We propose a lattice-reduction (LR)-aided breadth-first tree searching algorithm for MIMO detection achieving near-optimal performance with very low complexity. At each level of the tree in the search, only the paths whose accumulated metrics satisfy a particular restriction condition will be kept as the candidates. Furthermore, the number of child nodes expanded on each parent node, and the maximum number of candidates preserved at each level, are also restricted, respectively. All these measures ensure the proposed algorithm reaching a preset near-optimal performance and achieving very low average and maximum computational complexity. Simulation results verify the proposed algorithm’s higher efficiency in terms of the performance/complexity tradeoff than the existing LR-aided K-best detectors and LR-aided fixed-complexity sphere decoders.
['Jinzhu Liu', 'Song Xing', 'Lianfeng Shen']
Lattice-Reduction-Aided Breadth-First Tree Searching Algorithm for MIMO Detection