Fuzzy channel ranking estimation in cognitive wireless networks

Abstract

In an opportunistic spectrum access (OSA) of cognitive radio wireless networks (CRNs), unlicensed secondary users (cognitive radios, CRs) have only partial knowledge of channel parameters (or other users information) and asymmetric spectral opportunities due to time and space varying channel availabilities. Due to the inherent asymmetry and uncertainty of traffic patterns, CRs can have difficulties to determine properly the real usability of unoccupied channels. In this paper we propose a channel ranking algorithm exploiting fuzzy logic (FL) theory. Using current and prior knowledge of channel availability each CR user builds a channel ranking list that serves as an input entry for an asynchronous neighborhood discovery protocol. Since the rendezvous protocol exploits the channel prioritization, and gives more opportunities to better-quality channels, FL-based channel ranking leads to more efficient communications that traditional crisp value based approaches.