesame time by using different hopping sequences that over-lap at certain point. This approach permits multiple pairsof communication at the same time across all availablechannels making it most robust to sudden PU activities.However, it requires strict synchronization between thehopping pairs since they need to concern about their over-lapping times of one-hop neighbors. However, they requirea high overhead for supporting broadcast communicationbecause of the randomized connections between neigh-bors [46]. The last approach, ultra-wideband NDCC (UWB-NDCC) utilizes spread spectrum techniques in underlayfashion.

2.8 Effects of number of radio front ends (RFEs)

The number of RFEs extensively plays a pivotal role inthe operation of an SU node which consequently affectsthe scanning procedure and OSA MAC operation. Indeed,

having multiple RFEs means concurrent control and datatransmission which significantly boosts system throughputand decreases delay. Multiple RFEs also provide higherspectrum efficiency and better sensing accuracy. However,they also increase node complexity, deployment cost andpower consumption. Alternatively, single RFE needs scan-ning and transmission (control and data) to be split intime domain. This not only simplifies the structure butalso reduces node complexity, deployment cost and powerconsumption. However, single RFE also reduces spectrumefficiency, sensing accuracy and also suffers from multi-channel hidden terminal problem. In the literature, the num-ber of RFEs differs from one (control and data exchangeis performed by time sharing) to three (one for controlmessage exchange and two for data transmission).

2.9 Network topologies

A CRN may have a single-hop or multi-hop network infras-tructure. The emerging IEEE 802.22 standard-based [47]WRAN technology is based on the single-hop CRN con-cept. Here, a centralized cognitive base station managesthe SUs that opportunistically use the TV bands whenthey are unoccupied by the incumbent TV services. On theother hand, multi-hop CRNs (MHCRN) have no fixed net-work infrastructure or central controller. They also havean additional requirement that the information needs tobe relayed over multiple wireless links. Therefore, theSUs in a MHCRN have to coordinate themselves in adistributed fashion [48]. MHCRNs have the potential toachieve efficient spectrum usage, interference mitigation,higher throughput and extended coverage [49]. The termMHCRN and a multi-channel network seems to be simi-lar, because both control channel and multi-channel hiddenterminal problems [50] are common to these two networkenvironment. But there are some major differences betweenthese two such as 1) channel availability for each node isvariable for MHCRN whereas it is fixed for multi-channelnetworks, 2) transmission ranges and bandwidths varyin MHCRN forming heterogeneous environment whereasthese two parameters are equal in multi-channel environ-ment. Thus, a multi-hop and a multi-channel environmentjointly form MHCRNs [51].

Figure 4 shows generic OSA MAC design parametersfor each section, that are found in the literature. A genericOSA MAC design structure consists of four portions: (1)inputs; (2) outputs; (3) objectives; and (4) constraints. Dif-ferent input parameters are provided by regulatory author-ities. Under different constraints the OSA MAC protocolsare analyzed and evaluated where protocol performance ismeasured in different metrics in order to produce desiredoutputs.



Fig. 4 Generic OSA MACdesign structure

Input Metrics(any combination)

Number of SUs, Number of PUs,

Number of transceivers, Channel sensing procedure,

Protocol type, CC mechanism,

Queueing model, Channel access technique, Channel state information, Channel allocation scheme,

Network environment, Customized network related

parameters.

Output Metrics(any combination)

Aggregate throughput,Optimal number

of sensed channels,Channel access delay,

Packet transmission delay, Blocking probability, Continuty probability,

Interference time, Number of interfered incumbent systems,Successful packettransmission ratio,Collisions per slot,

Collision probability with PUs, Forced termination

Probability.

Constraint (any combination)Interference with PUs,

Adjacent channel interference const, Channel selection/assignment,

Sensing errors, QoS, Delay, Bandwidth, Fairness, Topology, Traffic characteristic, Security.

Objective (any combination)

MaximizeSpectrum utilization,

Channel grabbing, Bandwidth utilization,

Link maintenance,Incumbent protection,

Traffic admission probability,

Acceptable sensingerror probability

Packet delivery ratio, Energy efficiency,

Network connectivity.

MinimizeQueueing delay, Packet

transmission delay, Access delay, System

time for buffering, Join time of SUs,

Collision rate, Sensing overheads,

Communication overheads, Blocking

probability, False alarm and miss

detection probability, Probability of collision

with Pus.

3 Taxonomy of objectives, solution approachesand performance metrics

Taxonomy of OSA MAC protocol objectives for CRNis described in Fig. 5. Depending on different objec-tives, researchers proposed different solution approaches toachieve certain goals.

3.1 Spectrum utilization

One important objective for designing OSA MAC isresourceful usage of unused or under-utilized spectrum.

To achieve this goal based on control channel mecha-nism as discussed earlier, some researchers use dedicatedapproaches while others exploit non-dedicated approaches.For dedicated approach, in [52] a CSMA/CA based MACprotocol is proposed for single channel where a dynamicback-off algorithm is exploited that utilizes the networksituation depending on traffic. Another three-dimensionaldiscrete time Markov chain (DTMC) CSMA/CA MACprotocol is proposed in [53]. Here, the censored Markovchain method is utilized to get the steady state dis-tribution for the evaluation of throughput and accessdelay.

Fig. 5 OSA MAC protocolobjective types



For dynamic spectrum utilization, IEEE 802.11 basedMAC protocol is proposed in [54]. Here, reporting, nego-tiation (reduced duration) and data transmission are carriedout immediately during the ongoing time slot. The authorsin [55] proposed a contention based distributed multi-channel MAC where spectrum sensing part is exclusivelyhandled by sensing nodes. The length of contention win-dow is optimized to maximize idle channel utilization. Tosupport spectrum agility along with spectrum utilization,the authors proposed an efficient MAC (OS-MAC) protocolin [56]. Here, group based scheme is utilized to choose bestdata channel based on current traffic.

Another CSMA/CA-based cognitive MAC (SCA-MAC)protocol is proposed in [57]. Here, statistical channel allo-cation is performed based on controlling parameters suchas operating range and channel aggregation. In [58] theauthors proposed a decentralized opportunistic cognitiveMAC (OC-MAC) over CRNs along with WLAN usingalmost identical approach of that in [57]. OC-MAC ismainly based on improved version of cognitive borrow-ing algorithm [59] that has three main attributes: channelselection, connection negotiation and collision avoidance.A well-organized handshaking process and a maximumtransmission duration prediction model keep this protocolaway from generating interference to PUs. Like in [58]to co-exist with legacy users (PUs), dynamic open spec-trum sharing (DOSS) MAC protocol is proposed in [60]. Atri-band approach: control band, data band and busy-toneband, is utilized for channel negotiation, for data transmis-sion and for solving hidden and exposed terminal problemsrespectively.

Under non-dedicated approaches, for efficient spectrumutilization, a distinct channel-hopping based OSA MACprotocol is proposed in [61]. Another common hoppingsequence based protocol called dynamic channel hoppingMAC (DH-MAC), is proposed in [62]. The channel-hoppingsequence maintains a cyclic pattern that is adaptive to theactivity of neighboring PUs, thus avoiding the PU long-timeblocking problem. For spectrum utilization under fadingenvironment, the authors in [63] proposed a throughputoptimization OSA MAC strategy with cross-layer designapproach. A partially observable Markov decision process(POMDP) framework has been utilized for optimal spec-trum sensing and access policies which is evaluated by aniterative approach of linear programming. Table 2 sum-marizes different approaches of OSA MAC protocol forspectrum utilization.

3.2 Protection of incumbent system

The major focus of the OSA MAC policy is how it canexploit unused radio resources and avoid interference toboth PUs and other SUs in CRNs. For the detection and

protection of incumbent systems, a CSMA/CA based dis-tributed cognitive radio MAC (DCR-MAC) protocol isproposed in [64]. Here a reactive, reliable and collision-free reporting procedure with little overhead is presentedto obtain the incumbent system sensing results from theneighbor nodes. A channel status table with explicit andimplicit channel sensing and monitoring using an overhear-ing method is also utilized. Another CSMA/CA based reac-tive multi-channel cognitive MAC protocol (RMC-MAC) isproposed in [65]. A reactive sensing period is included andan efficient recovery scheme based on handoff method ispresented to decrease the forced termination probability thatprovides higher capacity for SUs. Table 3 summarizes dif-ferent approaches of OSA MAC protocol for protection ofincumbent system.

3.3 Spectrum sensing

Spectrum sensing is a key utility for OSA MAC designto avert harmful interference with PUs and discover theavailable spectrum holes for improved spectrum exploita-tion. The following aspects need to be carefully designedand handled regarding spectrum sensing in order to developefficient OSA MAC protocols.

3.3.1 Signal detection schemes

In OSA MAC paradigm, the primary aim is to exploreand exploit spectrum holes i.e., idle PU channels by SUwhenever PUs are not present. Detection of spectrum holesi.e., opportunities can be executed by some type of sig-nal detection techniques. State-of-the-art research in signaldetection schemes are categorized in two major classes:blind and feature detection techniques [66]. In blind detec-tion scheme, the presence or absence of any sort of signalcan be detected without apriori information about PU traf-fic statistics. Energy detection [67–69] is one of the mosttypical examples of blind detection schemes. In the featuredetection technique, a signal can be detected as well as clas-sified to make PU distinction from different SUs signal.It can also differentiate between various types of PU andSU signals. Matched filter [70] and cyclostationarity detec-tion techniques are two most popular examples of featuredetection technique.

3.3.2 PU channel models

While designing OSA MAC, PU behavior and activity aremodeled based on predefined or estimated parameters todevelop optimal spectrum sensing, spectrum sharing andcontrol channel management [71]. In this context, the mostcommonly used PU channel model is Gilber-Eliot channelmode [72]. In particular, this model is suitable for slotted



Tabl

e2

Different

approaches

forspectrum

utilizatio

n

Ref.

Objectiv

eSo

lutio

napproach

CCmechanism

Spectrum

sensing

Performance

metric

[52],2

014

Spectrum

utilizatio

nDynam

icback-offalgorithm

Singlechannel

Sensingalgorithm

isnotd

escribed

Throughput

(NoCC)

andperfectsensing

isassumed

[53],2

013

Spectrum

utilizatio

nCensoredMarkovchainmethod

Dedicated

CCC

Sensingalgorithm

isnotd

escribed

Throughput,channelaccessdelay

used

forsteady

statedistributio

nandperfectsensing

isassumed

[54],2

009

Spectrum

utilizatio

nReportin

g,negotiatio

n(reduced

Dedicated

CCC

Sensingalgorithm

isnotd

escribed

Throughput

duratio

n)anddatatransm

ission

andperfectsensing

isassumed

carriedouto

ntheongoingtim

e

slot

[55],2

013

Spectrum

utilizatio

nSeparatesensingpartexclusively

Dedicated

CCC

Sensingalgorithm

isnotd

escribed

Channelutilizatio

nandgrabbing,

handledby

sensors

andperfectsensing

isassumed

blocking

probability

[56],2

008

Spectrum

utilizatio

nGroup

basedapproach

where

each

Dedicated

CCC

Sensingalgorithm

isnotd

escribed

Throughput,sessiondelayand

andagility

groupchoose

bestdatachannel

andperfectsensing

isassumed

sessionsharing

basedon

currenttrafficloads

[57],2

007

Spectrum

utilizatio

nStatisticalchannelallo

catio

nDedicated

CCC

Sensingalgorithm

isnotd

escribed

Throughput

coupledwith

operatingrange

andperfectsensing

isassumed

andthechannelaggregatio

n

[58],2

008

Spectrum

utilizatio

n,Use

cognitive

borrow

ingalgorithm,

Dedicated

CCC

Sensingalgorithm

isnotd

escribed

Throughput

avoiding

interference

awell-organizedhandshaking

andperfectsensing

isassumed

toPU

sprocessandamaxim

umtransm

is-

sion

duratio

npredictio

nmodel

[60],2

005

Spectrum

utilizatio

nby

real-

Atri-band

approach

:control

band,

Dedicated

CCC

Sensingalgorithm

isnotd

escribed

Throughput

timedynamicspectrum

databand

andbusy-toneband

andperfectsensing

isassumed

allocatio

nareutilized

[61],2

008

Spectrum

utilizatio

nDistin

ctchannel-hoppingsequence

Non

dedicatedandnon

Sensingalgorithm

isnotd

escribed

Aggregatethroughput

utilizatio

nglobal(M

ultip

leandperfectsensing

isassumed

rendezvous)CCC

[62],2

010

Spectrum

utilizatio

n,Cyclic

switching

ofhopping

Non

dedicatedandnon

Sensingalgorithm

isnotd

escribed

Aggregatethroughput

PUlong

timeblocking

patte

rnwhich

isadaptiv

eto

global(M

ultip

leandperfectsensing

isassumed

problem

PUsactiv

ityrendezvous)CCC

[63],2

013

Spectrum

utilizatio

nunder

Iterativeapproach

basedon

NodedicatedCCC

Realistic

sensingalgorithm

with

errors

Throughput

fading

environm

ent

POMDPfram

ework



Table 3 Different approaches for incumbent protection mechanism

Ref. Objective Solution approach CC mechanism Spectrum sensing Performance metric

[64], 2009 Protection of Reactive reporting from neighbor Dedicated CCC No algorithm, Interference time, number

incumbent nodes and channel-status table no errors are of interfered incumbent

system maintenance with explicit and considered systems, successful packet

implicit sensing and monitoring transmission ratio, access

using an overhearing technique delay.

[65], 2011 Protection of An efficient recovery scheme Dedicated CCC No algorithm, Bandwidth utilization, forced

incumbent based on handoff method by no errors are termination probability

system introducing reactive sensing considered

period

PU structures. When the PU channel state is continuouslytracked using spectrum sensing, the Gilber-Eliot channelmodel results in a hidden Markov model (HMM) [73]. Inthis case the OSA MAC protocol utilizes the HMM frame-work. On the contrary, when there are only partial obser-vations of the PU channel, the model results in a POMDP.In this case, the spectrum sensing and sharing processes aredriven under the POMDP framework.

3.4 Cooperative sensing

Cooperative spectrum sensing is an effective scheme wherelocal sensing results are combined to develop signal detec-tion performance [66]. Cooperative sensing can result insensing overhead such as additional sensing time, delay,energy and functions assigned for cooperative sensingwhich in turn cause performance degradation [74]. In orderto avoid complex hardware, an efficient OSA MAC isproposed in [75] where a novel deterministic sensing pol-icy called allocated-group sensing policy is designed todiscover spectrum opportunities based on a dynamic IDnumbering scheme.

3.4.1 Sensing errors

In general, there are two types of spectrum sensing errors:1) False alarm: This happens when an idle channel is rec-ognized as busy. Hence, a spectrum opportunity will besquandered, 2) Miss detection: This occurs when a busychannel is recognized as idle, thus causing collision withPUs. Both these spectrum sensing errors need to be takeninto account in efficient OSA MAC design. Consideringimperfect spectrum sensing, the authors of [76] proposedan OSA MAC protocol with two spectrum sensing policies:memoryless sensing policy and improved sensing policy.In order to effectively address spectrum sensing error, theauthors of [77] exploited a control transceiver attached tothe with sensors that effectively improves spectrum sensingaccuracy and carefully handles interference with PUs. The

design of optimal frame duration, sensing time and MACrandom access on frame-by-frame basis under imperfectsensing is addressed in [78].

3.4.2 Sensing stopping rule

SU needs to pay careful attention and instantaneous deci-sion when to stop sensing. The sensing process can be endedbased on several criteria: 1) when an idle or a predefinednumber of unused PU channels is discovered, 2) when theassessment of spectrum availability crosses certain thresh-old, 3) when the energy consumption for sensing purposegoes above the permitted level. A decentralized multi-channel cognitive MAC (HC-MAC) is proposed in [37]considering the hardware constraints (e.g., single radio,partial spectrum sensing and spectrum aggregation limit)into consideration. This protocol also integrates sensingand transmission overhead for intelligent spectrum sensing.Based on optimal sensing decision, a k-stage look-aheadmethod is used to formulate an optimal stopping rule withreduced overhead.

3.4.3 Learning capabilities

Learning is a general term that can be integrated into sens-ing scheme to improve system performance. The sensingschemes can be categorized based on learning capabilitiessuch as non-learning or learning approach. In non-learningapproach, spectrum sensing is carried out without consid-ering previous knowledge on spectrum availabilities andopportunities. In learning approach, sensing is performedbased on historical data and feedback results that are used togain knowledge on PU channel structure and traffic parame-ters such as state probabilities, state transition probabilities,activities of belief vectors of PU channels etc. Typicalexample of learning based sensing approach is myopic sens-ing. In [79] the authors proposed a decentralized cognitiveMAC where a decision-theoretic approach is adopted basedon POMDP. In order to design general primary network



models both for slotted and un-slotted structures, in [80]the authors proposed blind cognitive MAC protocols basedon augmented whittle index strategy of [81] without apri-ori knowledge about the statistics of the primary traffic.To overcome limitations in spectrum sensing, the authorsin [82] proposed a distributed MAC protocol with one-slotmemory where SUs adjust their transmission parametersbased on the local history of their own transmission actionsand feedback information. To make full use of the pastsensing and access experiences to optimize current chan-nel access, the authors of [83] proposed a decentralizedMAC protocol based on SARSA (state, action, reward, state,action) under POMDP framework. SARSA is a kind ofimportant reinforcement learning algorithm [84, 85] whichhas a self-learning and online learning ability and does notrequire the channel state transition probability of the pri-mary network. Table 4 summarizes different approachesof OSA MAC protocol regarding spectrum sensing relatedissues.

3.5 Channel access issues

Interference free dynamic channel access while meeting allcommunication requirement is the most crucial aspect ofCRNs. For dynamic channel access, a residual white spacedistribution based cognitive MAC (RWS-CMAC) is pro-posed in [86]. For efficient spectrum access as well as toprotect PU activity, a CR-CSMA/CA based MAC protocolis proposed in [87]. A prepare-to-sense frame is incor-porated with conventional RTS/CTS scheme to performasynchronous spectrum sensing and a blocking method isproposed to toil together with the traditional exponentialbackoff method. In order to address fairness issue of chan-nel access in [88], the authors presented a priority basedmulti-channel OSA MAC under Markov chain framework.The authors in [89] developed a CSMA/CA based multi-channel MAC protocol to prevent adjacent-channel inter-ference in channel access. A guard-band-aware sequentialfixing linear program channel assignment algorithm is inte-grated to reduce the quantity of necessary guard channelsfor a given transmission by utilizing adjacent channels andalready reserved guard channels. Table 5 summarizes dif-ferent approaches of OSA MAC protocol regarding channelaccess issues.

3.6 Avoiding the use of dedicated CC

In order to avoid the drawbacks of dedicated CC men-tioned earlier, researchers have, proposed different protocoldesigns. In [36] a two level carrier sensing - multiple accesscollision avoidance (CS-MACA) protocol based on slowcommon hopping (SH-MAC) is proposed for a coordinator-based CRN. In [90] a concurrent access MAC (CA-MAC)

based on split phase MAC protocol is proposed. Here, twochannel lists are exploited, namely 1) sorted channel list forgiving high priority to common channels and, 2) commonchannel list for faster reservation to reduce channel accessdelay.

To overcome the shortcomings of dedicated global CCC,the authors in [91] proposed a decentralized multi-channeladaptive medium access control (AMAC) protocol. Here,channel indexing based on available bandwidth, adaptedrate, channel condition, channel reliability and dual chan-nel usability, is utilized for most reliable CCC. In anotherinteresting approach, a simple learning based on decentral-ized MAC is proposed in [92]. This MAC utilizes multi-channel preamble reservation scheme with multichannelcarrier sensing principle and distributed channel selectionalgorithm.

On the same line, a novel decentralized multi-channelcognitive MAC (C-MAC) is proposed in [44] that uti-lizes the concept of rendezvous channel (RC) which ischosen dynamically based on the reliability of the avail-able channels. Here, backup channel (BC) is exploited formore robust RC to incumbents which can be determinedby in-band and out-of-band measurements via quiet periods(QPs). The authors in [44] did not take the full advantage ofdedicated beacon period for collision avoidance during datatransmission. Addressing this oversight, an efficient dynam-ically adjusting MAC (EDA-MAC) protocol for CRNs isproposed in [93]. In order to address slot-asynchronous ren-dezvous issue, a MAC protocol is designed in [94] with anovel RTS/CTS handshake scheme during channel hoppingprocess. An optimal time slot in terms of the shortest timeto handshake, is also devised.

In order to avoid dedicated CC, a novel stochasticmedium access (SMA-MAC) is proposed in [95]. Simi-larly, a MAC based on dynamic Markov-chain monte-carloapproach is proposed in [96]. A power controlled distributedRTS/CTS exchange scheme is also designed including con-tention resolution and data fragmentation methods for mini-mizing interference to PUs. In order to provide an enhancedmethod for idle channel selection in the NDCC approach,the authors of [97] proposed a MAC protocol where a chan-nel status table (CST) is formed. This is done by sortingand ranking of the channel according to the availability.The highest ranked CC is selected as CCC and the secondhighest CC is selected as data channel.

In order to improve the coexistence of PUs and SUsin CRNs, a novel opportunistic periodic MAC protocol(OP-MAC) is proposed in [98]. Here, the SU uses both slot-structured channels and slot-unstructured channels periodi-cally to sense channels, report channel states and exchangecontrol signals in a NDCC approach. An analytical modelin terms of channel utility, capacity and PU delay for anON/OFF channel scenario based on renewal theory [99] is



Tabl

e4

Different

approaches

regardingspectrum

sensingrelatedissues

Ref.

Objectiv

eSo

lutio

napproach

CCmechanism

Spectrum

sensing

Performance

metric

[75],2

009

Cooperativ

espectrum

Asensingalgorithm

based

Dedicated

localC

CC

Sensingalgorithm

and

Throughput,sensingduratio

n,

sensingmethod,

onallocatedgroupsensing

errorsareconsidered

optim

alnumberof

sensed

interference

constraint

policyby

dynamicID

channels

tothePU

snumbering

scheme

[77],2

012

Sensingalgorithm

and

Mem

orylesssensingpolicy,

Dedicated

CCC

Sensingalgorithm

and

Throughput,Collision

errors,P

Uprotectio

nandim

proved

sensingpolicy

errorsareconsidered

probability

with

PUs

constraints

andadjustingcontentio

n

windows,back-offduratio

ns

andaccess

probabilities

[76],2

009

Sensingerroranddelay,

Control

transceiverattached

Dedicated

CCC

Sensingalgorithm

isnot

Throughput,Collisionprobability

interference

constraint

with

sensors

describedbuterrors

with

PUs,maxim

umacceptable.

tothePU

sareconsidered

sensingerrorprobability

[78],2

009

Spectrum

sensingandaccess,

Contin

uous-tim

eMarkovchain

Singlechannel(no

CC)

Sensingalgorithm

isnot

Achievablethroughput,F

alse

PUprotectio

nconstraints

modelbasedon

sensingthroughput

describedbuterrorsare

alarm

probability

trade-offto

optim

izefram

eduratio

n,considered

sensingtim

eandp-persistent

CSM

A

underinterference

constraint

[37],2

008

Spectrum

sensingandaccess

Ak-stagelook-ahead

methodisused

Dedicated

CCC

Sensingalgorithm

anderrors

Throughput

with

hardwareconstraints

toform

ulatean

optim

alstopping

rule

arenotconsidered

basedon

optim

alsensingdecision

ofasecondarytransm

ission

pair

[79],2

007

Dynam

icspectrum

sensing,

POMDPfram

eworkthatincorporates

Synchronoushopping

Sensingalgorithm

isnot

Throughput,spectrum

efficiency

avoiding

theuseof

dedicated

aspectrum

occupancymodelanda

describedbuterrors

CCC,incum

bent

protectio

nsuboptim

alstrategy

with

reduced

areconsidered

mechanism

complexity

basedon

greedy

approach

[80],2

009

Generalprim

arynetworkmodels,

Blin

dMACprotocolsbasedon

NodedicatedCCC

Sensingalgorithm

isnotd

escribed

Throughput

avoiding

theuseof

dedicated

augm

entedWhittleindexstrategy

buterrorsareconsidered

CCC,incum

bent

protectio

nwith

outa-prioryknow

ledge

mechanism

ofPU

traffic

[82],2

011

Spectrum

sensingandsharing,

Use

ofone-slot

mem

oryto

obtain

Singlechannel(no

CC)

Sensingalgorithm

isnotd

escribed

Channelutilizatio

nrate

interference

constraint

tothePU

sdecision

inform

ationin

lasttheslot

buterrorsareconsidered

[83],2

012

Spectrum

sensingandsharing

Makefulluseof

pastsensing

Noinform

ation

Sensingalgorithm

anderrors

Throughput,collisionsperslot,

access

experience

arenotconsidered

spectrum

efficiency



Table 5 Different approaches regarding channel access issues

Ref. Objective Solution approach CC mechanism Spectrum sensing Performance metric

[86], 2013 Dynamic channel access, An algorithm using FSM for Dedicated CCC Sensing algorithm Throughput, sensing

PU interference constrain sensing schedule generation is considered but overhead

for data channel and channel selection errors are

considered

[87], 2013 Channel access, A prepare-to-sense frame is Realistic CCC Sensing algorithm Throughput, packet

incumbent protection incorporated to perform adopted by is not described service time, packet

mechanism asynchronous spectrum guaranteed but errors are delay

sensing and a blocking access model considered

method is proposed with

exponential back-off

mechanism

[88], 2009 Fairness issue Markov chain framework Dedicated CCC Sensing algorithm Aggregate throughput,

where priority is set based and errors are not packet transmission

on volume and urgency of considered delay

traffic to adjust contention

window

[89], 2014 Adjacent-channel Integrate guardband-aware Dedicated CCC Sensing algorithm Spectrum efficiency,

interference channel assignment and errors are not throughput, blocking

algorithm considered rate, energy

consumption

also developed. Table 6 summarizes different approaches ofOSA MAC protocol that avoid the use of dedicated CCC.

3.7 Reliable control channel assignment

Since CC establishment is challenging due to differentaspects such as coverage, saturation and security [46],some researchers propose a hybrid approach to balancethese shortcomings. In [38], a novel dynamic de-centralizedhybrid DDH-MAC protocol is proposed. This is designedwith the best attributes of global common control chan-nel (GCCC) but avoid the saturation and security issuesof GCCC by being non-GCCC algorithm. This protocolpartially utilizes GCCC to broadcast a beacon frame thatcontains information about primary control channel (PCCH)for control message exchange and backup control channel(BCCH) when a PU disrupts PCCH. Another interestinghybrid MAC protocol based on 802.11 DCF is proposedin [100]. Here, both common control channel and channelhopping schemes are utilized for reliable CCs assignment.Another hybrid MAC protocol that works between in-bandand out-of-band CCC, is proposed in [101] to improvethe performance of CRNs with respect to CR node syn-chronization, multi-channel hidden terminal and networkconnectivity time. This provides a trade-off between in-band CCC-MAC protocols with higher PU free channelsand saturated unlicensed out-of band CCCMAC protocols.

Table 7 summarizes different approaches of OSA MACprotocol that provide reliable control channel assignment.

3.8 Spectrum mobility

Characterizing spectrum mobility of CRNs is a challengingtask because of the heterogeneous environment. The mainpurpose of spectrum mobility is to carry out seamless spec-trum switching while maintaining ongoing SU transmission.Therefore, spectrum mobility can be envisioned as a combi-nation of two processes: spectrum handover and connectionmanagement. These can be broadly categorized as eithercontinuing on the same channel (buffering) or switch overto a new vacant channel (switching) as soon as PU reclaimsthe channel temporarily occupied by SU. In [67] the authorshave described MAC protocols for CRNs into two majorclasses according to how the SU deals with the suddenappearance of the PU: buffering and switching. In [68],the authors extended the work by introducing the collab-orative spectrum sensing process. Energy detection basedspectrum sensing architecture is decomposed into layersin [102], where each layer is parameterized and, classified.A novel protocol called truncated time division multipleaccess (TTDMA) is proposed that supports efficient distri-bution of sensing results using K-out-of-N fusion rule [103].In order to handle sudden PU appearance efficiently withBC, a new contention-based multi-channel MAC protocol



Tabl

e6

Different

approaches

thatavoidtheuseof

dedicatedCCC

Ref.

Objectiv

eSo

lutio

napproach

CCmechanism

Spectrum

sensing

Performance

metric

[36],2

012

Avoidingtheuseof

dedicatedCCC

TwolevelC

S-MACAoperation

NodedicatedCCC

Sensingalgorithm

and

Aggregatethroughput,

basedon

slow

common

hopping

errorsarenot

packetdelay

forCoordinator-based

CRN

considered

[90],2

013

Avoidingtheuseof

dedicatedCCC

Concurrentm

ultip

leaccess

basedon

NodedicatedCCC

Sensingalgorithm

and

Throughput,channel

split

phasewhere

sorted

channellist

errorsarenot

access

delay,network

isused

forprioritized

control

considered

connectiv

ity.

message

exchange

andcommon

channellistfor

faster

reservation

[91],2

009

Avoidingtheuseof

dedicatedCCC

Channelindexing

basedon

available

NodedicatedCCC

Sensingalgorithm

and

Aggregatethroughput,

bandwidth

formostreliableCCC

errorsarenotconsidered

networkconnectiv

ity[92],2

010

Avoidingtheuseof

dedicatedCCC

Multi-channelp

ream

blereservation

NodedicatedCCC

Sensingerrorsarenot

Normalized

throughput,

schemewith

multichannelcarrier

considered

packetdeliv

eryratio

sensingprincipleanddistributed

channelselectio

nalgorithm

[44],2

007

Avoidingtheuseof

dedicatedCCC,

Dynam

icRCbasedon

reliabilityand

Dynam

icRC

Sensingalgorithm

and

Aggregatethroughput

incumbent

protectio

nmechanism

useof

BCby

in-bandandout-of-band


measurementsviaQPs

[93],2

010

Avoidingtheuseof

dedicatedCCC,

Use

ofdynamically

adjusted

signaling

Dynam

icRC

Sensingalgorithm

and

Join

time,throughput

incumbent

protectio

nmechanism

sslots,dedicatedbeacon

slot

and


leader

selectionapproach

[95],2

011

Avoidingtheuseof

dedicatedCCC,

Anovelstochastic

schemebasedon

NodedicatedCCC

Sensingalgorithm

isnot

Accessfailu

rerate,access

incumbent

protectio

nmechanism

sMarkov-Chain

Monte-Carlo

approach

considered

buterrorsare

overhead,throughput,

andapower

controlledRTS/CTS

considered

packetdelay

exchange

mechanism

with

contentio

nresolutio

nanddatafragmentatio

n

method

[94],2

014

Avoidingtheuseof

dedicatedCCC,

AnovelR

TS/CTShandshakescheme

Blin

dRC

Sensingalgorithm

and

Expectedtim

eto

slot-asynchronousrendezvous

during

channelh

opping

processwith


handshake

optim

altim

eslot

interm

sof

shortest

timeto

handshake

[97],2

011

Avoidingtheuseof

dedicatedCCC,

Achannelstatustableisused

andhighest

NodedicatedCCC

Sensingalgorithm

and

Aggregatedthroughput,

incumbent

protectio

nmechanism

s,ranked

CCisselected

asCCCand


packetdelay,

channelselectio

nsecond

highestC

Cas

datachannel

connectiv

ityaccordingto

availability

[98],2

010

Avoidingtheuseof

dedicatedCCC,

SUscooperateperiodically

tosensechannels,

NodedicatedCCC

Sensingalgorithm

and

Channelutility

and

coexistenceof

PUsandSU

sin

CRNs

reportchannelstatesandexchange

control


capacity

signalsin

aNDCCapproach



Table 7 Different approaches that provide reliable control channel assignment

Ref. Objective Solution approach CC mechanism Spectrum Performance

sensing metric

[38], Reliable Hybrid between GCCC and non-GCCC families, Hybrid approach Sensing Pre-transmission time

2011 control channel partial use of GCCC to broadcast beacon that contain algorithm and

assignment information about PCCH, BCCH and multiple levels errors are not

of secure transmission using dedicated local CC considered

[100], Reliable Hybrid protocol of using CCC and channel hopping Hybrid approach Sensing Throughput, collision

2012 control channel where multiple control channels are used indepen- algorithm and rate, connectivity

assignment dently for channel negotiation and channel hopping errors are not

is executed only for control channels considered

[101], Reliable Hybrid between in-band and out-of-band CCC with Hybrid approach Sensing Aggregate

2014 control channel respect to CR node synchronization, multi-channel algorithm and throughput, packet

assignment hidden terminal and network connectivity time errors are not delay

considered

named opportunistic spectrum access with backup channel(SWITCH) is developed in [104]. To cope with the appear-ance of the PUs, another unaided rendezvous, asynchronousand contention-based multi-channel MAC protocol namedopportunistic spectrum access with backup channel andbuffered data with resume (OSA-BR) is proposed in [69].To combat the major drawbacks associated with CCC,this protocol exploits the blind rendezvous algorithm [105]under the PUs activities where all channels are availablefor exchanging information and establishing data commu-nications. Table 8 summarizes different approaches of OSAMAC protocol for spectrum mobility.

3.9 Analysis of delay and quality of service (QoS)provisioning

QoS provisioning is essential for satisfactory service, espe-cially in a multimedia environment where different mediashave difference attributes. For, example real time voice

communications is very sensitive to delay. Hence, delayis another significant metric for designing OSA MAC. Itincorporates queueing delay and transmission delay. Themain aim of QoS provisioning in OSA MAC design isto guarantee a minimum delay, reduction in jitter andpacket loss. Different researchers have dealt this problemdifferently. In [106] the authors focused on SUs queue-ing delay analysis based on a stochastic fluid queueapproximation approach [107]. The system is mod-eled using Poisson driven stochastic differential equa-tions and characterized the moments of the queuelengths of SUs. In order to optimize transmission delayperformance considering traffic characteristics of SUs,the authors of [108] proposed contention based multi-channel OSA MAC protocol. This protocol exploitsresource reservation mechanism to improve QoS require-ments that support important data traffic transmission ofSUs for some successive time slots without interferingPUs.

Table 8 Different approaches for spectrum Mobility

Ref. Objective Solution approach CC mechanism Spectrum sensing Performance

metric

[67], Handling sudden Use buffering or switching Both DCC and HCC Energy detection is used but Throughput

2010 appearance of PUs errors are not considered

[68], Handling sudden Joint spectrum sensing and use Both DCC and HCC Energy detection is used and Throughput

2011 appearance of PUs buffering or switching errors are considered

[104], Handling sudden Use backup channel Dedicated CCC Cooperative sensing but algo- Throughput

2012 appearance of PUs rithm and no errors are not con-

sidered

[69], Handling sudden Use backup channel and No dedicated CCC, Energy detection is used but Throughput, dropping

2014 appearance of PUs buffered data to resume use blind rendezvous errors are not considered. probability, commu-

algorithm nications overhead



To improve the delay-QoS provisioning over CRNs,the authors of [109] proposed cross-layer based oppor-tunistic multi-channel MAC protocol. Two collaborativespectrum-sensing policies, the random sensing policy andthe negotiation-based sensing policy, are also proposed toattain the channel state correctly. Markov chain model andM/GY /1-based queueing model are exploited to charac-terize the protocol performance for both saturated networkand un-saturated network settings. A throughput analysis isperformed in [110] in the presence of saturated traffic byutilizing buffering and switching policies [68]. The authorsalso provide a comprehensive delay and queuing analysisunder unsaturated traffic.

In [111] a throughput aimed MAC (T-MAC) with QoSprovisioning and a power control scheme that renders im-proved space reuse efficiency are proposed based onTDMA slot assignments. For efficient channel access, anopportunistic spectrum access MAC (OSA-MAC) is pro-posed in [112] that utilizes the idea of power savingmechanism (PSM) in 802.11 DCF. Two channel selec-tion schemes are included, namely uniform channel selec-tion and spectrum opportunity-based channel selection. Theauthors in [113] provide some improvements over previouswork where 1) the broadcast mechanism avoided colli-sion resulting from several communication pairs selectingthe samel channel and 2) an innovative contention schememade all SUs to possess the same opportunity for datatransmission.

For efficient spectrum utilization and QoS provision-ing of delay sensitive applications, in [114], an oppor-tunistic multi-channel MAC (OMC-MAC) for distributedCRNs is proposed. Here, a method for calculating priori-tized applications during channel reservation is exploited todesign admission control modules. In order to support datarate sensitive applications for QoS provisioning, a novelCSMA/CA-based multichannel cognitive radio mediumaccess control (MCR-MAC) protocol is devised in [115].Here, IEEE 802.11 DCF is modified to dynamically assignavailable channels to SUs by an inventive random arbitra-tion scheme. The authors in [116] provide an improvementof MCR-MAC protocol by incorporating packet size varia-tion in accordance with the level of PUs distraction to limitinterference.

For efficient spectrum usage and QoS provisioning, agroup based MAC protocol is proposed in [117] where,SUs are split into a number of non-overlapping groups. Theexisting channels are shared among these groups accord-ing to their bandwidth requirements. In order to maintainefficient wireless link establishment and reliable transmis-sion for QoS provisioning, an orthogonal frequency divi-sion multiple access (OFDMA) based cross layer MACprotocol (LM-MAC) is proposed in [118] where a fatherspectrum list (FSL) with different functional sub-channels

like redundant sub-channels (RSC), backup sub-channels(BSC) and data sub-channels (DSC), are devised to compen-sate packet loss and enhance channel quality. Three accessmechanisms, first access, continuous access and intermittentaccess, are adopted and a quasi-synchronous access algo-rithm (QSAA) [119] is used to avoid direct contention overCCC directly after sensing process. Table 9 summarizes dif-ferent approaches of OSA MAC protocol for delay analysisand quality of service (QoS) provisioning.

3.10 Multi-hop communication

Most of the OSA MAC protocols found in the literature areproposed for single hop domain. There are some approachesin the literature where the authors especially focus onmulti-hop domain for OSA MAC protocol. A common-hopping-based MAC protocol called synchronized MAC(SYN-MAC) is proposed in [120] for multi-hop CRNsthat is pertinent in heterogeneous environment. The ideabehind the protocol is to divide the total time into groupsof fixed time slot where number of slots represent num-ber of available channels. Using synchronized time slots, allSUs negotiate for a channel to exchange control informationwhich can vary with time and the following data transmis-sion occurs in asynchronous fashion using random channelaccess schemes. In order to address interference-dependentcontention resolution problem for OSA MHCRNs, a newoptimal cross-layer cognitive MAC (OCC-MAC) frame-work is proposed in [121]. This protocol incorporatesfew auxiliary variables that are interpreted as interferenceweights and noisy channel estimations. Table 10 sum-marizes different approaches of OSA MAC protocol formulti-hop communication. Table 11 shows characteristicfeatures based on classification of CR MAC protocol thatare described in the literature. Since the focus of this paper ison decentralized overlay approaches, other features such aschannel usage strategy, access method, allocation behavior,number of RFEs and network topology of MAC protocolsare summarized to provide a clear outlook regarding thoseaspects.

4 Standardization endeavor regarding CR-MACengineering

There has been significant and momentous developmentin the spectrum regulation paradigm to tackle the grow-ing demand for radio communication provisions during thepast few years. The regulatory and standardization authori-ties, such as international telecommunications union (ITU),IEEE, and European telecommunications standards institute(ETSI), have arranged abundant consultations, accumulatedconcerns and proposals regarding various CR usages, that



Tabl

e9

Different

approaches

fordelayAnalysisandQoS

provisioning

Ref.

Objectiv

eSo

lutio

napproach

CC

Spectrum

sensing

Performance

metric

mechanism

[106],

Queueingdelayperfor-

Adaptivealgorithm

basedon

stochastic

Noinform

a-Sensingalgorithm

Queueingdelay,traf-

2012

mance

ofSU

sfluidqueueapproxim

ation

tion

anderrorsnotare

ficadmission

proba-

considered

bility

[108],

Transmission

delaycon-

Resourcereservationincorporatingback-

Dedicated

Sensingalgorithm

Transmission

delay

2012

sidering

trafficcharacter-

offmechanism

CCC

anderrorsnotare

istic

sof

SUs(Q

oS)

considered

[109],

Throughputand

delay

MarkovchainmodelandM/G

Y/1-based

Dedicated

Sensingerrorsarenot

Throughput,packet

2008

analysisforQoS

queueing

modelareexploitedunderran-

CCC

considered

transm

ission

delay

provisioning

dom

sensingpolicyandnegotiatio

n-based

sensingpolicy

[110],

Delay

andqueueing

anal-

Queue

occupancyMarkovChain

model

Dedicated

Sensingalgorithm

System

time

2015

ysisforbufferingand

andaservicecycleanalysisbasedon

CCC

anderrorsnotare

switc

hing

Geom/M

/1queue

considered

[111],

QoS

provisioning

StrictTDMAslot

synchronization,

power

Dedicated

Sensingalgorithm

Throughput,access

2010

controlschem

e,protectio

nof

dataand

CCC

anderrorsnotare

delay

controlp

acketsby

exclusiveACKfram

esconsidered

[112],

QoS

provisioning

Uniform

channelselectio

nandspectrum

Dedicated

Sensingalgorithm

isThroughput,collision

2008

opportunity

-based

channelselectio

nare

CCC

notconsideredbuter-

probability

with

PUs

used

alongwith

PSM

in802.11

DCF

rorsareconsidered

[113],

Spectrum

utilizatio

n,QoS

Broadcastmechanism

,innovativecon-

Dedicated

Sensingalgorithm

isThroughput

2009

provisioning

tentionscheme

CCC

notconsideredbuter-

rorsareconsidered

[114],

QoS

provisioning

ofdelay

Prioritized

applications

during

channel

Dedicated

Sensingalgorithm

isThroughput,collision

2011

sensitive

applications

reservation

CCC

notconsideredbuter-

probability

with

PUs

rorsareconsidered

[116],

QoS

provisioning

fordata

Random

arbitrationschemeby

modify-

Nodedicated

Sensingalgorithm

Throughput,collision

2012

ratesensitive

applications,

ingthe4-way

handshakingbasedIEEE

CCC

anderrorsnotare

probability

with

PUs

incumbent

protectio

n802.11

DCFandpacketsize

variation

considered

mechanism

sbasedon

PUsinterruptio

nto

limitinter-

ference

[117],

Spectrum

utilizatio

nand

Dynam

icchannelallo

catio

nby

group

Dedicated

Sensingalgorithm

Throughput

2008

QoS

provisioning

basedarchitectureconsideringbandwidth

CCC

anderrorsnotare

requirem

ents

considered

[118],

QoS

provisioning

forlin

kThree

access

mechanism

sandFS

Lalong

Dedicated

Cooperativ

esensing

Saturatio

n2015

maintenance

with

differentfunctionalsub-channelsare

CCC

isappliedandsensing

throughput,access

designed

errorsareconsidered

delay,continuity

prob

ability



Table 10 Different approaches for multi-hop communication

Ref. Objective Solution approach CC Spectrum Performance metric

mechanism sensing

[120], Avoiding the use of dedi- Common-hopping-based hybrid channel ac- No Sensing Aggregate throughput,

2008 cated CCC, spectrum het- cess where control message exchange follows dedicated algorithm and network connectivity.

erogeneity synchronized slotted transmission and data CCC errors not are

exchange use un-synchronized random access considered

[121], Channel contention reso- A distributed solution using some auxiliary Dedicated Sensing Social welfare, PU target

2013 lution, incumbent protec- variables that are interpreted as interference CCC algorithm and collision probability, fair-

tion mechanism, fairness weights and noisy channel estimations errors not are ness index

issue considered

lead towards the evolution of standardization and technicalresolutions.

The IEEE 802.22WRAN standard [122] defines the poli-cies and procedures for the operation in spectrum allocatedto the television broadcasting service in the frequency rangeof 54 MHz to 862 MHz. It includes the MAC and PHYlayer of the fixed and portable point-to-multipoint WRANsthat integrate CR technology. Recently, there have been twoamendments of the standard, i.e. the IEEE 802.22a and theIEEE 802.22b amendments to further enhance it [123]. TheIEEE 802.22 standard and its two amendments describe thecognitive capabilities that are attained by utilizing a spec-trum manager along with the functionalities such as spec-trum sensing, channel set management, incumbent databaseservice and geo-location management, and self-co-existencemechanism. It also includes enhanced broadband services(e.g. remote medical service) and monitoring use (e.g. smartgrid).

The IEEE 802.11af standard [8] is aimed to allow IEEE802.11 wireless local area networks (WLANs) to be uti-lized in white spaces of the RF spectrum. The added featuresof IEEE 802.11af are devised to offer geolocation databaseaccess to previously unavailable, unused or under-used fre-quencies. The amendment to IEEE 802.11 establishes aglobal standard with a new cognitive radio tool for theirspectrum-sharing toolbox that allow users worldwide tomake use of unused or under-used spectrum, based onlocation and time of the day.

The regulatory arrangements such as authorized sharedaccess (ASA) [124] and licensed shared access (LSA) [125]provide a controlled framework for spectrum sharing, thatincreases spectrum utilization in an authentic way. The LSAconcept is a complementary approach that may take use ofCR technology to adapt to the varying spectrum availabil-ity, particularly in the form of a geolocation database [126].The LSA concept has been successfully applied with alive LTE network in the 2.3 GHz shared band [12] butthe first standardization studies are done by ETSI that arereported in [11]. LTE or the E-UTRAN (evolved universal

terrestrial access network), introduced in the third gener-ation partnership project (3GPP) release 8 (Rel-8) [127].This is the access part of the evolved packet system (EPS).Note that the main requirements for the new access net-work are high spectral efficiency, high peak data rates,short round trip time as well as flexibility in frequency andbandwidth. Compared to the legacy technologies such asLTE Rel-8, LTE-advanced release 10 (Rel-10) [127], tar-gets the achievement of 1 Gb/s downlink and 500 Mb/suplink throughput [128]. The performance improvements ofLTE-advanced are achieved with advanced physical layertechniques including enhanced interference coordinationtechniques, and enhanced multiple-antenna schemes [129].Thus 3GPP’s potential efforts towards LTE-advanced, areexpected to be the dominating standard on the mobile com-munication system in near future. The carrier aggregation(CA) features of LTE-A can be exploited for enabling a cog-nitive operation in a subset of component carriers [130].Using CA, an operator can aggregate up to 5 component car-riers of 20 MHz each [131], thus cognitive spectrum sharingbecomes particularly interesting in the context of CA inLTE-A systems.

The IEEE 802.15 task group 4m (TG4m) [13] isemployed to specify a physical layer for 802.15.4 and todevelop and add functional operations to the existing stan-dard 802.15.4-2006 MAC meeting the TV white space reg-ulatory requirements. The amendment enables operation inthe available TV white space, supporting typical data ratesin the order of 40 kbps-2000 kbps, to recognize optimal andpower efficient communication in large scale command andcontrol applications.

5 Future research directions

Ongoing research focuses on improving the performance ofthe OSA-MAC protocols for CRN. We discuss some of themajor topics in this domain. Figure 6 shows the potentialroadmap of OSA MAC schemes for CRNs.



Table 11 Taxonomy of OSA MAC protocol characteristic features

Ref. Usage strategy Access method Allocation RFEs Topology

behaviour

[52], 2014 Single channel Hybrid Non-cooperative Single radio Single hop

[53], 2013 Single and Hybrid Non-cooperative Single and two radios Single hop

multi-channel

[54], 2009 Multi-channel Hybrid Non-cooperative Two radios Single hop


[56], 2008 Multi-channel Hybrid Cooperative Single half-duplex Single hop

[57], 2007 Multi-channel Contention-based(CSMA/CA) Non-cooperative Two radios Single hop


[60], 2005 Multi-channel Contention-based Non-cooperative Threeo radios Single hop

(non-persistent CSMA)

[61], 2008 Multi-channel Time-slotted(Channel hopping) Non-cooperative Single radio Single hop

[62], 2010 Multi-channel Hybrid Non-cooperative Single radio Single hop

[63], 2013 Single channel Time-slotted Non-cooperative Single radio Single hop

[64], 2008 Multi-channel Contention-based(CSMA/CA) Non-cooperative Single radio Single hop

[65], 2011 Multi-channel Hybrid Non-cooperative Two half-duplex-radios Single hop

[75], 2009 Multi-channel Time-slotted Cooperative Single radio Single hop



[78], 2009 Single channel Hybrid Non-cooperative No information Single hop

[37], 2008 Multi-channel Contention-based(CSMA/CA) Non-cooperative Single half-duplex radio Single hop

[79], 2007 Multi-channel Hybrid Non-cooperative Single radio Single hop

[80], 2009 Single and Time-slotted Non-cooperative Single radio Single hop

multi-channel

[82], 2011 Single channel Time-slotted Non-cooperative Single radio Single hop

[83], 2012 Multi-channel Time-slotted Non-cooperative Single radio Single hop

[86], 2013 Multi-channel Time-slotted Non-cooperative Two radios Single hop

[87], 2013 Single and Contention-based(CSMA/CA) Non-cooperative No information Single hop

multi-channel

[88], 2009 Multi-channel Contention-based Cooperative Two radios Single hop

(p-persistent CSMA)

[89], 2014 Multi-channel Contention-based(CSMA/CA) Cooperative Single half-duplex radio Single hop

[36], 2012 Multi-channel Contention-based(CS-MACA) Cooperative Single radio Single hop

[90], 2013 Multi-channel Time-slotted Non-cooperative Two radios Single hop

[91], 2009 Multi-channel Contention-based(CSMA/CA) Non-cooperative No information Single hop

[92], 2010 Multi-channel Contention-based(CSMA) Non-cooperative Single half-duplex Single hop

[94], 2014 Multi-channel Hybrid Non-cooperative Single half-duplex Single hop

[98], 2010 Multi-channel Contention-based(CSMA/CA) Cooperative Single Radio Single hop

[38], 2011 Multi-channel Contention-based(CSMA/CA) Non-cooperative Two half-duplex radios Single hop

[100], 2012 Multi-channel Contention-based(CSMA/CA) Non-cooperative No information Single hop

[101], 2014 Multi-channel Time-slotted Non-cooperative Single half-duplex Single hop

[67], 2010 Multi-channel Time-slotted Non-cooperative Single radio Single hop

[68], 2011 Multi-channel Time-slotted(TTDMA) Cooperative Single radio Single hop

[104], 2012 Multi-channel Contention-based(CSMA/CA) Cooperative Two radios Single hop

[69], 2014 Multi-channel Contention-based(CSMA/CA) Cooperative No information Single hop

[106], 2012 Multi-channel Contention-based(Slotted ALOHA) Non-cooperative Single and two radios Single hop

[108], 2012 Multi-channel Contention-based(CSMA/CA) Non-cooperative Two radios Single hop

[110], 2015 Multi-channel Time-slotted(Slotted ALOHA) Non-cooperative Single radio Single hop



Table 11 (continued)

Ref. Usage strategy Access method Allocation RFEs Topology

behaviour

[111], 2010 Multi-channel Time-slotted Non-cooperative Single half-duplex radio Single hop

[112], 2008 Multi-channel Time-slotted (CSMA/CA, PSM) Non-cooperative Single radio Single hop

[114], 2011 Multi-channel Contention-based(CSMA/CA) Non-cooperative Single half-duplex radio Single hop

[116], 2012 Multi-channel Contention-based(CSMA/CA) Non-cooperative Single radio Single hop

[117], 2008 Multi-channel Hybrid Cooperative Two half-duplex radio Single hop

[118], 2015 Multi-channel Hybrid Cooperative Single half-duplex radio Single hop

[186], 2011 Multi-channel Hybrid Non-cooperative Single half-duplex radio Single hop

[120], 2008 Multi-channel Hybrid Non-cooperative Two radios Multi-hop

[121], 2013 Multi-channel Hybrid Non-cooperative Two radios Multi-hop

5.1 Spectrum sensing issues

5.1.1 Spectrum opportunities discovery

Discovery process of spectrum need to be carried out morecarefully because it is influenced by three main issues: thehidden transmitter, the exposed transmitter and the hiddenreceiver. The hidden transmitter issue has been resolvedby carrying out sensing operation at both transmitter andreceiver ends, but there are still no satisfactory solutions forthe latter issues. A CR user should be capable of discovering

the existence of a neighboring primary receiver to resolvethese issues. Hence, feasible solutions for this purpose areyet to be investigated.

5.1.2 Sensing performance

Spectrum sensing performance is limited by hardwareand physical constraints. For instance, SUs with a sin-gle transceiver cannot transmit and sense simultaneously.Moreover, users usually only observe a partial state ofthe network to limit sensing overhead. There is a fun-

Fig. 6 The future roadmap ofOSA MAC schemes for CRNs



damental trade-off between the undesired overhead andspectrum holes detection effectiveness: the more bands aresensed, the higher the number and quality of the availableresource. Thus this problem needs to be further investigatedto improve spectrum sensing effectiveness.

5.1.3 Sensing errors

Sensing errors due to false detection and miss detectionin PU signal sensing are ignored in many cases in the lit-erature. Accurate models that take both false alarm andmis-detection probabilities into account, need to be devised.Therefore, the simplified ON/OFF model for PU traffic maynot be a proper choice for practical environment wherePUs may be cellular or wireless sensors. To improve theprobability of detection with less sensing errors, coopera-tive techniques have been proposed [66]. However, manyaspects of cooperative sensing need to be still investigatedfor better solutions [51]. Future OSA-MAC protocols haveto incorporate more complex considerations such as theimpact of correlation among sensing channels, imperfect-ness of reporting channels etc. to develop more efficientcooperative sensing schemes [132]. Furthermore, trade-offbetween sensing action and throughput as well as otherapplications such as multimedia application over CRNsneeds to be further investigated.

5.1.4 Utilization of other decision theoretic schemes

For OSA systems, POMDP is the most popular tool forautomated decision-making that notifies CR users whataction to perform. This two-dimensional framework isused to solve a situation by considering the channel qual-ity under fading environment [133]. Some other decisiontheoretic frameworks such as game theory [134], opti-mal stopping problem [135, 136] and multi-armed bandit(MAB) problem [137] can be incorporated with POMDPin order to address channel quality issues. These deci-sion theoretic frameworks can be utilized to constructbetter OSA MAC structures to address two or more chal-lenges simultaneously which form active areas for futureresearch.

5.2 Backoff algorithms

Backoff algorithms, part of MAC protocol, play a signif-icant role in decreasing packet conflicts, increasing suc-cessful transmission rate and overall throughput. Evaluationof a backoff algorithm mainly depends on two basic per-formance metrics: throughput and delay analysis. Due tovariation in network nodes, channel contention may varywhich consequently affects in selecting backoff values.Therefore, optimal backoff value selection becomes crucial

and challenging which leads to an open area for research.A new backoff algorithm based on the dynamic modulat-ing parameters is presented in [138] to improve the useof wireless channel for the competition. This algorithmuses a network performance of slot utilization indicator todescribe the current network state of competition. In orderto decrease the MAC overhead and the collision probabil-ity, in [139] a new backoff strategy is proposed leading tobetter saturation throughput and access delay performancecomparing to the classical protocol. Few attempts that arefound in the literature, which are not sufficient and urgentattention is needed for designing dynamic backoff algorithmin order to improve network throughput and to minimizedelay.

5.3 CC issues

CC in CRNs are radio resources provisionally assigned andcommonly accessible to CR users for control informationexchange. For CC establishment, CR users need cooper-ation among spectrum management functions. CC designand assignment become more difficult by the impacts of PUactivities, transmission impairments and intelligent attacks.Therefore, reliable and secure establishment of CC for effi-cient and seamless communication in CRNs is a very crucialand challenging task. In order to enhance awareness ofPU activities, a competent control channel design is neces-sary [140]. This will enable efficient establishment of con-trol links as well as extension of control channel coverageupon PUs detection to protect from interference. Transmis-sion impairments like multipath fading and shadowing inCCs have considerable impact on PU detection capabilities.Cooperative sensing [132, 141] can be treated as an effec-tive solution to combat transmission impairments which canhowever incur delay and overhead in the network. There-fore, self-organized [142] and robust cooperative sensingschemes [143] for CCC allocation need to be investigated inorder to enhance cooperative gain and minimize overheadand delay.

Utilization of single dedicated CC is more prone tosecurity attacks such as control channel jamming denialof service attacks [144]. This may devastate the wholenetwork with single point of failure [145]. Moreover, tra-ditional schemes like channel hopping may not be ableto mitigate jamming under PUs activities and sensingerrors. Therefore, CC establishment become another cru-cial issue. A scalable mechanism [146] incorporating reli-ability and security issues needs to be developed forimproved control channel assignment by increasing com-munication and sensing abilities. Hence, a complete frame-work for CCC design and allocation need urgent attentionfor further investigation in order to provide innovative CCsolutions.



5.4 Cross-layer design approaches and security issues

In CRNs, superior interaction is needed between differ-ent layers of protocol stacks in order to attain desiredgoals and performance in terms of radio resource man-agement, QoS provisioning, security and other networkobjectives. The idea behind the Cross-layer design [147]approach refers to devise the protocol stack by exploitingthe information exchange and reliance between differentprotocol layers to acquire superior performance. But at thesame time, it will also be susceptible to cross-layer attackswhich may happen due to malevolent operations executedat one layer that could cause security violations at anotherlayer [148]. CRNs inherently require greater interactionbetween different layers of the protocol stack. Therefore,cross-layer attacks and security related issues [149] includ-ing jamming attack and mitigation, selfish behavior incollaborative sensing and misbehavior in detection, physi-cal layer and MAC layer in security, and the modeling anddetection of insider attacks should be given special atten-tion. A cross-layer security mechanism that incorporatesrecent advances on security threats/attacks and counter-measures, need to be investigated in OSA MAC designin order to permit a reliable and secure environment forCRNs [150]. Finally, the application of artificial intelli-gence (AI) techniques can be included in OSA MAC designto tackle security challenges for dynamic spectrum access[151].

5.5 Spectrum mobility issues

Spectrum mobility is also an essential issue in OSA MACdesign aspect. Studies in the literature incorporate severaldesign issues such as PU detection, handoff decision, tar-get channel selection and spectrum handoff strategy [152].Spectrum sensing speed and precision that greatly influ-ence PU detection event, can be increased by cooperativesensing [153]. Handoff decision is another important issuewhich can cause harmful interference to PU. This can begreatly improved by using proper handoff algorithm e.g. fuzzy logic based algorithm [154]. Appropriate targetchannel selection approaches in the literature include hav-ing a backup channel, target channel availability predictionunder partial sensing scheme and selection utilizing his-torical data. PU traffic modeling taking PU mobility [155]into account needs careful attention in order to intelli-gently select the target channel by SUs. Several predictionand estimation schemes [156], like hidden Markov mod-els [157], neural networks [158], Bayesian inference [159]and, autoregressive model [160] can be adopted for betterrealization of PU activity. Proper spectrum handoff strate-gies need to be chosen that are adaptive in nature according

to PU traffic. In order to minimize delay in handoff event,simultaneous data transmission in multi-channel CRNs needto be performed. Effective contention resolution for multi-ple SUs during handoff need to be carried out for successfulhandoff. Cross-layer approach for link maintenance is nec-essary to effectively address mobility issues in physical,MAC and network layers. Finally an integrated handoffmanagement process [161] is necessary to improve networkperformance.

5.6 Multi-hop scenario

Dynamic spectrum access in multi-hop domain incorporatesseveral challenges in MAC layer. Several studies [162, 163]in the literature tried to bring up research issues regard-ing OSA MAC design for multi-hop CRNs which canbe summarized as 1) control channel establishment andmanagement scheme without a predefined dedicated con-trol channel, 2) transceiver synchronization, 3) CTS timeoutand problems in decoding CTS, 4) multi-channel hiddenterminal problem, 5) hidden incumbent node problem, 6)number of transceivers, 7) coordination of spectrum sensingand accessing decision making, 8) radio frequency het-erogeneity 9) group communication and 10) MAC layerauthentication. Some other attributes like the effect ofchannel state information in spectrum access, QoS guar-antee, concern in fairness aspect, PU protection also needcareful attention and further investigation in multi-hopenvironment.

5.7 Quality of service (QoS) management in CRenvironment

Spectrum utilization and network capacity of CRNs canbe increased by dynamic spectrum supervision. However,this imposes several challenges in QoS management [164].Users can exploit available spectrum successfully capturedby a CR but accurate information needs to be forwarded tothe application to amend traffic features and user require-ments. Once the available frequency bands are character-ized, the most suitable spectrum bands can be selected bytaking into account the spectrum characteristics and QoScriteria. However, spectrum characteristics can alter dueto the dynamic nature of PU traffic and network param-eters. Thus, appropriate spectrum decisions and necessaryinteractions among application streams, need to be per-formed to meet the QoS provisioning. Several QoS sup-portive MAC protocols are reported in the literature. Mostof the approaches assumed that PU traffic characteristicsare known by SUs. However, this may not be true in gen-eral. Hence, PU traffic parameter estimation needs to bedone often [165]. Such accurate estimation is necessary to



guarantee QoS criteria in terms of disruption caused to thePUs. Overall, further investigations are needed to designQoS supportive MAC schemes for CRN based on differentcriteria.

5.8 Multi-purpose OSA MACs

Depending on the requirements of CRNs, the purpose ofOSA MAC protocols may differ in nature. Some pro-tocols are devised with the goal of offering throughput-maximization or delay-minimization while some othersintending at energy-efficiency. However, each protocol ispreferred in its specific goal. Therefore, adaptive frame-works that alter the objectives according to the CR proper-ties and applications are necessary in order to fulfill multipleobjectives at different levels. This adaptive property is moreappropriate to the nature of CRNs which is presumed tobe agile. Agility mainly refers to the competence of CR toadjust functional parameters and also to the nimbleness inthe protocol stack. In other words, SUs can switch its MACprotocol stack depending on its purpose. Hence, spectrumagility in OSA MAC protocols requires adaptability andclose PHY-MAC interaction [166] which brings up a newresearch dimension and challenges.

5.9 Green OSA MACs

Energy efficiency is another important objective whiledesigning OSAMAC protocol, especially in cognitive wire-less sensor networks. Usual research trends in OSA MACdesign has mainly been focused on the functional behav-ior and performance measurement, except on battery con-sumption. Green communications, aiming towards energyefficiency as a main concern, have therefore induced a newresearch horizon. Several investigations [167–170] are car-ried out in order to address different challenges regardingenergy efficiency, but still needs more attention to explorethis area. RF energy harvesting is another promising tech-nique to obtain enough energy and spectrum opportunity forpacket transmission. The spectrum access, that determinesthe channel for the SU to transmit a packet or to har-vest RF energy, is a critical component to achieve optimalperformance. Thus MAC protocols, developed for energyharvesting CRNs, are recently investigated [171] and offeran active area for research.

5.10 Cognitive heterogeneous networks (HetNets)

Cognitive heterogeneous networks (HetNets) are an attrac-tive solutions for expanding network capacity to multi-ple spectrum access technologies, network structures andcommunication protocols. Some applications such as tac-

tical applications in military communications [172], med-ical applications in CR-based wireless body area net-works [173], are few interesting recent applications ofcognitive HetNets. A thorough study of MAC protocol withthe capability of cognitive HetNets is still an open area ofresearch. However, only a few works address the issues ina coexistent heterogeneous CRNs scenario [174]. Since thesystem characteristics of these cognitive HetNets, are differ-ent in several categories such as spectrum sensing aspects,PU detection ability, hardware capacity, fairness issue, allthese categories need to be explored while designing MACstructure. A scenario of coexistent heterogeneous CRNswith collision-based PUs and fairness issue are discussedin [175]. Further research towards opportunistic 3G/4G/5Gspectrum sharing involve precise evaluation of the scenarioconditions, in terms of terminal confinement, link mainte-nance, and user preferences, and will also need to considerface side aspects such as security supervision and privacypreservation. The rising requirement of wireless data trafficand the scarceness of accessible radio spectrum, will extend3GPP’s LTE (Release 8) and LTE-Advanced (Release 10) tounlicensed bands (5 GHz). Thus dynamic spectrummanage-ment for LTE [176] and LTE-Advanced [177, 178] mobilecommunication network as a CR-ready technology, becomechallenging and provide an active area for research.

5.11 Cognitive machine-to-machine (M2M)communications

The CR research community has considered the machine-to-machine (M2M) communications, as one of the emergingand indispensable CR usage area. M2M communicationsreduce costs and provide considerable efficiency that affectindividual as well as industrial use with smart services,such as smart city, smart grid and, smart home [179]. Cog-nitive M2M communications can be envisioned as newparadigm in terms of efficient spectrum utilization due todynamic spectrum access capabilities [180]. In addition,cognitive M2M is intrinsically enriched to tackle the chal-lenges of spectrum scarcity issue due to huge and increas-ing number of devices, interference management, energyefficiency, network coverage issue and device heterogene-ity [181, 182]. Thus cognitive M2M opens new horizonby providing enormous unexplored field for researchers.Designing MAC protocols that effectively meet the M2Mservice requirements, along with integrating CR technol-ogy, become crucial and challenging. Only a few handfulstudies regarding MAC protocol, are found in the literaturesuch as data aided cognitive technique (DACT) protocol forcognitive M2M proposed in [183]. A receiver-based cog-nitive MAC protocol, termed as cognitive receiver-based(CRB)-MAC, has been proposed in [184] with special



emphasis on energy efficiency and reliability requirementsof M2M devices operating in challenging wireless environ-ments such as smart grid. The basic Packet ReservationMultiple Access (PRMA) is enhanced in [185] with novelmodifications especially tailored for cognitive M2M com-munication. Therefore, the ongoing research on structuringMAC framework for cognitive M2M is still in infancy.

6 Conclusion

Different OSA MAC protocols have different focus, crite-ria, objective, mechanism and performance issues. In thispaper, we explored different MAC schemes in OSA contextfor CRNs. The main contributions of this paper are fourfold.First, we pointed out differences of OSA MAC approachesfrom conventional MAC protocols and also figured out thebasic elements for OSA based MAC protocols. Second,we classified CR MAC framework based on different cri-teria and provided a generic OSA MAC design structurein CRNs. Third, we presented a comprehensive literaturereview of protocol objectives, solution approaches, charac-teristic features and performance metrics. Forth, we ana-lyzed and compared of these different schemes to highlightmajor attributes, outlined further research issues and chal-lenges, presented roadmap for future OSA MAC structure.

Acknowledgments The authors sincerely acknowledge the supportfrom Natural Sciences and Engineering Research Council (NSERC) ofCanada and support from the Ryerson University Faculty of Engineer-ing and Architectural Science Dean’s Research Fund.

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Ajmery Sultana ([email protected]) obtainedher master of science degreefrom University of Dhaka in2008. She is currently pursu-ing her PhD degree at RyersonUniversity. Her researchinterests are cognitive andcooperative communicationsystems.

Xavier N. Fernando([email protected], S’97-M’01-SM’04) received thePh.D. degree from the Uni-versity of Calgary, Canadain 2001. In 2001, he joinedRyerson University, where heis currently a Professor. Hehas authored or coauthoredclose to 100 research articles.

Prof. Fernando is a mem-ber of the IEEE COMSOCEducation Board WorkingGroup on Wireless Com-munications and an IEEEDistinguished Lecturer. He

has delivered invited lectures and tutorials worldwide. He is a Pro-gram Evaluator for ABET. He is the General Chair for the 2014 IEEECanadian Conference on Electrical and Computer Engineering. Hewas a member of Ryerson Board of Governors during 2010–2011 andthe Chair of the IEEE Toronto Section during 2012–2013. His workhas won several awards and prizes, including the IEEE HumanitarianInitiative Technology Workshop First Prize in 2014, IEEE MicrowaveTheory and Techniques Society Prize in 2010, Sarnoff SymposiumPrize in 2009, Opto-Canada Best Poster Prize in 2003, and CCECEBest Paper Prize in 2001.

Lian Zhao ([email protected], S99-M03-SM06) receivedher PhD degree from theDepartment of Electricaland Computer Engineering(ELCE) from University ofWaterloo, Canada, in 2002.She joined the Electricaland Computer EngineeringDepartment, Ryerson Uni-versity, Toronto, Canada,as an Assistant Professor in2003 and now is a Profes-sor. Her research interestsare in the areas of wire-less communications, radio

resource management, power control, cognitive radio and cooperativecommunications.


http://dx.doi.org/10.1002/ett.2955

to primary users (pus), ... very important example is ieee 802.22 wireless regional ... several...

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