WiMax signal detection
Zhongding Lei, Francois Po Shin Chin · 2008
In this paper, we consider the detection of WiMax signals under noise uncertainty. Based on the special feature - cyclic prefix embedded in WiMax signals, we propose an optimal Neyman-Pearson likelihood test for the signal detection. We have derived rigorously the probability distribution function of the corresponding decision statistics under frequency selective fading channels and obtained the closed forms of the probability of signal detection and the false alarm rate. Since the threshold could be set without prior information on noise power, it can be shown that the algorithm is robust even under noise uncertainty. Simulations have been conducted to illustrate the promising performance of the proposed detection under various channels.