scholarly journals Message-Passing Receiver for Joint Channel Estimation and Decoding in 3D Massive MIMO-OFDM Systems

2016 ◽  
Vol 15 (12) ◽  
pp. 8122-8138 ◽  
Author(s):  
Sheng Wu ◽  
Linling Kuang ◽  
Zuyao Ni ◽  
Defeng Huang ◽  
Qinghua Guo ◽  
...  
Keyword(s):  
Channel Estimation ◽  
Message Passing ◽  
Massive Mimo ◽  
Ofdm Systems ◽  
Mimo Ofdm ◽  
Joint Channel

scholarly journals Distributed Structured Compressive Sensing-Based Time-Frequency Joint Channel Estimation for Massive MIMO-OFDM Systems

2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Wenjie Zhang ◽  
Hui Li ◽  
Rong Jin ◽  
Shanlin Wei ◽  
Wei Cheng ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Channel Estimation ◽  
Massive Mimo ◽  
Orthogonal Frequency Division Multiplexing ◽  
Spectrum Efficiency ◽  
Ofdm Systems ◽  
Time Frequency ◽  
Common Support ◽  
Mimo Ofdm ◽  
Joint Channel

In massive multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) systems, accurate channel state information (CSI) is essential to realize system performance gains such as high spectrum and energy efficiency. However, high-dimensional CSI acquisition requires prohibitively high pilot overhead, which leads to a significant reduction in spectrum efficiency and energy efficiency. In this paper, we propose a more efficient time-frequency joint channel estimation scheme for massive MIMO-OFDM systems to resolve those problems. First, partial channel common support (PCCS) is obtained by using time-domain training. Second, utilizing the spatiotemporal common sparse property of the MIMO channels and the obtained PCCS information, we propose the priori-information aided distributed structured sparsity adaptive matching pursuit (PA-DS-SAMP) algorithm to achieve accurate channel estimation in frequency domain. Third, through performance analysis of the proposed algorithm, two signal power reference thresholds are given, which can ensure that the signal can be recovered accurately under power-limited noise and accurately recovered according to probability under Gaussian noise. Finally, pilot design, computational complexity, spectrum efficiency, and energy efficiency are discussed as well. Simulation results show that the proposed method achieves higher channel estimation accuracy while requiring lower pilot sequence overhead compared with other methods.

scholarly journals Distributed Channel Estimation and Pilot Contamination Analysis for Massive MIMO-OFDM Systems

2016 ◽  
Vol 64 (11) ◽  
pp. 4607-4621 ◽  
Author(s):  
Alam Zaib ◽  
Mudassir Masood ◽  
Anum Ali ◽  
Weiyu Xu ◽  
Tareq Y. Al-Naffouri
Keyword(s):  
Channel Estimation ◽  
Massive Mimo ◽  
Pilot Contamination ◽  
Ofdm Systems ◽  
Mimo Ofdm

scholarly journals Channel Estimation for Massive MIMO-OFDM Systems by Tracking the Joint Angle-Delay Subspace

IEEE Access ◽  
2016 ◽  
pp. 1-1 ◽  
Author(s):  
Yu Zhang ◽  
Dongming Wang ◽  
Jiangzhou Wang ◽  
Xiaohu You
Keyword(s):  
Channel Estimation ◽  
Massive Mimo ◽  
Joint Angle ◽  
Ofdm Systems ◽  
Mimo Ofdm

An Auxiliary Variable-Aided Hybrid Message Passing Approach to Joint Channel Estimation and Decoding for MIMO-OFDM

2017 ◽  
Vol 24 (1) ◽  
pp. 12-16 ◽  
Author(s):  
Zhengdao Yuan ◽  
Chuanzong Zhang ◽  
Zhongyong Wang ◽  
Qinghua Guo ◽  
Jiangtao Xi
Keyword(s):  
Channel Estimation ◽  
Message Passing ◽  
Auxiliary Variable ◽  
Mimo Ofdm ◽  
Joint Channel
Sign in / Sign up

Export Citation Format

Share Document