基于空间谱的多天线盲频谱感知算法

doi:10.11959/j.issn.1000-436x.2015087

摘要/Abstract

摘要：

现有的频谱感知算法主要在时间、频率以及地理空间维度进行检测，对角度维的利用尚不成熟。将多天线技术中的到达角（AOA，angle of arrival）估计算法应用到频谱感知领域，提出了2种基于空间谱的盲频谱感知算法，分别为最大—最小延迟相加谱值比检测和平均—最小延迟相加谱值比检测。利用空域匹配滤波的优势，新算法在低信噪比下得到了较高的检测概率，同时为角度维的频谱接入提供了AOA信息，从而提高了频谱利用率。此外，运用随机矩阵理论，推导了检测阈值和检测概率的理论值。仿真结果表明，在 Nakagami-m 信道下，提出的算法具有比现有盲感知算法更优的检测性能。

关键词: 频谱感知, AOA估计, 空间谱, 空域匹配滤波, 随机矩阵

Abstract:

State-of-the-art sensing methods only exploit three dimensions of the spectrum space:frequency，time and space whereas the angle dimension has not been exploited well enough for opportunistic spectrum access.Motivated by this，the authors apply angle of arrival (AOA) estimation algorithm to spectrum sensing and propose two blind spectrum sensing methods based on spatial spectrum.First is based on the ratio of maximum to minimum delay-sum spatial spectrum; the other is based on the ratio of average to minimum delay-sum spatial spectrum.Taking the advantage of spatial matched filtering，the proposed methods can achieve high probability of detection as well as offer the AOA information for spectrum access，which improve the spectrum efficiency.In addition，utilizing latest random matrix theories (RMT)，this work quantifies the detection threshold and derives the probabilities of detection for the proposed methods in theory.Extensive simulations carried out in Nakagami-m fading channel indicate that the proposed methods outperform the existing blind spectrum sensing methods.

Key words: spectrum sensing, AOA estimation, spatial spectrum, spatial matched filtering, random matrix theories

刘畅,张锐,李思莹,王洁,金明录. 基于空间谱的多天线盲频谱感知算法[J]. 通信学报, 2015, 36(4): 115-124.

Chang LIU,SajjadAli Syed,Rui ZHANG,Si-ying LI,Jie WANG,Ming-lu JIN. Spatial spectrum based blind spectrum sensing for multi-antenna cognitive radio system[J]. Journal on Communications, 2015, 36(4): 115-124.

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参考文献 29

[1]	FCC，Spectrum Policy Task Force Report，E D N 02-135[R]. Washington DC， 2002.
[2]	MITOLA III J ， MAGUIRE JR G Q . Cognitive radio:making software radios more personal[J]. IEEE Personal Communications， 1999，6(4): 13-18.
[3]	YUCEK T ， ARSLAN H . A survey of spectrum sensing algorithms for cognitive radio applications[J]. IEEE Communications Surveys & Tutorials， 2009，11(1): 116-130.
[4]	LEE W ， CHO D H . Enhanced spectrum sensing scheme in cognitive radio systems with MIMO antennae[J]. IEEE Transactions on Vehicular Technology， 2011，60(3): 1072-1085.
[5]	AXELL E ， LEUS G ， LARSSON E ，et al. Spectrum sensing for cognitive radio:state-of-the-art and recent advances[J]. IEEE Signal Processing Magazine， 2012，29: 101-116.
[6]	YIN S ， CHEN D ， ZHANG Q ，et al. Prediction-based throughput optimization for dynamic spectrum access[J]. IEEE Transactions on Vehicular Technology， 2011，60(3): 1284-1289.
[7]	CHEN Y ， WANG C ， ZHAO B . Performance comparison of feature-based detectors for spectrum sensing in the presence of primary user traffic[J]. IEEE Signal Processing Letters， 2011，18(5): 291-294.
[8]	BOKHARAIEE S ， NGUYEN H H ， SHWEDYK E . Blind spectrum sensing for OFDM-based cognitive radio systems[J]. IEEE Transactions on Vehicular Technology， 2011，60(3): 858-871.
[9]	ZENG Y ， LIANG Y C ， HOANG A T ，et al. A review on spectrumsensing for cognitive radio:challenges and solutions[J]. EURASIP Journal on Advances in Signal Processing， 2010(2).
[10]	KAY S M . Fundamentals of Statistical Signal Processing，Volume 2:Detection Theory[M]. Prentice Hall PTR， 1998.
[11]	GARDNER W A . Exploitation of spectral redundancy in cyclostationary signals[J]. IEEE Signal Processing Magazine， 1991，8: 14-36.
[12]	CHEN H S ， GAO W ， DAUT D G.Signature based spectrum sensing algorithms for IEEE 802 . 22 WRAN[A]. IEEE International Conference on Communications[C]. Glasgow，Scotland， 2007. 6487-6492.
[13]	URKOWITZ H . Energy detection of unknown deterministic signals[J]. Proceedings of the IEEE， 1967，55(4): 523-531.
[14]	TANDRA R ， SAHAI A . SNR walls for signal detection[J]. IEEE Journal of Selected Topics in Signal Processing， 2008，2: 4-17.
[15]	ZENG Y ， LIANG Y C . Eigenvalue-based spectrum sensing algorithms for cognitive radio[J]. IEEE Transactions on Communications， 2009，57(6).
[16]	ZENG Y ， LIANG Y C . Covariance based signal detections for cognitive radio[A]. Proceedings of the 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks[C]. Dublin，Ireland， 2007. 202-207.
[17]	ZHANG R ， LIM T J ， LIANG Y C ，et al. Multi-antenna based spectrum sensing for cognitive radios:a GLRT approach[J]. IEEE Transactions on Communications， 2010，58(1): 84-88.
[18]	TSAKALAKI E P ， ALRABADI O N ， PAPADIAS C B ，et al. Spatial spectrum sensing for wireless handheld terminals:design challenges and novel solutions based on tunable parasitic antennas Dynamic Spectrum Management[J]. IEEE Wireless Communications， 2010，17(4): 33-40.
[19]	WILCOX D ， TSAKALAKI E ， KORTUN A ，et al. On spatial domain cognitive radio using single-radio parasitic antenna arrays[J]. IEEE Journal on Selected Areas in Communications， 2013，31(3): 571-580.
[20]	BARTLETT M S . An Introduction to Stochastic Processes:With Special Reference to Methods and Applications[M]. CUP Archive， 1978.
[21]	VAN V B D ， BUCKLEY K M . Beamforming:a versatile approach to spatial filtering[J]. IEEE ASSP Magazine， 1988，5(2): 4-24.
[22]	TULINO A M，VERDú S . Random Matrix Theory and Wireless Communications[M]. Now Publishers Inc， 2004.
[23]	ZETTERBERG P ， OTTERSTEN B . The spectrum efficiency of a base station antenna array system for spatially selective transmission[J]. IEEE Transactions on Vehicular Technology， 1995，44(3): 651-660.
[24]	PILLAY N ， XU H J . Blind eigenvalue-based spectrum sensing for cognitive radio networks[J]. IET Communications， 2012，6(11): 1388-1396.
[25]	GROSS F B . Smart Antennas for Wireless Communications:With MATLAB[M]. New York: McGraw-HillPress， 2005.
[26]	王永良，丁前军，李荣锋 . 自适应阵列处理[M]. 北京：清华大学出版社， 2009. WANG Y L ， DING Q J ， LI R F . Adaptive Array Processing[M]. Beijing: Tsinghua University PressPress， 2009.
[27]	NEUMANN M . Weak stability for matrices[J]. Linear and multilinear algebra， 1979，7(3): 257-262.
[28]	王磊，郑宝玉，崔景伍 . 基于随机矩阵理论的频谱感知技术研究综述[J]. 信号处理， 2011，27(12): 1889-1897. WANG L ， ZHENG B Y ， CUI J W . Survey on the research of spectrum sensing technologies based on random matrix theory[J]. Journal of Signal Processing， 2011，27(12): 1889-1897.
[29]	金明，李有明，高洋 . 基于广义特征值的合作频谱感知方法[J]. 通信学报， 2013，34(1): 105-110. JIN M ， LI Y M ， GAO Y . Cooperative spectrum sensing detector based on generalized eigenvalue[J]. Journal on Communications， 2013，34(1): 105-110.

天线个数M	F ²(ψ)，d=λ/2
2	1.384
4	2.678
6	3.958
8	5.233
10	6.505

P_fa理论值	MMDS	AMDS
0.02	0.015 1	0.019 5
0.04	0.026 2	0.030 1
0.06	0.043 6	0.041 2
0.08	0.051 7	0.052 3
0.1	0.070 2	0.060 2