A new joint channel equalization and estimation algorithm for underwater acoustic channels
A new joint channel equalization and estimation algorithm for underwater acoustic channels
复制标题
一种新的水声信道联合信道均衡和估计算法
DOI：
10.1186/s13638-017-0955-7
复制
发表时间：
2017
影响因子：
2.6
通讯作者：
Gongliang Liu
中科院分区：
文献类型：
--
作者：
Bo Li;Hongjuan Yang;Gongliang Liu
水声信道是当今世界上最具挑战性的通信信道之一，它具有复杂的多途性、吸收性和多变的环境噪声。虽然自适应均衡可以有效地消除符号间干扰（ISI）的训练序列的帮助下，稀疏UAC均衡的收敛速度显着下降。此外，信道估计算法可以通过一些特定的数学准则粗略地计算出信道冲激响应和其他信道参数。本文将一种典型的信道估计方法--最小二乘（LS）算法应用于自适应均衡中，以获得最小均方（LMS）算法的初始抽头权值。仿真结果表明，该方法显著提高了LMS算法的收敛速度。
Underwater acoustic channel (UAC) is one of the most challenging communication channels in the world, owing to its complex multi-path and absorption as well as variable ambient noise. Although adaptive equalization could effectively eliminate the inter-symbol interference (ISI) with the help of training sequences, the convergence rate of equalization in sparse UAC decreased remarkably. Besides, channel estimation algorithms could roughly figure out channel impulse response and other channel parameters through several specific mathematical criterions. In this paper, a typical channel estimation method, least square (LS) algorithm, is applied in adaptive equalization to obtain the initial tap weights of least mean square (LMS) algorithm. Simulation results show that the proposed method significantly enhances the convergence rate of the LMS algorithm.