Channel Estimation in MIMO-OFDM by Improved Crow Search Algorithm

Abstract

: Multiple Input Multiple Output (MIMO) is exploited by the current mobile telecommunication systems with the cooperative of Orthogonal Frequency Division Multiplexing (OFDM) that is renowned as MIMO-OFDM to present sturdiness as well as superior spectrum effectiveness. In this case, the main significant confront is to attain a precise channel estimation in order to recognize the information symbols, if the receiver should possess Channel State Information (CSI) in order to balance as well as the procedure the received signal. Therefore, a competent approach is developed by developing the Improved Crow Search algorithm (ICSO) to enhance the MIMO-OFDM system performance in multimedia applications. Additionally, in the MU-MIMO system user admission control is performed by exploiting the priority-based scheduling based on Cat and Mouse Optimization algorithm (CMO) approach which is combined in the STBC-MIMO-OFDM system for competent power allocation to make sure energy effectiveness. In addition, the fitness metrics like priority, power, throughput, and Proportionally Fair are calculated. The simulation is performed in diverse fading environments with three modulation strategies, such as QPSK, BPSK, and QAM with the performance measures, like BER and throughput. The proposed model outperforms the conventional models with minimum BER and maximum throughput.