期刊
IEEE COMMUNICATIONS LETTERS
卷 20, 期 11, 页码 2225-2228出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LCOMM.2016.2598810
关键词
Channel estimation; expectation propagation; massive MIMO; OFDM
资金
- National Nature Science Foundation of China [91338101, 61231011, 91438206]
- National Basic Research Program of China [2013CB329001]
- Tsinghua University Initiative Scientific Research Program [20131089219]
To address the challenging problem of downlink channel estimation with low pilot overhead in massive multiple-input multiple-output (MIMO) systems, an empirical Bayesian block expectation propagation (EP) algorithm is proposed. Specifically, a block Bernoulli-Gaussian prior channel model is proposed to fit the underlying block sparsity, and a block EP algorithm is derived to estimate the channels more accurately by clustering all the channel taps that pertain to the same delay, while the model parameters are learned by minimizing the Bethe free energy. Simulation results show that the proposed algorithm achieves considerable reduction of pilot overhead in a massive MIMO system with tens of antennas, while maintaining superior channel estimation performance.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据