  In this paper, we introduce a new detection algorithm for large-scale
wireless systems, referred to as post sparse error detection (PSED) algorithm,
that employs a sparse error recovery algorithm to refine the estimate of a
symbol vector obtained by the conventional linear detector. The PSED algorithm
operates in two steps: 1) sparse transformation converting the original
non-sparse system into the sparse system whose input is an error vector caused
by the symbol slicing and 2) estimation of the error vector using the sparse
recovery algorithm. From the asymptotic mean square error (MSE) analysis and
empirical simulations performed on large-scale systems, we show that the PSED
algorithm brings significant performance gain over classical linear detectors
while imposing relatively small computational overhead.
