A Quick Wideband Spectrum Sensing Algorithm Based On Analog Filter

Abstract

Wideband spectrum sensing is very essential in Cognitive Radio (CR) systems. In order to improve the opportunistic throughput for mobile devices, the CR must sense the signals in multiple bands or wideband quickly and efficiently. The relevant literature has discussed a lot about OFDM and compressed sensing to deal with the wideband detection of signals. In this paper, we propose a quick analog-filter based spectrum sensing algorithm, using energy detection in each sub-band. The insight idea of this algorithm is that we use exponential sense to quickly find out the sequential sub-bands which are clear in the wideband, and linear sense to find the occupied sub-bands in the sensing window step by step. Furthermore, we design a dynamic adaptive algorithm to optimize the total time of sensing. This algorithm is much faster than sequential scan and much cheaper than using a wideband radio. Meanwhile, it can reach the same asymptotic complexity as compressed while the realization is much easier. Further performance improvement can be achieved through channel bonding. It is shown that our algorithm can obtain an excellent wideband spectrum sensing performance without the sparsity information.