In this paper, we propose an iterative receiver based on gridless variational Bayesian line spectra estimation (VALSE) named JCCD-VALSE that \emph{j}ointly estimates the \emph{c}arrier frequency offset (CFO), the \emph{c}hannel with high resolution and carries out \emph{d}ata decoding. Based on a modularized point of view and motivated by the high resolution and low complexity gridless VALSE algorithm, three modules named the VALSE module, the minimum mean squared error (MMSE) module and the decoder module are built. Soft information is exchanged between the modules to progressively improve the channel estimation and data decoding accuracy. Since the delays of multipaths of the channel are treated as continuous parameters, instead of on a grid, the leakage effect is avoided. Besides, the proposed approach is a more complete Bayesian approach as all the nuisance parameters such as the noise variance, the parameters of the prior distribution of the channel, the number of paths are automatically estimated. Numerical simulations and sea test data are utilized to demonstrate that the proposed approach performs significantly better than the existing grid-based generalized approximate message passing (GAMP) based \emph{j}oint \emph{c}hannel and \emph{d}ata decoding approach (JCD-GAMP). Furthermore, it is also verified that joint processing including CFO estimation provides performance gain.
翻译:在本文中,我们提议基于无网格变异的巴伊西亚线光谱估计的迭代接收器,名为 JCCD- VALSE 的 JCCD- VALSE (VALSE), 以 emph{j} ointly 估计 /emph{c} 增强频率( CFO), 高分辨率的\ emph{ c} 卫生网, 并进行 emph{ d} 解码。 基于一个模块化观点, 并受高分辨率和低复杂性的VALSE算法驱动, 三个模块命名为 VALSE 模块、 最低平均平方差( MMSE) 模块和解码模块。 模块之间交换了软信息, 以逐步改进频道估计和数据解码精确度。 由于频道多路径的延迟被视为连续参数, 而不是在网格上, MSDMD\ 。 此外, 拟议的方法更完整, 巴伊西亚方法, 如噪音差异、 先前的分布参数, 路径数是自动估算的。 NumicCD 和海域域域域域分析工具, 用来 。