Spectrum Sensing for Cognitive Radios Based on Space-Time FRESH Filtering

In this paper, we consider the problem of spectrum sensing of cyclostationary signals for cognitive radios. It is shown that the detection performance in this case may be improved by enhancing the cyclostationary features of the signal of interest. The optimal filter for cyclostationary features is revisited, following which an adaptive space-time structure exploiting the spatial, temporal and spectral coherence of a cyclostationary signal incident upon an antenna array is proposed for enhancing the signal. A low complexity adaptation algorithm for this structure is also proposed. The performance of this detector is evaluated and compared with standard spectrum sensing methods. Simulation results show that a suitable space-time FRESH filtering configuration may be used to yield gains of up to 10 dB over both the standard energy detector and the traditional cyclostationary detector.