MIMO Detection Algorithm for Metaheuristic Maximum-Likelihood
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For multiple-input multiple-output (MIMO) systems, the optimum maximum likelihood (ML) detection requires tremendous complexity as the number of antennas or modulation level increases. This paper proposes a new algorithm which attains the ML performance with significantly reduced complexity Based on the metaheuristic algorithm HISD (Hyperplane Intersection and Selection Detector). We apply a new type of cost function and give an efficient calculation algorithm. This detection is determinate from the diversification and the intensification methods.
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