Transmit antenna subset selection in MIMO OFDM system using adaptive mutation Genetic algorithm
Nidhi Sindhwani, Manjit Singh

TL;DR
This paper introduces an adaptive mutation genetic algorithm for selecting optimal transmit antenna subsets in MIMO-OFDM systems, aiming to reduce hardware complexity while maintaining high data rates.
Contribution
It proposes a novel adaptive mutation genetic algorithm for antenna subset selection in MIMO-OFDM, improving efficiency over traditional genetic algorithms.
Findings
Enhanced system capacity with optimal antenna selection
Reduced hardware complexity in MIMO-OFDM systems
Better performance compared to existing genetic algorithms
Abstract
Multiple input multiple output techniques are considered attractive for future wireless communication systems, due to the continuing demand for high data rates, spectral efficiency, suppress interference ability and robustness of transmission. MIMO-OFDM is very helpful to transmit high data rate in wireless transmission and provides good maximum system capacity by getting the advantages of both MIMO and OFDM. The main problem in this system is that increase in number of transmit and receive antennas lead to hardware complexity. To tackle this issue, an effective optimal transmit antenna subset selection method is proposed in paper with the aid of Adaptive Mutation Genetic Algorithm (AGA). Here, the selection of transmit antenna subsets are done by the adaptive mutation of Genetic Algorithm in MIMO-OFDM system. For all the mutation points, the fitness function are evaluated and from that…
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