隐马尔可夫模型
频道(广播)
计算机科学
算法
多普勒效应
传输(电信)
无线
马尔可夫过程
语音识别
人工智能
模式识别(心理学)
数学
电信
统计
天文
物理
作者
Zhongjie Li,Weijie Yuan,Lin Zhou
标识
DOI:10.1109/icccworkshops55477.2022.9896709
摘要
Orthogonal time frequency space (OTFS) modulation is a promising candidate to support reliable information transmission in high-mobility wireless communications. In this paper, we consider the channel estimation problem for OTFS in the presence of fractional Doppler. We first propose a statistical channel model based on the hidden Markov model (HMM) to characterize the structured sparsity of the effective delay-Doppler (DD) domain channel. The HMM prior is then incorporated with the unitary approximate message passing (UAMP) algorithm to solve the structured sparse channel estimation problem. Finally, simulation results verify that the proposed algorithm can achieve a significant gain over various state-of-art algorithms.
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