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Cognitive Radio Networks: Technology Survey & Research Challenges Presented By: Vatsala Sharma PhD (ECE) I year College of Technology And Engineering MPUAT, Udaipur

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Page 1: Cognitive radio networks

Cognitive Radio Networks: Technology Survey & Research Challenges

Presented By:

Vatsala Sharma

PhD (ECE) I year

College of Technology And EngineeringMPUAT, Udaipur

Page 2: Cognitive radio networks

Outline• Introduction to Cognitive Radio Network• Objectives of Cognitive Radio Networks • CR Network Architecture• Main Issues in Cognitive Radio Networks• CRN Standards• Spectrum sensing & analysis• Dynamic spectrum allocation & sharing• Cognitive Radio platforms• Future Research Directions• Conclusion

Page 3: Cognitive radio networks

Introduction to Cognitive Radio Networks•A cognitive radio is an intelligent radio that can be programmed and configured  dynamically.

• Radio that automatically detects available channels in wireless spectrum, accordingly changes its transmission or reception parameters to allow more concurrent wireless communications in a given spectrum band.

• FCC assigns spectrum to licensed holders, known as primary users (PU).

• Users who have no spectrum licenses, known as secondary users (SU).

• FCC has been considering more flexible and comprehensive uses of the available spectrum, through the use of cognitive radio technology.

Figure 1: Spectrum usage

Page 4: Cognitive radio networks

DYNAMIC SPECTRUM ACCESS

• CR Technology works on the principle of dynamic spectrum access, where secondary users utilize spectrum holes.

• A spectrum hole is a band of frequencies assigned to a primary user, but, at a particular time and specific geographic location, the band is not being utilized by that user.

Page 5: Cognitive radio networks

Software Radio

• Dynamically support multiple variable systems, protocols and interfaces

• Interface with diverse systems

• Provide a wide range of services with variable QoS

ConventionalRadio

• Supports a fixed number of systems

• Reconfigurability decided at the time of design

• May support multiple services, but chosen at the time of design

Cognitive Radio• Can create new

waveforms on its own

• Can negotiate new interfaces

• Adjusts operations to meet the QoS required by the application for the signal environment

• SDR+intelligence

How is a Cognitive Radio Different from Other Radios?

Page 6: Cognitive radio networks

Objectives of Cognitive Radio Networks

• spectrum sensing - determine the spectrum holes • spectrum decision - select the best spectrum opportunities to meet the user

communication requirements• spectrum sharing - coordinate access to the selected channels with CR

neighbours • spectrum mobility - switch to the selected opportunities • maintain seamless communication during spectrum handovers• avoid any harmful interference to primary users.

Page 7: Cognitive radio networks

CR Network ArchitectureIn a CR network architecture, the components include both a secondary network and a primary network.

Page 8: Cognitive radio networks

CR architectural approachesThe architecture of CR networks can either be centralized or distributed.

• Centralized Approach - Spectrum allocation and access are controlled by a central entity (e.g., a base station)

• Distributed Approach – Spectrum Allocation and access controlled by CR users

Centralized Approach Distributed Approach

Page 9: Cognitive radio networks

Main Issues in Cognitive Radio Networks1) Self-coexistence - One of the most important and specific issue of CR is to avoid

secondary users to harmfully interfere with primary users. Overlay and underlay are two possible spectrum access techniques.

2) Accurate Sensing - Sensing aims to determine if a channel is idle or busy in terms of primary user activity.

3) Signalling - CR scenarios require the exchange of control information between CR devices for spectrum sensing and sharing. Most CR MAC protocols use a common control channel (CCC), which facilitates signalling and also neighbour discovery in CR adhoc networks.

4) Optimized spectrum decision - secondary users are expected to dynamically choose the best available channels and transmission parameters.

5) Seamless spectrum handover - Seamless transition with minimum quality degradation is a fundamental goal for any spectrum handover scheme.

Page 10: Cognitive radio networks

5) Cross layer design - to get better performance, the strict layer-based approach is often violated in wireless networks, namely through cross-layer interactions.

6) Energy efficiency - The number of sensed channels must also be minimized through appropriate prioritization mechanisms as sensing is one of the main sources of energy and time consumption.

Cross layer design

Page 11: Cognitive radio networks

The IEEE 802.22 standard is the first effort for achieving a CR international standard. It defines CR techniques that are specifically targeted to enable unlicensed devices to exploit television white spaces in the VHF and UHF bands (54862 MHz) in a non-interfering basis for the deployment of Wireless Regional Area Networks (WRAN).

CRN Standards

Page 12: Cognitive radio networks

SPECTRUM SENSING & ANALYSIS

First critical step towards dynamic spectrum management, having three aspects of spectrum sensing.

a) Interference Temperature Model The interference temperature approach used to enforce an interference limit

perceived by receivers. It is a measure of the RF power available at a receiving antenna to be delivered to a receiver, reflecting the power generated by other emitters and noise sources.

TI (fc,B) =

Where PI(fc,B) is the average interference power in Watts centered at fc

b) Spectrum Sensing Enables the capability of a CR to measure, learn and be aware of the radio’s

operating environment, such as the spectrum availability and interference status. Spectrum sensing techniques can be categorized as:(i) Energy Detector(ii) Feature Detector(iii)Matched Filtering & Coherent Detection

Page 13: Cognitive radio networks

Summary of main spectrum sensing techniques

Page 14: Cognitive radio networks

c) Cooperative Sensing

• By taking advantage of the independent fading channels (i.e., spatial diversity) and multiuser diversity, cooperative spectrum sensing is proposed to improve the reliability of spectrum sensing, increase the detection probability to better protect a primary user, and reduce false alarm to utilize the idle spectrum more efficiently.

• In centralized cooperative spectrum sensing, a central controller, e.g., a secondary base station, collects local observations from multiple secondary users, decides the available spectrum channels using some decision fusion rule, and informs the secondary users which channels to access.

• In distributed cooperative spectrum sensing, secondary users exchange their local detection results among themselves without requiring a backbone infrastructure with reduced cost.

Page 15: Cognitive radio networks

DYNAMIC SPECTRUM ALLOCATION & SHARING

Classification of spectrum allocation and sharing schemes

Page 16: Cognitive radio networks

Considering the access technology of the secondary users, licensed spectrum sharing can be further divided in two categories:

1) Spectrum underlay: In spectrum underlay secondary users are allowed to transmit their data in the licensed spectrum band when primary users are also transmitting. The interference temperature model is imposed on secondary users’ transmission power so that the interference at a primary user’s receiver is within the interference temperature limit and primary users can deliver their packet to the receiver successfully.

2) Spectrum overlay: Spectrum overlay is also referred to as opportunistic spectrum access. Unlike spectrum underlay, secondary users in spectrum overlay will only use the licensed spectrum when primary users are not transmitting, so there is no interference temperature limit imposed on secondary users’ transmission. Instead, secondary users need to sense the licensed frequency band and detect the spectrum white space, in order to avoid harmful interference to primary users.

Page 17: Cognitive radio networks

COGNITIVE RADIO PLATFORMS

A. Wireless open-Access Research Platform (WARP)

B. SORA

C. COgnitive RAdio Learning (CORAL)

D. Berkeley Emulation Engine (BEE2)

E. Lyrtech’s small form factor (SFF) SDR

Page 18: Cognitive radio networks

FUTURE RESEARCH DIRECTIONS

A. Seamless spectrum handovers

B. Proactive spectrum selection and interference avoidance

C. Interdependency between the propagation characteristics of radio signals and the frequency band in usage

D. Alternatives to the common channel

E. Energy efficiency

F. Validation of CR protocols

Page 19: Cognitive radio networks

CONCLUSIONS

• This presentation gives an overview of Cognitive Radio Network technology, which is still in its infancy and aims to enable an efficient utilization of the radio spectrum, has been briefly described under different perspectives, putting the emphasis on layer-2 issues, learning based on past experience, and implications on upper layer protocols.

• Provide the readers a global vision of CR concerning its principles, present state of development, and possible future directions.

• It was shown that several challenging issues still need further investigation, making CR an open research area, such as: (1) seamless spectrum handovers; (2) proactive spectrum selection; (3) interference avoidance; (4) energy efficiency; (5) alternatives

•In addition, recently proposed dynamic spectrum management and sharing schemes are reviewed, such as medium access control, spectrum handoff, power control, routing, and cooperation enforcement

Page 20: Cognitive radio networks

REFERENCES

[1] Beibei Wang and K. J. Ray Liu, “Advances in Cognitive Radio Networks: A Survey”, IEEE Journal of selected topics in signal processing, VOL. 5, NO. 1, FEBRUARY 2011.

[2] G. Ganesan and L. Ye, “Cooperative spectrum sensing in cognitive radio, part I: Two user networks,” IEEE Trans. Wireless Commun., vol. 6, no. 6, pp. 2204–2213, Jun. 2007.

[3] T. Yucek and H. Arslan, “A survey of spectrum sensing algorithms for cognitive radio applications,” IEEE Commun. Surveys Tutorials, vol. 11, no. 1, pp. 116–130, First Quarter, 2009.

[4] W. D. Horne, “Adaptive spectrum access: Using the full spectrum space,” in Proc. Annu. Telecomm. Policy Res. Conf., Arlington, VA, Oct. 2003.

[5] R. Ruby, S. Hanna, J. Syndor, and V. C. M. Leung. Interference sensing using coral cognitive radio platforms. In Int. Conf. on CHINACOM Proc., 2011.

[6] P. D. Sutton, J. Lotze, H. Lahlou, S. A. Fahmy, K. E. Nolan, B. Ozgul, T. Rondeau, J. Noguera, and L. E. Doyle. Iris: an architecture for cognitive radio network testbeds. IEEE Comm. Mag., 48(9), 2010.

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[7] K. Tan, J. Zhang, J. Fang, H. Liu, Y. Ye, S. Wang, Y. Zhang, H. Wu, W. Wang, and G. M. Voelker. Sora: high performance software radio using general purpose multi-core processors. In USENIX Symp. on Net. Systems Design and Impl. Proc., 2009.

[8] Elias Z. Tragos, Sherali Zeadally, Alexandros G. Fragkiadakis, and Vasilios A. Siris, “Spectrum Assignment in Cognitive Radio Networks: A Comprehensive Survey”, IEEE communication surveys & tutorials, VOL. 15, NO. 3, third quarter 2013, pg.no. 1108-1135.

[9] Hasegawa M., Hirai H., Nagano K.,  Harada H., and Aihara K., “Optimization for Centralized and Decentralized CognitiveRadio Networks”, Proceedings of the IEEE, Volume: 102 , Issue:4, 2014.

[10] Hattab, G. and Ibnkahla, M.,”Multiband Spectrum Access: Great Promises for FutureCognitive Radio Networks”, Proceedings of the IEEE  Volume: 102 , Issue: 3 , 2014.

[11] Li Jianwu ; Feng Zebing; Feng Zhiyong and Zhang Ping Communications, China , “A survey of security issues in Cognitive Radio Networks”, Volume: 12 , Issue: 3 , 2015.

[12]Kulkarni, S.; Markande, S., “Comparative study of routing protocols in Cognitive RadioNetworks”, Pervasive Computing (ICPC), 2015 International Conference, 2015.