Improved MCAS Based Spectrum Sensing with Multiple Antennas

Abstract

This letter presents improved maximum cyclic autocorrelation selection (MCAS) based spectrum sensing techniques with multiple antennas. The improved MCAS based spectrum sensing employs two types of statistic; one includes an information of target signals and another one is for the comparison with the former one. These statistics are computed from a cyclic autocorrelation function (CAF) at only one cyclic frequency. In this letter, we attempt to enhance the performance of signal detection by selecting a receive antenna element with a minimum statistic for the comparison. The presented results are compared with some conventional results. Numerical examples are shown to validate the effectiveness of the presented technique and the performance of the presented technique is superior to the conventional technique.