Asymptotic Performance of Box-RLS Decoders Under Imperfect CSI With Optimized Resource Allocation

This paper considers the problem of symbol detection in massive multiple-input multiple-output (MIMO) wireless communication systems. We consider hard-thresholding preceded by two variants regularized least squares (RLS) decoder; namely unconstrained RLS and with a box constraint, which is called Box-RLS. For all schemes, we focus on evaluation mean squared error (MSE) probability (SEP) for M-ary pulse amplitude modulation (M-PAM) symbols transmitted over MIMO system when channel estimated using linear minimum (LMMSE) estimator. Under such circumstances, estimation Gaussian allows use convex min-max theorem (CGMT) to derive asymptotic approximations MSE SEP dimensions coherence duration grow large same pace. The obtained expressions are then leveraged optimal power distribution between pilot data under total transmit energy constraint. In addition, an approximation goodput schemes used jointly optimize number training their associated power. Numerical results presented support accuracy theoretical results.