一种基于黏性隐马尔可夫模型的多频带频谱感知方法

doi:10.11959/j.issn.1000-0801.2021018

Abstract

Abstract:

Existing multi-band spectrum sensing methods often use the sparsity of broadband spectrum.However, high spectrum occupancy rate of primary users degrades their performance severely.To address this issue, a novel multi-band spectrum sensing method was proposed by exploiting the state correlation among adjacent frequency bands.Firstly, a sticky hidden Markov model (SHMM) was established by regarding the multi-band states and measured energies as hidden and observed variables.In the SHMM, a sticky factor was introduced to represent the state correlation among adjacent frequency bands.Secondly, iterative expressions for the parameters of SHMM were derived.Finally, multi-band spectrum sensing was implemented by obtaining the posterior mean of observations from every frequency bands.Simulation results show that the proposed method outperforms existing methods, and when the false alarm probability is 0.1, the average frequency band occupancy rate is 50%, and the average signal-to-noise ratio is -12 dB, the detection probability can reach close to 0.99, which is about 30% higher than the detection probability of other methods.In addition, the proposed method had a faster convergence rate than existing methods and therefore has lower computational complexity.

Key words: cognitive radio, multi-band spectrum sensing, sticky hidden Markov model

CLC Number:

TP929.5

Zhongjie JIA, Ming JIN, Xiaoqun SONG. A multi-band spectrum sensing method based on sticky hidden Markov model[J]. Telecommunications Science, 2021, 37(1): 48-57.

Figures/Tables 7

References 19

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参数	取值
最大迭代次数T	100
隐藏状态总数K	4
初始概率分布π	0.25,0.25,0.25,0.25]
均值的先验超参数m₀	1
均值的先验超参数η₀	1
精度的先验超参数a₀	1
精度的先验超参数b₀	1
狄利克雷分布参数γ	1
黏性因子κ	50
样本数N	1 000
蒙特卡洛次数	1 000

A multi-band spectrum sensing method based on sticky hidden Markov model

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