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科学通报  2012 

认知无线网络中基于共识理论的分布式聚类合作频谱感知研究

, PP. 776-783

Keywords: 认知无线网络,频谱感知,分布式聚类,无监督学习,共识理论

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Abstract:

大量的已有研究工作表明多用户合作频谱感知可以明显提升检测性能.然而,当网络中用户数目较多,并且用户所分布的空间范围较大时,所有用户均参与合作将会带来巨大的感知开销(例如感知时间和能量消耗).基于无监督学习技术和共识理论的最新进展,在本文中我们提出了一种全分布式的合作频谱感知方案.在所提方案中,仅通过一跳可达的邻居之间的信息交互,具有潜在最佳检测性能的用户会自组织地聚到一起,这些用户进而利用平均共识协议来进行合作频谱感知,然后将感知结果广播至全网用户.为了进行性能比较,进一步给出了最优软合并的一种分布式实现方案.数值结果表明所提方案获得了与最优软合并方案相近的检测性能,并明显优于已有等增益合并方案和基于位置信息的方案.同时,相比于最优软合并方案,所提方案可以大幅度降低感知开销,并且不需要关于用户本地信噪比的先验信息.

References

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[2]  Tandra R, Mishra S M, Sahai A. What is a spectrum hole and what does it take to recognize one. Proc IEEE, 2009, 97: 824-848
[3]  Ma J, Li G, Juang B H. Signal processing in cognitive radio. Proc IEEE, 2009, 97: 805-823
[4]  Cabric D.[J].Mishra S M, Brodersen R. Implementation s in spectrum sensing for cognitive radios. In: Michael B M, ed. Proceedings of38rd Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, USA.2004,:-
[5]  Sahai A, Tandra R, Mishra S M, et al. Fundamental design tradeoffs in cognitive radio systems. In: Milind B, Anant S, Kitti H, eds. Proceedings of the first international workshop on Technology and policy for accessing spectrum, Boston, USA, 2006. 1-6
[6]  Duan D L, Yang L Q, Principe J C. Cooperative diversity of spectrum sensing for cognitive radio systems. IEEE Trans Signal Process,2010, 58: 3218-3227
[7]  Yucek T, Arslan H. A survey of spectrum sensing algorithms for cognitive radio applications. IEEE Commun Surveys Tuts, 2009, 11:116-130
[8]  Zeng Y H, Liang Y C, Hoang A T, et al. A review on spectrum sensing for cognitive radio: Challenges and solutions. EURASIP J Adv Signal Process. 2010: 1-15
[9]  Shen J Y, Jiang T, Liu S Y, et al. Maximum channel throughput via cooperative spectrum sensing in cognitive radio networks. IEEE Trans Wireless Commun, 2009, 8: 5166-5175
[10]  Jayakrishnan U, Venugopal V V. Cooperative sensing for primary detection in cognitive radio. IEEE J Sel Topics Signal Process, 2008, 2:18-27
[11]  Reza O S, Fax J A, Richard M M. Consensus and cooperation in networked multi-agent systems. Proc IEEE, 2007, 95: 215-233
[12]  Peh E C, Liang Y C, Guan Y L, et al. Optimization of cooperative sensing in cognitive radio networks: A sensing-throughput tradeoff view. IEEE Trans Veh Technol, 2009, 58: 5294-5299
[13]  Quan Z, Ma W, Cui S G, et al. Optimal linear fusion for distributed detection via semi-definite programming. IEEE Trans Signal Process,2010, 58: 2431-2436
[14]  Ma J, Zhao G, Li Y. Soft combination and detection for cooperative spectrum sensing in cognitive radio networks. IEEE Trans Wireless Commun, 2008, 7: 4502-4507
[15]  Miia M, Marja M, Aarne M. Cooperative spectrum sensing using quantized soft decision combining. In: Souhir D, Joao P M, eds. Proceedings of 4th International Conference on Cognitive Radio Oriented Wireless Networks and Communications, Hannover, Germany,2009. 1-5
[16]  Wang B B, Liu K J R, Clancy T C. Evolutionary cooperative spectrum sensing game: How to collaborate? IEEE Trans Commun, 2010, 58:890-900
[17]  Saad W, Han Z, Debbah M, et al. Coalitional games for distributed collaborative spectrum sensing in cognitive radio networks. In: Artur Z, Li Q, ed. Proceedings of 28th Conference on Computer Communications, Rio de Janeiro, Brazil, 2009. 2114-2122
[18]  Li Z Q, Yu F R, Huang M Y. A distributed consensus-based cooperative spectrum sensing scheme in cognitive radios. IEEE Trans Veh Technol, 2010, 59: 383-393
[19]  Zaheer K, Janne L, Kenta U, et al. On the selection of the best detection performance sensors for cognitive radio networks. IEEE Signal Process Lett, 2010, 17: 359-362
[20]  Guo C, Peng T, Xu S Y, et al. Cooperative spectrum sensing with cluster-based architecture in cognitive radio networks. In: Guillem F, ed. Proceeding of 69-th Vehicular Technology Conference: VTC2009-Spring. Bacolona, Spain, 2009. 1-5
[21]  Pedro A F, Alfonso C, Georgios B G. Distributed clustering using wireless sensor networks. IEEE J Sel Topics Signal Process, 2011, 5:707-724
[22]  Andrea G. Wireless Communications. London: Cambridge University Press, 2005

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