EFFICIENT PAPR REDUCTION TECHNIQUES FOR MIMO-OFDM BASED COGNITIVE RADIO NETWORKS

This paper presents an efficient peak to average power ratio (PAPR) reduction schemes for a multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) based cognitive radio (CR) network. The proposed scheme makes use of a constrained adaptive Markov chain Monte Carlo (CAMCMC) technique to select peak reduction tones (PRT) for the tone reservation (TR) technique. The CAMCMC algorithm exploits non contiguous (NC) subcarriers available for a secondary user (SU) and make appropriate selection of the PRT set to reduce the PAPR of a MIMO-OFDM based CR system. To the selected PRT set, adaptive amplitude clipping (AAC) technique as well as convex optimization based schemes are employed to reduce the PAPR of the SU with multiple transmit antennas. Numerical simulations are provided to corroborate the efficacy of the designed PRT set with the AAC algorithm and the convex optimization technique.