Applied Mathematics & Information Sciences

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Multiple Input Multiple Output (MIMO) is a technology to meet high data rate necessity for next generation communication system. It can well use the spectrum to enhance the communication throughput. Design a low-complex, high performance detection algorithm for the MIMO system has been a vital issue. The efficient detection of MIMO signal using Modified Memetic Algorithm (MMA) with Quadrature Amplitude Modulation (QAM) varying constellation size is proposed in this paper. The performance of the proposed work is at far with the optimum Maximum Likelihood Detector (MLD) in terms of Bit Error Rate (BER) and computational complexity. Three stages are there in proposed work. In the first stage, using partial ML detections certain bits are detected. The undetected bits in the first stage are calculated in the second stage using soft values generation method. Using MMA algorithm the undetected bits is detected in the last stage. The soft values obtained from second stage and the partial ML bits from the first stage are combined and used as the input for the last stage. In this stage, the best individuals are obtained. MMA uses hill climbing local search technique to obtain the high quality individuals as starting point. The simulation results demonstrate that MMA based MIMO detectors outperformed the state of art detectors for different antenna configurations. Also it gives reduced complexity as compared to the existing detectors. For a 4×4, 16-QAM MIMO system, the proposed work gives BER of 10−4 for 8dB SNR with the complexity value of 51.4.

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