标题： GfcLLL：一种基于贪心选择的固定复杂度LLL约化方法 显示英文标题

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

摘要： LLL格约减已被广泛用于降低Babai点的误比特率(BER)，但其运行时间因矩阵而异。为解决这个问题，已经提出了一些固定复杂度的LLL约减(FCLLL)。在本文中，我们提出了两种基于贪心选择的FCLLL算法：GfcLLL(1)和GfcLLL(2)。仿真结果表明，它们在相似或更短的CPU时间内的Babai点具有更低的BER。 显示英文摘要

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 paper, 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.