Title :
Full-Diversity Approximated Lattice Reduction Algorithm for Low-Complexity MIMO Detection
Author :
Kanglian Zhao ; Sidan Du
Author_Institution :
Sch. of Electron. Sci. & Eng., Nanjing Univ., Nanjing, China
Abstract :
In this letter, we propose a new approximated basis vector reordering (ABVR) criterion for low-complexity lattice reduction aided (LRA) multiple-input multiple-output (MIMO) detection. Despite the approximation, the ABVR criterion is proved to collect the full receiving diversity for LRA linear detection. A variant of the well-known complex Lenstra Lenstra Lovász (CLLL) algorithm, i.e., LLL with deep insertion (DLLL), is employed to accommodate the ABVR criterion (DLLL-ABVR). Compared with the original CLLL and other approximated algorithms, the proposed DLLL-ABVR algorithm largely reduces the number of basis vector reordering (BVR) operations. Simulation results show that, on a practical MIMO scale, the proposed lattice reduction algorithm provides similar detection performance, especially for successive interference cancelation (SIC) detectors, while requiring significantly lower computational complexity.
Keywords :
MIMO systems; computational complexity; diversity reception; interference suppression; signal detection; ABVR; CLLL; LRA linear detection; SIC detectors; approximated basis vector reordering criterion; complex Lenstra Lenstra Lovasz algorithm; computational complexity; full-diversity approximated lattice reduction algorithm; low-complexity MIMO detection; successive interference cancelation; Approximation algorithms; Approximation methods; Complexity theory; Detectors; Lattices; MIMO; Vectors; Basis vector reordering (BVR) criterion; lattice reduction; multiple-input multiple-output (MIMO) detection;
Journal_Title :
Communications Letters, IEEE
DOI :
10.1109/LCOMM.2014.2323235