Journal of Network and Computer Applications 35 (2012) 518–526

Contents lists available at ScienceDirect

Journal of Network and Computer Applications

1084-80

doi:10.1

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journal homepage: www.elsevier.com/locate/jnca

Cognitive maritime wireless mesh/ad hoc networks

Ming-Tuo Zhou �, Hiroshi Harada

Wireless Communications Laboratory, NICT Singapore Representative Office, 20 Science Park Road, #01-09A/10 TeleTech Park, Singapore 117674, Singapore

a r t i c l e i n f o

Article history:

Received 1 July 2010

Accepted 23 December 2010Available online 14 January 2011

Keywords:

Cognitive radio networks

Maritime communications

Mesh/ad hc networks

Maritime mesh networks

IEEE 802.16

White Space

45/$ - see front matter & 2011 Elsevier Ltd. A

016/j.jnca.2010.12.018

esponding author.

ail address: zhou.mingtuo@ieee.org (M.-T. Zh

a b s t r a c t

Cognitive maritime wireless mesh/ad hoc networks are proposed in this paper, for the purpose to

provide high-speed and low-cost communications for the current maritime users by incorporating the

licensed but unused frequency bands opportunistically. Compared to other technologies, this scheme

offers advantages of plenty of available bandwidth, easy installation, easy coverage extension, and high

resilience. Nodes design requirements, possibly available frequency bands, regulation requirements,

operation standards, and maritime communication challenges of the proposed networks are introduced

and analyzed. A cognition-enhanced mesh medium access control (MAC) protocol for the operation of

the proposed cognitive maritime mesh/ad hoc networks is presented, as well as a routing protocol and a

switching antenna design that are capable of meeting the maritime challenges. Simulation results show

that a higher detection probability and a longer sensing interval are both helpful to achieve better

network performance, especially in case of high sea state. The operators need to find balance among

cost, network performance, and protection of incumbents in the operation of the networks.

& 2011 Elsevier Ltd. All rights reserved.

1. Introduction

Nowadays, with the proliferation of Internet and variousinformation technologies, wireless broadband access has become anecessity in daily life and work. While wireless broadband access iscommonly available on land, it is not the case for users onboard aship. The current wireless communications at sea mainly rely on thesatellite links that are relatively slow and expensive. It is believedthat there is a strong need of high-speed and low-cost communica-tions at sea as that enjoyed on land (Pathmasuntharam et al., 2008).

To meet the above need, some new maritime communica-tion systems are emerging in recent years. In Singapore, WISE-PORT (WIreless-broadband-access for SeaPORT) provides a mobilewireless broadband access up to 5 Mbps based on 802.16e (Singa-pore’s Seaport To Be World’s First Wi-Max-Ready by 2008, 2007).However, the coverage distance is still short (up to 15 km fromSingapore’s southern coastline). In Norway, the world-first digitalVery High Frequency (VHF) network with data rate of 21 and133 kbps are developed and rolled out along the whole Norwegiancoast, and the coverage distance can be up to 130 km (Bekkadal).However, since it operates in the legacy marine VHF channel, thebandwidth is narrow and the speed is still low. Other systems basedon hybrid satellite and Digital Video Broadcasting (DVB) system mayhave a broad bandwidth (http://www.dvb.org/); however, they are

ll rights reserved.

ou).

also expensive as it requires a Television Receive Only (TVRO) ante-nna mounted onboard a ship.

We have envisaged a mesh/ad hoc network to provide high-speed and low-cost ship-to-ship/shore communication based onthe IEEE 802.16d Mesh technology in a project called TRITON(Pathmasuntharam et al., 2008). The network is formed byneighboring ships, marine beacons and buoys, and is connectedto the terrestrial networks via land stations that are regularlyplaced along the coastlines. As each mesh node can route andrelay traffic from others, the network coverage can be easilyextended. We have developed prototypes and carried out fieldmeasurements at frequency of 2.3 and 5.8 GHz (ITU-R WP 5B-3Maritime Group, 2009).

The difficulty of a maritime mesh/ad hoc network is to finddedicated operation spectrums due to the current congestedbandwidth allocations. The mesh/ad hoc stations on the landand ships nearby the coast may have to coexist with other radiodevices installed near the coastal region. Further more, as someships may travel across countries and continents, it is required tostill harmonize the frequency bands around the world for mar-itime mesh/ad hoc networking.

In this paper, we propose scheme alleviating the above spectrumissues in maritime communications by incorporating cognitive radiotechnologies. A high-level network architecture is presented, and thedesign requirements of the cognitive maritime mesh/ad hoc nodes toenable cognitive operations and suit the maritime environment areanalyzed. We also analyze the cognitive networking issues in mari-time environment, on topics of possible available spectrum ‘‘WhiteSpace’’ (WS), regulation requirements need to follow and possible

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available standards. The challenges for cognitive maritime mesh/adhoc communications are presented and analyzed, including the seasurface movement, the channel property, and the effect of the firstFresnel Zone. Further more, we present a medium access control(MAC) protocol that is developed for cognitive maritime mesh/ad hocnetworks, and introduce a routing protocol and a switching antennato meet the challenges of the maritime communication environment.Finally, simulation is performed to investigate the network perfor-mance as function of the important cognitive radio parameters likespectrum sensing detection probability and interval. Simulationresults are presented and analyzed.

Cognitive radio is a technology to allow the unlicensed users touse the licensed but unused frequency bands opportunistically(Mitola and Maguire, 1999). It is an effective method to improvethe usage efficiency of the spectrum and to mitigate the spectrumcongestion issue as illustrated by lots of research recently. Asanalyzed by the authors in this study, there is plenty of spectrumWS at sea. This provides a great opportunity for maritime users toopportunistically access the unused bands. The advantages ofdoing so are versatile. First, the spectrum scarcity issue can bealleviated—this is the most important point driving this study.Second, some WS frequency bands may offer large bandwidth andvirtues of propagation that are suitable for long range maritimecommunications, like the television WS (TVWS). Third, the cost ofmaritime communications can be saved as the operators possiblywill not pay for the spectrum license since they use the licensedbands opportunistically. This is good for maritime users ascurrently they pay high price for their maritime satellite commu-nications, e.g., 10USD per Mbyte in Singapore.

Regarding to the system architecture, we envisage three net-work scenarios. The first is the mesh/ad hoc network rolled outalong coastlines, where the ships at sea ports or narrow shippinglanes can be served. The second is ad hoc network at deep sea thatis formed by neighboring ships. The third is mesh network formedby the maritime facilities like sea farms, oil/gas platforms, etc. Forthe maritime cognitive mesh/ad hoc nodes, it is required beingcapable of sensing spectrum and (if necessary) accessing geoloca-tion/database to detect the channel availability. Moreover, itneeds the capability to meet the challenges in maritime environ-ment like two-ray ground channel model, unstable link qualitydue to sea wave movement, and so on. The available WS at seaincludes TVWS, cellular WS, and maritime WS, which may rangebetween tens MHz and several GHz. A maritime cognitive mesh/adhoc node needs being intelligent to switch its operation frequenciesto suit the geographic location, sea state, node density, communica-tion range, and region, to achieve the best communication qualityand follow the regional/national regulations of cognitive radios.

In analysis of the possible standards that are under develop-ment for cognitive radios, we found that none of them canmeet all of the requirements of a cognitive maritime mesh/adhoc network. As such, we use a cognition-enhanced mesh MACprotocol based on the IEEE 802.16d Mesh standard. In ourprevious study, it was enhanced to support mobility. In thisstudy, a sensing period is inserted in the frame structure, alsoan algorithm is developed to dynamically access the availablechannels for control messages transmission. This algorithmrequires no a specially reserved common channel for controlmessages, and then it saves cost on spectrum resource and radiocomponents. It offers chances of network entry and configurationto nodes with any available channels, and it can minimizeresource allocation conflicts by broadcasting bandwidth grantinformation to as-many-as-possible neighbors.

In simulations, we found that a higher detection probability ishelpful to achieve better network performance, especially in a highsea state like 6.0. A longer sensing interval has similar effect on thenetwork performance. The simulation results indicate that at a

relatively calm sea (e.g., sea state 3.0), relatively simple and generalsensing algorithm/components may be used for purpose of savingcost, however, when sea state is high, relatively advance algorithmand components for spectrum sensing are required. Operators needto find a balance between the system cost and network performancein different application scenarios. The operators also need to findbalance between the spectrum sensing interval and the protection ofthe incumbent users as required by the regulations.

The paper is organized as follows. In Section 2, we introduce thehigh-level system architecture, nodes design requirements, issues ofcognitive radio networking at sea, and challenges of maritimecommunications. In Section 3, the cognition-enhanced mesh MACprotocol, the routing protocol suitable for the maritime mesh/ad hocnetworks, and a switching antenna design meeting the maritimechallenges are presented. Simulation settings and results are givenin Section 4. This paper is concluded in Section 5.

2. Cognitive maritime mesh/ad hoc networks

2.1. High-level architecture

Figure 1 shows the high-level architecture of the proposed cogni-tive maritime mesh/ad hoc networks. Depending on the connectivityto the terrestrial networks, network coverage, and node mobility, it iscategorized into: (1) ship-to-ship/shore mesh/ad hoc networks closeto shore, (2) ship-to-ship ad hoc networks at deep sea, and (3) fixedmaritime facility mesh networks close to shore.

The ship-to-ship/shore mesh/ad hoc networks are formed byneighboring ships close to shore, marine buoys used as relaystations, and base stations that are regularly installed along thecoastline. A typical scenario of this type of network is in a narrowstrait with busy shipping lanes (like Malacca Strait) or in a seaport with many ships at anchor (like Singapore sea port). As thenode density is relatively high, the traffics between a base stationand a ship that is several hops away are forwarded by middleships or marine buoys.

The ship-to-ship ad hoc networks at deep sea are different asthere is no multi-hop connections to a land base station. In thiscase, the communication can fall back to the satellite commu-nication link meaning that an intelligent network switch middle-ware is needed onboard each ship. Communications among shipsnearby are still possible.

The fixed maritime facility mesh networks are formed bymaritime facilities like oil/gas platforms, sea farms, maritimesecurity/saft monitors, and marine environment monitors anddata collectors, etc. If necessary, marine buoys can be set up torelay and route packets. It is to meet the increasing need ofexploration of hydrocarbons in offshore locations, sea farming,piracy against, environment protection and so on. Land basestations can be installed on shore that is close to these facilities.The mesh nodes installed on these facilities can route trafficsfrom/to nearby ships, and vice versa.

The cognitive mesh/ad hoc ships/facility nodes and the basestations installed on shore may be in the coverage of theincumbent networks. In order to coexist with the incumbentusers, the cognitive mesh/ad hoc nodes sense the spectrumregularly. And possibly, they access geolocation/database regu-larly to update the channel availability as required by theregulations. Spectrum managers can also be used to dynamicallycontrol the channel access of the cognitive mesh/ad hoc nodes.

2.2. Cognitive maritime mesh/ad hoc nodes

In above, each ship is equipped with a mesh/ad hoc node thatis capable of performing cognitive radio functions. The cognitive

Fig. 1. High-level architecture of cognitive maritime mesh/ad hoc networks.

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mesh/ad hoc nodes sense the radio environment regularly anddynamically access the frequency channels that are not used bythe primary users. As some ships may travel across countries andcontinents, it is important to still harmonize the frequency bandsaround the world for cognitive maritime mesh/ad hoc network-ing. Currently, some countries have regulations about using theunused licensed bands, like TVWS, while most of the other countrieshave no regulations about the opportunistic access of the unusedlicensed frequency bands. Further more, the regulations of differentcountries may be different, meaning that the installed cognitivemaritime mesh/ad hoc nodes must be able to flexibly configure theoperation parameters when travel across the countries with differ-ent regulations. In cognitive operations, at sea that is far from land, itis hard for a node to connect a database for updating the availablefrequency channels by using cable, an ISM channel, or a specialcognitive pilot channel (CPC). One possible way is through satellitelinks, meaning that a ship with a cognitive mesh/ad hoc node thatneeds connection to database will be required to install a satellitereceiver.

The radio can also be designed more intelligent that theoperation frequencies can be switched to suit the geographiclocation, the sea state, and the ship nodes density. In port watersor narrow water channels that are close to land, the frequencybands are relatively crowded and there are less WS available. Theradio frequency usage will be mainly based on radio frequenciesthat are limited by land based terrestrial communications and TVbroadcast. In locations that are far away from land, signal trans-mitted by the on land primary users is less likely to introduceinterference so there are much more spectrum WS available. Con-sidering in this case ships may be sparse and one-hop distance isrelatively long, lower-end UHF and VHF bands can be used due tosmaller attenuation rate. Sea state is a description of the sea surfacemovement. Higher sea state means that the sea surface is morerough, and the transmitter/receiver antennas more likely deviatefrom alignment, resulting in more unstable link quality. In this case,MHz-frequencies is more helpful than GHz-frequencies to maintainnode connectivity due to larger beam width that is able to reduce themisalignment of the antennas.

Maritime communication environment is different from thatof land in many aspects thus the cognitive maritime mesh/ad hocnodes need to suit the special environment. In most cases, there isno blocks at sea and the sea surface is flat, the channel showsproperty of two-ray ground model, meaning that the mesh/ad hoc

nodes need to overcome the issue of huge path loss at certaindistances due to negative interference between the line-of-sight(LOS) path and the reflected path (Pathmasuntharam et al., 2007).The sea surface moves constantly, leading to frequent misalign-ment of the antennas and then unstable link quality. The link mayalso suffer sea wave occlusion. It is important that the mesh/adhoc nodes are capable of maintaining robust connectivity and theprotocols (routing and MAC, etc.) need to be resilient enough. Atsea, the distance between two ships in communication maypossibly be 10 km, then high-gain directional antenna is required.From another point of view, for mesh/ad hoc and spectrumsensing operation, an omnidirectional antenna that is able toreceive signal from 3601 direction is required.

2.3. Maritime cognitive networking

2.3.1. White Space at sea

There is few studies of WS at sea. Almost all of the reportedmeasurements of spectrum WS were carried out on land. Themost interested bands studied on land is TV bands. Anotherpossible band is frequencies allocated for cellular communica-tions, like IMT-advanced networks between 400 MHz and 5 GHz.As currently there is nor TV broadcast towers installed at sea,neither wireless cellular infrastructures, logically, there is plentyof TVWS and cellular WS at sea, especially at deep sea where theterrestrial radio signal may be extremely weak.

The frequency bands allocated for maritime communicationsneed being investigated separately. The current maritime com-munication frequencies are mainly in Medium Frequency band(MF, 300 kHz–3 MHz), High Frequency band (HF, 3–30 MHz), andVery High Frequency band (VHF, 30–300 MHz). These frequenciesare suitable for long range (from tens to hundreds km) commu-nications. In these bands, the amount of spectrum allocated in MFand HF bands for maritime communications is small (usually lessthan 0.5 MHz) and scattered across different bands. As such, thechannels of maritime VHF band between 156 and 174 MHz are ofhigher interest for opportunistic access for high-speed commu-nications. Some maritime radio navigation services use Ultra HighFrequency band (UHF, 300 MHz–3 GHz) and Super High Fre-quency band (SHF, 3–30 GHz). One example is in USA, thefrequencies between 2.9 and 3.1 GHz, 5.47 and 5.65 GHz, and9.2 and 9.3 GHz. Also, some maritime satellite communications

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use UHF and SHF bands. The bands are broad and can offerbandwidth of more than 100 MHz. They are suitable for relativelyshort range (from several to over 10 km) communications. It ispossible to use these bands for high-speed maritime communica-tions opportunistically since the ships are relatively sparse at sea.In this study, we call the unused bands of the spectrum allocatedfor maritime mobile/navigation/satellite communication ‘‘mari-time WS’’.

An important consideration to use maritime WS is that theprimary users (ships and authorities, etc.) must be well protected,as usually these bands are for transmissions of important infor-mation such as disaster rescue, vessel navigation, weather broad-casting, and so on. In cognitive radio operations in these bands, itis required that the detection probability must be high enough sothat the primary transmission can be detected precisely andtimely. It is also required that the channels can be evacuated inshort enough time once a primary transmission is detected. Possibly,more strict regulation needs to be applied to use maritime WS thanto use TVWS and cellular WS.

2.3.2. Regulations of cognitive radio networks

In order to protect the primary users and to facilitate effectiveusage of the WS, national spectrum regulations are necessity todeploy cognitive radio networks. Currently, a number of countrieshave mandated regulations on using TVWS and many of othercountries are highly interested (Zeng et al., 2010; FCC, 2008).TVWS is the first focus as the TV frequencies in high-VHF andlow-UHF range are ideal for covering large areas. These regula-tions are mainly for terrestrial usage but are good guidance forcognitive radio networks at sea. In sea areas close to land such assea ports and straits (e.g., Malacca Strait), these regulations areapplicable, since the terrestrial primary users need being protectedto avoid harmful interference from transmissions in these areas. Fordeep sea area, these regulations provide useful reference, but possiblysome rules need being more relax. For example, as the ship nodes arerelatively sparse and then the one-hop distance is relatively long,higher radiation power (compared to upper limit of the regulations)may be required. For cellular WS and maritime WS, currently there isno regulations to the authors best knowledge.

Although the current TVWS regulations of different countriesdiffer in many features, they share several basic rules that arefundamentally important to guide cognitive radio networking atsea. First, it is required that each cognitive node is capable ofdetecting the availability of the frequency channels of the primaryusers. Generally, two methods are mandated: spectrum sensingand geolocation/database access, depending on the device typeand capability. A fixed device is usually required to employ bothof the methods, while a portable device is required at least beingcapable of sensing the spectrum. Second, the Equivalent Isotro-pically Radiated Power (EIRP) is usually limited under certainvalue. Different devices may have different limits on EIRP. Usually, afixed device that can perform both spectrum sensing and geoloca-tion/database access is allowed to transmit with higher EIRP, while aportable device that can only perform spectrum sensing is limited totransmit with lower EIRP. The current highest limit is the Canada’scognitive base station—up to 500 W EIRP is allowed. In USA, thelowest EIRP limit is 50 mW, for a portable device using spectrumsensing only.

To apply these rules in cognitive maritime mesh/ad hoc net-works, it needs to consider the device type, location, and thecapability to access Internet. For the base stations that are regularlyinstalled along the shorelines, they are fixed and are able to accessgeolocation/database by using cables. As such, they are capable ofdetecting channel availability by using both spectrum sensing anddatabase access and then are allowed to transmit higher power. For

fixed nodes of maritime facility mesh networks, they also can trans-mit higher power. Satellite links can be used to access database forthese maritime facilities if they install. Big ships that are installedsatellite receivers can access database through satellite links as well.For small ships that have no satellite receivers, they can performspectrum sensing only.

2.3.3. Standards of cognitive radio networks

A standard is needed to guarantee the proper operation of thecognitive maritime wireless mesh/ad hoc networks worldwide.This standard is required to have basic functions of: (1) supportingcognitive operations, i.e., it allows spectrum sensing, geolocation/database access, incumbent protection, and so on; (2) supportingmesh/ad hoc networking; (3) supporting long-distance (tens km)communications; (4) supporting mobility.

None of the standards currently under development forcognitive radio networking has all of the above four functions.IEEE 802.22 is the initiative of the standards for cognitive radiowireless networking. It is capable of providing wireless broad-band access over distance of 30 km (up to 100 km) by opportu-nistically using the unused TV bands. However, it only supportspoint-to-multipoint (PMP) communication and does not supportmobility. ECMA 392, the first standard completed for cognitiveradio networking using TVWS, supports high-speed communica-tions up to 24 Mbps, and supports master-slave, mesh, and peer-to-peer communications. The limit of this standard is the sup-ported distance, which is typically less than 1 km—it employs128-FFT size OFDM modulations thus is not efficient to overcomefading spread over 30 ms in long range (tens km) communications.IEEE 802.11af starts its standardization in January 2010 with anaim to provide high-speed WLAN using TVWS and now is in progress.It is also not optimized to support long range communications.

The standard used in TRITON for maritime mesh/ad hocnetworking is IEEE 802.16d Mesh MAC and 802.16e PHY. 802.16is used as it supports long-distance broadband communication,mesh networking, and mobility. However, it does not supportcognitive operation. In study of cognitive maritime mesh/ad hocnetworks, we extended the 802.16d mesh MAC protocol byadding functions of cognitive operation, as presented in Section 3.

One more possible standard to support cognitive maritimemesh/ad hoc networking is with IEEE 1900. Currently, IEEE 1900has set up a study group of WS and aims to develop new MAC andPHY to support cognitive radio networking by accessing WS thatis not limited to TVWS. A use model of maritime mesh/ad hocnetworks is included as one of the development targets (Zhouet al., 2010).

2.4. Challenges of maritime communications

Maritime communication environment has unique propertiesand challenges when compared to land environment. Towardssuccess of a maritime communication system, proper designs onboth protocol and hardware meeting the challenges are required.The maritime communication environment is mainly character-ized by sea surface movement, radio propagation, and Fresneleffect.

2.4.1. Sea surface movement

Sea surface moves all the time leading to unstable link quality.The sea wave movement continuously changes the antenna orienta-tion and height, and then changes the antenna gain and receivedradio signal power. The roughness of the sea surface is measured byso called sea states, which is characterized by parameters ofsignificant sea wave height, average sea wave length, and averagesea wave period. Signification sea wave height is the mean wave

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height of the one-third highest wave. A detailed sea state tablecan be found in http://www.eustis.army.mil/WEATHER/WeatherProducts/seastate.htm. A higher sea state means that it has higherwave height, longer wave length and period. A general model of seawave movement is Trochoid wave that is created by tracing the pathof a point inside a circle (http://hyperphysics.phy-astr.gsu.edu/hbase/waves/watwav2.html).

The quality of a mesh/ad hoc link may likely experience periodicdegradation due to the sea surface movement. It has significantimpact on higher layer protocol design. For example, a ‘‘bad link’’may last for several seconds due to long sea wave period. In thiscase, all retransmissions for a failed packet over the same link in thelong bad link duration may also fail. Increasing the maximumnumber of retransmission before discarding a packet is not effectiveto improve the performance, and thus retransmission is not a goodsolution for link failures in maritime mesh networking. Instead,communication diversity may be more effective (Kong et al., 2008).

2.4.2. Channel properties

The radio channel properties are closely related to the propa-gation environment. The maritime environment can be categor-ized into three types: (1) open sea and shipping lanes; (2) near-coast waters with hills and cliffs; (3) ports, harbors, and narrowshipping lanes with intense environmental mobility and urban/suburban onshore surroundings. As confirmed by many measure-ments, in the first case, for frequencies between high-VHF andUHF, a two-ray channel model with a LOS path and a reflectedpath is applicable (Pathmasuntharam et al., 2007; Schmalenbergerand Edrich, 2000). In the second case, other than the two main paths(LOS and the reflected one), reflections from rocks or hilly terrain onthe coastline can also be received, thus the channel shows propertiesof Rician fading. In the third case, plenty of reflection fromsurrounding environment can be received and LOS path does notdominate, thus the channel can be described by Rayleigh fading.

Different channel properties lead to different challenges thatneed to meet. When the channel follows two-ray ground model,the received signal experience periodic complete degradationalong the propagation distance due to negative interferencebetween the LOS path and the reflected path. When the channelshows deep Rayleigh fading, even the received signal has a goodsignal-to-noise ratio (SNR), the bit-error rate (BER) will possiblybe poor because of signal spreading (Schmalenberger and Edrich,

Fig. 2. Cognition enhanced frame struct

2000). As a ship may be at all of the maritime environments, itrequires the installed mesh/ad hoc node is capable of alleviatingall of the issues.

2.4.3. Fresnel effect

In order to maximize the signal strength for better link qualityin maritime communications, one needs to minimize the effect ofthe out of phase signal by removing obstacles from the radiofrequency LOS. As the strongest signals are on the direct linebetween transmitters and receiver and always lie in the firstFresnel zone, it is necessary to clear the first Fresnel zone by usingantenna with proper height or suitable frequency. It is confir-med by a recent measurement carried out in Singapore (ITU-R WP5B-3 Maritime Group, 2009). The experiment shows that in somecase although the link budget is sufficient, but when Fresnel zoneclearance is violated, the performance will degrade.

Lower frequencies require higher antenna to clear the firstFresnel Zone, and may impose challenges when use MHz-fre-quencies. A calculation shows that for frequency 700 MHz, inorder to achieve a 60% clearance of the first Fresnel Zone, for acommunication distance of 15 km, the average antenna heightneeds being more than 27 m—for small ships it is hard to installso high antenna. When increase the operation frequency to 3 GHz,the required average antenna height decreases to 15 m, which ismuch reasonable. It means that in cognitive maritime commu-nications, other than consideration of available WS, it needs toachieve balance between frequencies, antenna heights, and com-munication distances.

3. Development of protocols and hardwares

3.1. Cognition enhancement of the mesh MAC protocol

IEEE 802.16d Mesh has been employed in our previous researchto provide multi-hop wireless mesh networking for high-speed ship-to-ship/shore communications (Pathmasuntharam et al., 2008). Inthis study, the IEEE 802.16d Mesh MAC protocol is enhanced tosupport cognitive operation.

The cognition-enhanced frame structure is shown in Fig. 2. Anoriginal 802.16d Mesh MAC frame consists of two subframes, i.e.,control subframe and data subframe (IEEE). In this study, as shown

ure of IEEE 802.16d Mesh network.

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in Fig. 2 we keep the control subframes unchange, while propose toinsert a sensing period in a data subframe every K frames, KZ1.Data subframes without sensing period are called full data sub-frames (fDS) and they are exactly the same as ones defined in theIEEE 802.16d Mesh standard. Each of them is divided into 256minislots for data bursts transmissions. Data subframes with sen-sing period are called mixed data and sensing subframes (mDS). Thefirst part of a mDS is data period, where data bursts can be trans-mitted. The second part is sensing period and a cognitive 802.16dMesh node performs spectrum sensing in this period.

The control subframes are same as the original design of theIEEE 802.16d Mesh mode. A control subframe consists of MSH-CTRL-LEN (up to 16) control slots, and within each of them acontrol message PDU can be transmitted. There are two types ofcontrol subframes, i.e., network control subframes (nCSs) andscheduling control subframes (sCSs). In an nCS, MSH-NENT mess-ages for network entry and MSH-NCFG messages for networkconfiguration are transmitted. In this study, we only employcoordinated distributed scheduling (CDS) (one of the three sche-duling schemes defined in the IEEE 802.16d Mesh mode forscheduling data transmission), so, in an sCS, only MSH-DSCHmessages are transmitted. Figure 2 also shows the structure of annCS and an sCS in detail. The first control slot of an nCS is fortransmission of a MSH-NENT message and the rest are for transmis-sion of MSH-NCFG messages. All of the control slots in an sCS areused for transmission of MSH-DSCH messages. nCSs occur periodi-cally with a period of L (¼ 4� Scheduling Framesþ1) frames, andthe other control subframes are sCSs.

Control messages are critical to the operation of a mesh/ad hocnetwork as they carry information like beacon, network entry,time stamp, and resource application and grant, etc. In cognitivemesh/ad hoc networks, as the available frequency channels mayfrequently change, it needs an algorithm to dynamically accessthe channels for control messages transmission.

The algorithm to access the available channels for controlmessages transmission in this study is so designed that in eachcontrol slot the channel accessing is ‘‘synchronized’’, i.e., in agiven control slot, all of the mesh/ad hoc nodes try to access asame frequency channel. The three types of control slots arenumbered separately based on the system time. For a givencontrol slot with an index number of Ni, the channel all nodestrying to access is given by ci¼Ni %Nc, where ‘‘%’’ standards formodulo operation (MOD) and Nc is the total number of thechannels. If the channel ci is available at a node, then the nodeaccesses it. Otherwise, if the control slot is a MSH-NCFG or MSH-NENT transmission opportunity, the node accesses an availablechannel that is randomly selected from the set of availablechannels. If the control slot is a MSH-DSCH transmission oppor-tunity, the node accesses an available channel with maximumchannel availability degree (CAD). CAD of a channel is defined asthe number of one-hop neighbors reporting the channel isavailable. If there are several channels having the maximumCAD, the node accesses the one with the lowest frequency. Byusing the above algorithm, the control messages for networkconfiguration and network entry (MSH-NCFG and MSH-NENT)can be fairly broadcasted over all of the available channels thus allof the nodes have equal chances to enter the network, while thecontrol messages for resource allocations (MSH-DSCH) can bereceived by as-many-as-possible neighbors and then collisions inallocations of the data minislots can be minimized.

With the above algorithm proposed for control messagesbroadcasting, a number of basic networking functions, such asneighbor discovery, network entry, and three-way handshake forbandwidth grant can be implemented. And then there is no needof a specially reserved control channel so the cost of frequencyresource and radio components can be saved.

A spectrum sensing reporting mechanism is also proposed inthis study: a new information element (IE)—Channel Status IE,which contains sensing results of the channel index and itsavailability, is added in MSH-NCFG messages each time needed.This information is broadcasted with MSH-NCFG messages andthen a cognitive mesh/ad hoc node is aware of the availabilities ofthe channels of all its one-hop neighbors.

3.2. Routing protocol

Routing protocol is important in ensuring connectivity andreliable packets delivery in mesh/ad hoc networks. We evaluateda number of routing protocols for maritime mesh/ad hoc networkcommunications, including Ad hoc On-demand Distance VectorRouting protocol (AODV), Ad hoc On-demand Multipath DistanceVector protocol (AOMDV), and Optimized Link State Routingprotocol (OLSR) (Kong et al., 2008). It is found that a proactiverouting protocol (e.g., OLSR) performs better in initial packetdelay, since it sets up routing path before arrival of packets. Initialpacket delay is the delay of the first packet received by thedestination node. However, this type of routing protocol isinferior to reactive routing protocol, due to slow reaction to thefrequent link breakage, while in maritime environment the linkmay break often because of sea wave movement. Performancecomparison between AODV and AOMDV shows that a backup ofrouting path is helpful to achieve better average packet delay andpacket delivery ratio (Kong et al., 2008).

A new routing protocol, MAC-based Routing Protocol forTRITON (MRPT), was developed by us recently specially formaritime mesh/ad hoc communications (Kong et al., 2009). It isa proactive type of routing protocol. But its proactiveness isachieved by pigging back the routing information on the MSH-NCFG messages that are frequently broadcasted by each of themesh/ad hoc nodes, so, unlike OLSR, it has a quick reaction to thelink breakage and then the performance on average packet delayand delivery ratio even performs better than AODV and AOMDV.In addition, alternative routes are available as backup for routeswitching when an existing link is broken, and this increases thenetwork robustness.

3.3. Switching antenna

In a mesh/ad hoc network, 3601 reception and broadcast arerequired for awareness of the MAC states among neighborhood.For spectrum sensing, it also requires a cognitive mesh/ad hocnode capable of receiving primary users transmission from anydirection. Meanwhile, for long range communications in maritimeenvironment, high antenna gain is a must. All the above require-ments are addressed by a switching antenna design that com-bines four sectors of 901 directional antennas to cover 3601horizontally. The vertical coverage is increased by configuringthree antennas in a vertically overlapping manner. For example,three units of 901 horizontal beam width and 51 vertical beamwidth antenna can be configured to provide an overlapping 151vertical beam width.

In order to reduce the destruction of the signal or signal lossdue to negative interference, the switching antenna is designed tomaintain the antenna beam in a horizontal direction. This isachieved by using a gyroscope (gyro) that continuously monitor-ing the ship movement and providing yaw, pitch and roll anglesinformation to an intelligent unit of the cognitive mesh/ad hocnode. The antenna in the horizontal direction is selected based onthese angle information. The issue of the two-ray ground channelmodel that at some distances the LOS path and the reflected pathmay interfere negatively can be mitigated by this design, as it

M.-T. Zhou, H. Harada / Journal of Network and Computer Applications 35 (2012) 518–526524

effectively reduces the power of the reflected path since thereflected path is not at the horizontal direction of the receivingantenna.

4. Simulation and results

Simulation has been carried out to investigate the networkperformance of the propose cognitive maritime mesh/ad hocnetworks. It is based on using a maritime simulator developedin Qualnet recently (Su et al., 2007). The simulator consists of seawave movement model, path loss model, ship mobility model,network model, MRPT protocol, and IEEE 802.16d Mesh MACprotocol with mobility supporting. In this study, it is enhanced byadding cognitive radio functions, like the proposed new framestructure and the algorithm proposed for control messages trans-mission.

As shown in Fig. 3, the network model considered is a generalmaritime wireless mesh/ad hoc network covering a narrownavigation channel with traffic separation scheme defined bythe International Maritime Organization (IMO). The network hastwo parallel shipping lanes, one eastbound and one westbound,each with a width of 20 km, and it has a land station, i.e., an IEEE802.16d mesh base station, located 10 km from the shore.

The ship mobility model is characterized by the statistic dis-tributions of the ships inter-arrival time and the constant speed. Thedistribution functions of the model used in this simulation arederived from the collected data from Maritime Port Authority (MPA)of Singapore, i.e., the mobility model represents the real traffic ofships in the Strait of Singapore (Pathmasuntharam et al., 2007).

The sea states simulated in this study is 3.0 and 6.0. Table 1lists the parameters of the two sea states. Sea state 3.0 is the usualcase and it is desired that a maritime communication system stillworks properly in sea state 6.0.

Totally 10 TVWS frequency channels in range between 632and 692 MHz are simulated. Each channel has a bandwidth of6 MHz. QPSK 1/2 modulation-coding is used for both data and

Fig. 3. A simulation model of maritime mesh/ad hoc networks in a narrow

navigation channel.

Table 1Parameters of sea state 3.0 and 6.0 (http://www.eustis.army.mil/WEATHER/

WeatherProducts/seastate.htm).

Sea state 3 6

Wind speed (knots) 14 27

Significant wave height (m) 1.0667 4.2670

Average wave length (m) 14.0201 56.0805

Average wave period (s) 3.5 7.5

control packets transmission. MRPT is used as routing protocol.The MAC frame duration is 40 ms, and the time used for sense onechannel is set to 0.5 ms.

In the simulated network model, there are totally 51 ship nodesat sea and one base station on shore. One of the ship nodes wasselected as source node in each simulation scenario and the des-tination node is the base station. In each simulation scenario, wechange either the detection probability, the spectrum sensing inter-val, the source node, or the sea state to evaluate the network per-formance with different spectrum sensing detection probabilities,sensing interval, number of communication hops, and sea state.Spectrum sensing detection probability is the probability that atransmission of a primary user being detected by a cognitive mesh/ad hoc node. All of the simulation scenarios have a simulation time of600 s. The system warms up in the first 300 s, and in the second300 s the selected source node sends constant bit-rate (CBR) datapackets to the base station. The packet size is 400 bytes and thepackets arrival interval is 5 ms.

Figure 4 shows the simulated packets delivery ratio as functionof the detection probability with sea state and the number ofcommunication hops as parameters. Delivery ratio is the ratiobetween the number of packets that are successfully delivered tothe destination node and the total number of packets sent by thesource node. It can be seen that with a higher detection prob-ability, more data packets can be successfully delivered to thedestination, for both sea states and all three hop numbers. This istrue since a higher detection probability means that there are lessconflicts to the primary transmissions. We also can see at a givendetection probability, when the sea state is 6.0, more data packetsare lost when compared to sea state 3.0, due to more unstable linkquality. When the detection probability is 0.8, at sea state 6.0, fora three hops communication, the end-to-end delivery ratio is justabout 0.72. However, when increase the detection probability to0.95, we can see its delivery ratio is improved by about 20%,reaches about 0.9, meaning that in high sea state, a high detectionprobability is helpful to improve the communication quality. Itindicates that in high sea states, more advance algorithms orcomponents for spectrum sensing are required. From the resultsshown in this figure, we also can see in cases of less number ofhops that the packets delivery ratios is normally higher. Sinceone-hop distance can be longer when use a lower frequency,when the cognitive mesh/ad hoc nodes dynamically access the WSfrequency channels, to use lower frequency WS is more helpful toimprove the communication quality, especially when sea state ishigh (like 6.0).

Figure 5 shows the average end-to-end delay as function of thedetection probability, with sea state and number of hops asparameters. Again, we can see that a higher detection probabilitycan help to improve the communication quality—increasing the

Fig. 4. Simulated packets end-to-end delivery ratio as function of the detection

probability, with sea state and the number of hops as parameters. The sensing

interval is set to 1 s (25 frames duration) in all of the simulations.

Fig. 5. Simulated average packet end-to-end delay as function of the detection

probability, with sea state and number of hops as parameters. The sensing interval

is set to 1 s (25 frames duration) in all of the simulations.

Fig. 6. Simulated packet end-to-end delivery ratio in different sea states, with

spectrum sensing interval and number of hops as parameters. The detection

probability is 0.9 in all of the simulations. SI: sensing interval.

Fig. 7. Simulated average packet end-to-end delay in different sea state, with

spectrum sensing interval and number of hops as parameters. The detection

probability is 0.9 in all of the simulations. SI: sensing interval.

M.-T. Zhou, H. Harada / Journal of Network and Computer Applications 35 (2012) 518–526 525

detection probability from 0.8 to 0.95, for case of seat state of6.0 and three hops, the average delay decreases from 0.95 toabout 0.18 s.

Spectrum sensing interval is an important parameter of cognitiveradio networks. Shorter spectrum sensing interval means a cognitiveradio node senses the spectrum more often and may evacuate thefrequency channels that are occupied by the primary users moretimely. However, it also means that the network has less time totransmit or receive data packets since when the cognitive nodessenses spectrum all of the nodes need to keep quiet in the bandsunder sensing. We also simulated the effect of the spectrum sensinginterval to the network performance in this study. Figure 6 showsthe average end-to-end delivery ratio in different sea states, withsensing interval and number of hops as parameters. The detectionprobability is set to 0.9 in all of the simulations. Two sensingintervals are simulated: duration of 25 frames and 75 frames. As oneframe duration simulated is 40 ms, the two sensing intervals are1 and 3 s, respectively. It can be seen that with a longer sensinginterval, more packets can be successfully delivered to the destina-tion node. When compare sea state 3.0 and 6.0, we can see theimprovement on delivery ratio by using longer sensing interval insea state 6.0 is bigger. For the three hop numbers, it can be seen thatthe improvement in case with three hops is the biggest. Thisindicates that in case of high sea state and large number of hops,a longer sensing interval is more helpful to improve the networkperformance. Anyway, in order to protect the incumbent transmis-sions, a WS regulation may require that all of the secondary nodes toperform spectrum sensing with an interval less than an upper limit.As such, the setting of the spectrum sensing interval needs to follow

the constraint given by the rules, and an operator needs to find abalance between the network performance and the protection of theincumbent users.

Figure 7 shows the simulated average packet end-to-end delayin sea state 3.0 and 6.0, with sensing interval and number of hopsas parameters. Similar observations can be seen as that of thesimulation results of the packet delivery ratio.

5. Conclusion

This paper proposed using cognitive radio technologies toalleviate the spectrum congestion and scarcity issues in maritimemesh/ad hoc networks. The network architecture, nodes designrequirements, issues of maritime cognitive networks, challengesof maritime environment are analyzed. A cognition-enhanced meshMAC protocol, MRPT routing protocol, and a switching antenna arealso presented, towards realization the cognitive maritime mesh/adhoc networks. Simulation results indicate that higher detectionprobability and longer sensing interval may achieve better networkperformance. Anyway, operators need to balance among cost, net-work performance, and protection of incumbent users. The proposaland analysis in this paper are helpful for future development ofhigh-speed and low-cost maritime communication networks usingspectrum WS.

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