Introduction to Algorithms
Multiuser detection techniques using maximum likelihood sphere decoding in multicarrier CDMA systems
IEEE Transactions on Wireless Communications
Closest point search in lattices
IEEE Transactions on Information Theory
Lattice decoding for joint detection in direct-sequence CDMA systems
IEEE Transactions on Information Theory
On maximum-likelihood detection and the search for the closest lattice point
IEEE Transactions on Information Theory
A unified framework for tree search decoding: rediscovering the sequential decoder
IEEE Transactions on Information Theory
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An efficient regularization approach is proposed for decoding underdetermined multiple input multiple output (MIMO) systems. The main idea is to transform an underdetermined integer least squares problem to an equivalent overdetermined integer least squares problem by using part of the transmit vector to do a regularization. Some strategies are proposed to enhance the efficiency of this approach. Specifically, we discuss how many entries of the transmit vector should be chosen and how to choose them when we do the regularization. An empirical formula for the regularization parameter is presented. Simulation results indicate that this modified approach can be much more efficient than current approaches for any square constellation higher than 4QAM.