GfcLLL: A Greedy Selection-Based Approach for Fixed-Complexity LLL Reduction

被引：6

作者：

Wen, Jinming ^{[1
]}

Chang, Xiao-Wen ^{[2
]}

机构：

[1] Univ Alberta, Dept Elect & Comp Engn, Edmonton, AB T6G 2V4, Canada

[2] McGill Univ, Sch Comp Sci, Montreal, PQ H3A 0E9, Canada

来源：

IEEE COMMUNICATIONS LETTERS | 2017年 / 21卷 / 09期

基金：

加拿大自然科学与工程研究理事会;

关键词：

Integer least squares problem; fixed-complexity LLL reduction; success probability; GfcLLL; LATTICE REDUCTION; ALGORITHM;

D O I：

10.1109/LCOMM.2017.2712600

中图分类号：

TN [电子技术、通信技术];

学科分类号：

0809 ;

摘要：

The LLL lattice reduction has been widely used to decrease the bit error rate (BER) of the Babai point, but its running time varies much from matrix to matrix. To address this problem, some fixed-complexity LLL reductions (FCLLL) have been proposed. In this letter, we propose two greedy selection-based FCLLL algorithms: GfcLLL(1) and GfcLLL(2). Simulations show that both of them give Babai points with lower BER in similar or much shorter CPU time than existing ones.

引用

页码：1965 / 1968

页数：4

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