Minkowski's convex body theorem and integer programming
Mathematics of Operations Research
An upper bound on the average number of iterations of the LLL algorithm
Theoretical Computer Science - Special issue on number theory, combinatorics and applications to computer science
A course in computational algebraic number theory
A course in computational algebraic number theory
Lattice Reduction in Cryptology: An Update
ANTS-IV Proceedings of the 4th International Symposium on Algorithmic Number Theory
Condition Numbers of Gaussian Random Matrices
SIAM Journal on Matrix Analysis and Applications
Complex lattice reduction algorithm for low-complexity full-diversity MIMO detection
IEEE Transactions on Signal Processing
Asymptotic performance of linear receivers in MIMO fading channels
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
On maximum-likelihood detection and the search for the closest lattice point
IEEE Transactions on Information Theory
LLL Reduction Achieves the Receive Diversity in MIMO Decoding
IEEE Transactions on Information Theory
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Lattice reduction algorithms, such as the LenstraLenstra-Lovasz (LLL) algorithm, have been proposed as preprocessing tools in order to enhance the performance of suboptimal receivers in multiple-input multiple-output (MIMO) communications. A different approach, introduced by Kim and Park, allows to combine right preprocessing and detection in a single step by performing lattice reduction on an "augmented channel matrix". In this paper we propose an improvement of the augmented matrix approach which guarantees a better performance. We prove that our method attains the maximum receive diversity order of the channel. Simulation results evidence that it significantly outperforms LLL reduction followed by successive interference cancellation (SIC) while requiring a moderate increase in complexity. A theoretical bound on the complexity is also derived.