A Blind OFDM Parameter Estimation Method Based on Cyclicprefix Analysis

摘要

The spectrum sensing problem has augmented new scenarios with cognitive radio and opportunistic spectrum access concepts. Further, it becomes one of the most challenging issues in cognitive radio systems when primary user signal characteristics at secondary level are unavailable. In this paper, we present a novel technique to sense, blindly infer signal features (FFT size, cyclic prefix (CP) length) and detect OFDM signal based on second order cyclostationarity analysis. First, we infer accurate FFT size and CP length from the sensed signal based on cross correlation through considering FFTs of different size (2 L ) and CPs length. In our experimental study, we assume that CP length in the sensed OFDM signal could be 5% to 15% of the FFT size {64, 128, 256, 512, 1024, 2048 and 4096} used at primary user level. We successfully estimate accurate FFT size and CP length and carryout performance analysis of the proposed approach at various channel conditions and effect of increase in sample length (frames) of the sensed signal. In addition to this, we derive recursive procedure to calculate cross-correlation at sample (l+1) using cross-correlation value at sample (l) and few mathematical operations. We have also tested MAX values distribution for FFT size and CP whether inferred parameters are valid or not by finding confidence of estimation. Experimental results show that the proposed approach can be successfully used to measure unknown OFDM signal parameters and to detect OFDM signal blindly in cognitive radio at 0 % false alarm rate with detection rate 100%.