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This paper explores the benefit of using some of the machine learningtechniques and Big data optimization tools in approximating maximum likelihood(ML) detection of Large Scale MIMO systems. First, large scale MIMO detectionproblem is formulated as a LASSO (Least Absolute Shrinkage and SelectionOperator) optimization problem. Then, Alternating Direction Method ofMultipliers (ADMM) is considered in solving this problem. The choice of ADMM ismotivated by its ability of solving convex optimization problems by breakingthem into smaller sub-problems, each of which are then easier to handle.Further improvement is obtained using two stages of LASSO with interferencecancellation from the first stage. The proposed algorithm is investigated atvarious modulation techniques with different number of antennas. It is alsocompared with widely used algorithms in this field. Simulation resultsdemonstrate the efficacy of the proposed algorithm for both uncoded and codedcases.

Two-Stage LASSO ADMM Signal Detection Algorithm For Large Scale MIMO