Optimal Pilot-Based Channel Estimation in Cognitive Radio

Abstract

Cognitive radio (CR) technology is to assure the better utilization of the spectrum, permitting the non-licensed users to utilize the unused bands provided to the Licensed or primary users, which is made effective through the application of the Orthogonal Frequency Division Multiplexing (OFDM). The effective utilization of the OFDM channels through temporarily allocating the bands to the unlicensed users avoids interference. In order to ensure the reliable spectrum sensing in CR with effective spectral efficiency, the channel estimation (CE) is enabled in the OFDM-based multi-input and multi-output systems. The channel estimation is facilitated through the pilot-based sequential approach for the least square CE in OFDM-based CR. The optimal insertion of the pilots in the input data symbols before transmitting the signal through the fading OFDM channels in CR is made through the proposed rider grey wolf optimization, which is the integration of the grey wolf optimization and rider optimization algorithm. The estimation is done through the least square of the original channel state and the estimated symbols. The experimental analysis is progressed both in Rician and Rayleigh environments with minimal mean square error of 1.28E−06 and bit error rate of 0.000626.