一种基于信誉度的航空无线电协作频谱感知方法

doi:10.11959/j.issn.1000-0801.2015145

摘要/Abstract

摘要：

摘要：传统的航空无线电协作频谱感知算法无法区分节点的性质（普通/恶意），而新的加权序贯检测（weighted sequential probability ratio test,WSPRT）算法虽然解决了这个问题，但在具有频谱感知数据篡改（spectrum sensing data falsification,SSDF）攻击节点的环境中，无法保持高的感知正确率。提出了一种改进型WSPRT 算法，在传统的 WSPRT 算法基础上改进了信誉度奖惩方案，增加了临近时间内感知稳定度的量化。从实验仿真结果看，改进后的算法不仅时间复杂度更低，而且能够有效地识别恶意节点，对于恶意用户的判定更准确。

关键词: 认知无线电, WSPRT, 协作频谱感知, SSDF

Abstract:

The traditional cooperative spectrum sensing algorithm of aeronautical radio can't distinguish the node type（normal/malicious）, though weighted sequential probability ratio test（WSPRT）method meets the requirement but when the spectrum sensing data falsification（SSDF）node is exist, it can't keep high sensing accuracy any more. An improved WSPRT was proposed. On the foundation of traditional WSPRT, reputation rewards and punishment algorithm was improved, and sensing stability factor was taken into account. The simulation results show that it can make identify malicious cognitive nodes easier and make the fusion algorithm distinguish malicious user more accurate.

Key words: cognitive radio, weighted sequential probability ratio test, cooperative spectrum sensing, spectrum sensing data falsification

李玉峰,胡乃瑞,王宇鹏. 一种基于信誉度的航空无线电协作频谱感知方法[J]. 电信科学, 2015, 31(9): 118-123.

Yufeng Li,Nairui Hu,Yupeng Wang. A Cooperative Spectrum Sensing Method of Aeronautical Radio Based on Reputation[J]. Telecommunications Science, 2015, 31(9): 118-123.

图/表 5

参考文献 12

1	Mitola J , Maguire G J . Cognitive radio making software radios more personal. Personal Communications,IEEE, 1999,6（4）:13～18
2	Liang Y , Chen K , Li G Y , et al. Cognitive radio networking and communications: an overview. IEEE Transactions on Vehicular Technology, 2011,60（7）:3386～3407
3	Yang P , Xiao Y , Li L , et al. An improved matched-filter based detection algorithm for space-time shift keying systems. Signal Processing Letters, IEEE, 2012,19（5）:271～274
4	Arezumand H , Azmi P , Sadeghi H . Cooperative spectrum sensing based on a low-complexity cyclostationary detection method for cognitive radio networks. Proceedings of Computer and Knowledge Engineering（ICCKE）, Mashhad, Iran, 2011:308～313
5	Ping Y , Li Y M , Heung-Gyoon R . On the performance of covariance based spectrum sensing for cognitive radio. IEEE Transactions on Signal Processing, 2012,60（7）:3670～3682
6	Saeid S , Abbas T , Josep S . Spectrum sensing using correlated receiving multiple antennas in cognitive radios. IEEE Transactions on Wireless Communications, 2013,12（11）:5754～5766
7	Zhao J H , Li F , Yang T . Weight sequential log-likelihood ratio detect algorithm with malicious users removing. Journal of China Universities of Posts and Telecommunications, 2013（2）:60～65
8	Quan Z , Cui S , Sayed A H . An optimal strategy for cooperative spectrum sensing in cognitive radio networks. Proceedings of 50th Annual IEEE Global Telecommunications Conference （GLOBECOM 2007）, New Orleans, LA, 2007:2947～2951
9	Visser F E , Janssen G M , Paweczak P . Multinode spectrum sensing based on energy detection for dynamic spectrum access. Proceedings of Vehicular Technology Conference（VTC Spring）, Marina Bay, Singapore, 2008:1394～1398
10	裴庆棋，李红宁，赵弘洋等．认知无线电网络安全综述．通信学报， 2013,34（1）:144～158 Pei Q Q , Li H N , Zhao H Y , et al. Security in cognitive radio networks. Journal on Communications, 2013,34（1）:144～158
11	Ming Z , Shen J F , Chen H F , et al. A cooperative spectrum sensing scheme based on the Bayesian reputation model in cognitive radio networks. Proceedings of Wireless Communications and Networking Conference, Paris,France, 2013:614～619
12	Zhang L , Wu Q , Ding G et al. Performance analysis of probabilistic soft SSDF attack in cooperative spectrum sensing. Eurasip Journal on Advances in Signal Processing, 2014（1）:81～89

算法种类	运行时间/s
“与”算法	0.005 71
WSPRT算法	2.328 77
本文改进算法	1.217 49

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