On the design of Massive MIMO-QAM detector via ℓ_2-Box ADMM approach
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In this letter, we develop an ℓ_2-box maximum likelihood (ML) formulation for massive multiple-input multiple-output (MIMO) quadrature amplitude modulation (QAM) signal detection and customize an alternating direction method of multipliers (ADMM) algorithm to solve the nonconvex optimization model. In the ℓ_2-box ADMM implementation, all variables are solved analytically. Moreover, several theoretical results related to convergence, iteration complexity, and computational complexity are presented. Simulation results demonstrate the effectiveness of the proposed ℓ_2-box ADMM detector in comparison with state-of-the-arts approaches.
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