Low-Complexity Soft-Output MIMO Detectors Based on Optimal Channel Puncturing

Channel puncturing transforms a multiple-input multiple-output (MIMO) channel into sparse lower-triangular form using the so-called WL decomposition scheme in order to reduce tree-based detection complexity. We propose computationally efficient soft-output detectors based on two forms of puncturing: augmented and two-sided. The detector (AWLD) employs punctured derived by triangularizing true form, followed left-sided Gaussian elimination. two-sided (dubbed WLZ) right-sided reduction elimination puncture channel. prove that is optimal maximizing lower-bound achievable information rate (AIR) new mismatched model. show AWLD decomposes an MMSE prefilter gain compensation stages, regular (WLD) computes least-squares soft-decision estimates. Similarly, WLZ pre-processing step WLD. attains same performance as existing AIR-based partial marginalization (PM) detector, but with less computational empirically best complexity-performance tradeoff among detectors.