Fixed-Complexity Soft MIMO Detection via Partial Marginalization
IEEE Transactions on Signal Processing - Part I
A QRD-M/Kalman filter-based detection and channel estimation algorithm for MIMO-OFDM systems
IEEE Transactions on Wireless Communications
Fixing the Complexity of the Sphere Decoder for MIMO Detection
IEEE Transactions on Wireless Communications
A universal lattice code decoder for fading channels
IEEE Transactions on Information Theory
On maximum-likelihood detection and the search for the closest lattice point
IEEE Transactions on Information Theory
From theory to practice: an overview of MIMO space-time coded wireless systems
IEEE Journal on Selected Areas in Communications
Adaptive control of surviving symbol replica candidates in QRM-MLD for OFDM MIMO multiplexing
IEEE Journal on Selected Areas in Communications
EURASIP Journal on Advances in Signal Processing - Special issue on advances in single carrier block modulation with frequency domain processing
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In this paper, a reduced-complexity multiple-input multiple-output (MIMO) detector for the spatial multiplexing systems is described. It incorporates the idea of Ungerboeck's set partitioning in the tree search to reduce the computational complexity. An algorithm that adapts the number of partitions based on the channel conditions is proposed to achieve a better tradeoff between complexity and performance. Simulation results are presented to demonstrate the efficacy of the proposed algorithm under the assumptions of perfect channel and noise power estimates.