LAUSR

In this paper, we propose a low-complexity multistage polyphase filter bank for the detection and estimation of center frequency of wireless microphone (WM) in television channels for cognitive radios. The detection precision is directly related to the number of subbands (granularity) in the filter bank. This implies that the computational complexity becomes high if the number of stages and granularity of the filter bank structure are increased. The novelty of the proposed method is the estimation of center frequency with higher precision and reduced computational complexity using the centroid method. The merit of the centroid method is that the presence of WM can be detected along with estimation of center frequency in the first stage, if the WM lies partly in one subband and partly in the adjacent subband. This single-stage detection and estimation of WM significantly reduces computational and hardware complexities as well as latency. However, if the WM appears anywhere exclusively within a single subband, the detection process can be completed in the second stage without ambiguity. A mathematical expression for calculating the center frequency of WM from the subband energy (power) using centroid method is also derived and presented. The proposed scheme is analyzed and validated through extensive simulations for the detection of WM. The error in estimation of center frequency in most of the cases is less than 4 % for SNR variations from 0 to −20 dB.