应用符号相关性的认知OFDM系统信噪比盲估计

Blind SNR estimation applying symbol correlation for cognitive OFDM system

  • 摘要: 针对认知无线电系统中OFDM(orthogonal frequency division multiplexing)信号信噪比估计算法适用范围受限、复杂度高的问题,提出一种新的基于符号相关性的信噪比盲估计算法,算法首先通过扩展前缀相关性检测区间得到一个特征序列,然后通过小波消噪去除多径信道的影响,最后通过序列极大值极小值与信号功率及噪声方差的关系得到信噪比的估计值。仿真结果表明,本文算法能够实现对ZP-OFDM(zero-padding OFDM)信号信噪比的准确估计,同时在应用于CP-OFDM(cyclic-prefix OFDM)信噪比估计时适用范围更广、运算更为简便,更加适用于认知无线电系统。

     

    Abstract: A novel algorithm based on correlation of symbols was proposed to solve the problem of high complexity and poor adaptability of traditional blind SNR estimators for OFDM signals in cognitive radio. Firstly the testing region of correlation of cycle padding correlation is expanded and got a signature sequence. Then use wavelet noise reduction to overcome the effect of multipath fading channel. Finally compute the SNR through the relationship between the max and min of the sequence and signal power and noise variance. Simulation results show that the proposed method can estimate the SNR of ZP-OFDM signals accurately as well as CP-OFDM signals, and gain better adaptability and lower complexity, which has better applicability for cognitive radio.

     

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