Channel-adaptive complex K-best MIMO detection using lattice reduction

Lattice reduction (LR) aided detectors mitigate the exponentially increasing complexity of large multiple-input, multiple-output (MIMO) systems while achieving near-optimal performance with low computational complexity. In this paper, a channel-adaptive complex-domain LR-aided K-best MIMO detector is presented that reduces the gap between the K-best sphere decoding (SD) detector and the maximum likelihood (ML) optimal MIMO detector. While maintaining BER performance, computational complexity is reduced by 50% over a conventional complex domain K-best SD detector by implementing a new on-demand complex-domain candidate symbol selection algorithm. Two tunable variables in the candidate selection process are introduced to enable both coarse-grained and fine-grained adaptation of computational complexity to channel conditions.