Novel Lattice Reduction Algorithms: Precoder reduction and vector perturbation tradeoffs

In this letter we present a novel iterative lattice reduction algorithm in precoded multiple input multiple output (MIMO) transmission. A unified framework is developed for this purpose, to reduce the precoder maximum row norm by iteratively minimizing the weighted sum of the precoder rownorms. We show that at each iteration in the optimization, the objective can be minimized using the least-squares or the sphere encoding (SE) or equivalently sphere decoding traditionally used for uplink data detection or for the computation of the vector perturbation (VP) in downlink precoded MIMO systems. We further investigate the different tradeoffs between the precoder reduction and the VP computation. Simulation results reveal that the proposed SE-based lattice reduction algorithm outperforms the state of the art LLL algorithm, and further relaxes the usage of advanced complex VP algorithms such as the sate of the art SE.