Robust constrained-optimization-based linear receiver for high-rate MIMO-OFDM against channel estimation errors

Abstract

We consider multi-input multi-output-orthogonal frequency division multiplexing (MIMO-OFDM) transmission in a scenario that the adopted cyclic-prefix (CP) length is shorter than the channel delay spread for boosting data rate and, moreover, the channel parameters are not exactly known but are estimated using the least-squares (LS) training technique. By exploiting the receiver spatial resource, we propose a constrained-optimization-based linear equalizer which can mitigate inter-symbol interference and inter-carrier interference incurred by insufficient CP interval, and is robust against the net detrimental effects caused by channel estimation errors. The optimization problem is formulated in an equivalent unconstrained generalized-sidelobe-canceller (GSC) setup. The channel parameter error is explicitly incorporated into the constraint-free GSC system model through the perturbation technique; this allows us to exploit the presumed LS channel error property for deriving a closed-form solution, and can also facilitate an associated analytic performance analysis. A closed-form approximate signal-to-interference-plus-noise ratio (SINR) expression for the proposed robust scheme is given, and an appealing formula of the achievable SINR improvement over the nonrobust counterpart is further specified. Our analytic results bring out several intrinsic features of the proposed solution. Simulation study confirms the effectiveness of the proposed method and corroborates the predicted SINR results.