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In this paper, we develop a novel iterative equalization algorithm for energy-spreading-transform (EST) based multiple-input multiple-output (MIMO) systems. We show that the proposed scheme significantly outperforms the existing non-linear MIMO equalizers in various system setups. We further investigate the precoder design based on the signal-to-interference-plus-noise-ratio (SINR) variance evolution...
Asymptotic analysis of the dual-diagonal (DD) linear-minimum-mean-square-error (LMMSE) channel estimation for orthogonal frequency-division multiplexing (OFDM) systems is presented. We prove that the DD-LMMSE estimator is asymptotically optimal among all DD estimators as the number of subcarriers tends to infinity. Based on the asymptotic analysis, we propose an evolution tool to predict the performance...
We propose a dual diagonal linear-minimum-mean-square-error (DD-LMMSE) channel estimation algorithm for orthogonal frequency division multiplexing (OFDM) systems involving joint channel estimation and signal detection. Computational complexity and mean-square-error (MSE) analysis are presented to evaluate the efficiency of the proposed algorithm. Compared with the optimal LMMSE method, the proposed...
We extend the area property to more general linear channel models (including inter-symbol-interference (ISI) and multiple-input multiple-output (MIMO) systems) with arbitrary input constellations. We show that the theoretical limit of a channel (i.e., the mutual information) can be achieved under some assumptions. Several engineering techniques are examined to ensure these assumptions. It is shown...
In this paper, we study the iterative detection problem for a coded system with multi-ary modulation. We show that, with iterative linear minimum-mean-square-error (LMMSE) detection, superposition coded modulation (SCM) can provide performance superior to that with other traditional signaling schemes used in trellis coded modulation (TCM) and bit-interleaved coded modulation (BICM). This finding provides...
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