Matching Pursuit versus threshold-based approach for channel estimation in OFDM systems

2012 ◽  
Author(s):  
Zakia Jellali ◽  
Leila Najjar Atallah
Keyword(s):  
Channel Estimation ◽  
Matching Pursuit ◽  
Ofdm Systems

Channel Estimation Based on Compressed Sensing Technique for Low-Voltage Power Line Communication

2018 ◽  
Vol 13 (10) ◽  
pp. 1468-1472
Author(s):  
Tao Liu ◽  
Yong-Jian Wang ◽  
Yu-Fei Zhao
Keyword(s):  
Channel Estimation ◽  
Compressed Sensing ◽  
Orthogonal Frequency Division Multiplexing ◽  
Low Voltage ◽  
Matching Pursuit ◽  
Estimation Method ◽  
Power Line ◽  
Power Line Communication ◽  
Ofdm Systems ◽  
Channel Information

Broadband low-voltage power line communication (PLC) has many advantages including less investment cost, construction speed, and convenient access. Since the orthogonal frequency division multiplexing (OFDM) technology has strong anti-jamming and anti-frequency selective fading characteristics naturally it becomes a better low voltage power line communication solution. We proposed an OFDM channel estimation method based on compressed sensing (CS) technique according to the channel characteristics of low-voltage power lines. CS algorithm in OFDM system was discussed and an orthogonal matching pursuit (OMP) algorithm was applied to reconstruct the PLC channel information. The simulation results showed that the communication channel estimation method based on CS technique was feasible in PLC system, and the validity of information transmission in OFDM systems can be enhanced.

scholarly journals Low-Complexity Channel Estimation in 5G Massive MIMO-OFDM Systems

Symmetry ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 713 ◽  
Author(s):  
Omar A. Saraereh ◽  
Imran Khan ◽  
Qais Alsafasfeh ◽  
Salem Alemaishat ◽  
Sunghwan Kim
Keyword(s):  
Channel Estimation ◽  
Compressed Sensing ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Matching Pursuit ◽  
Low Complexity ◽  
Mimo Channel ◽  
Ofdm Systems ◽  
Mimo Channels ◽  
Low Snr

Pilot contamination is the reuse of pilot signals, which is a bottleneck in massive multi-input multi-output (MIMO) systems as it varies directly with the numerous antennas, which are utilized by massive MIMO. This adversely impacts the channel state information (CSI) due to too large pilot overhead outdated feedback CSI. To solve this problem, a compressed sensing scheme is used. The existing algorithms based on compressed sensing require that the channel sparsity should be known, which in the real channel environment is not the case. To deal with the unknown channel sparsity of the massive MIMO channel, this paper proposes a structured sparse adaptive coding sampling matching pursuit (SSA-CoSaMP) algorithm that utilizes the space–time common sparsity specific to massive MIMO channels and improves the CoSaMP algorithm from the perspective of dynamic sparsity adaptive and structural sparsity aspects. It has a unique feature of threshold-based iteration control, which in turn depends on the SNR level. This approach enables us to determine the sparsity in an indirect manner. The proposed algorithm not only optimizes the channel estimation performance but also reduces the pilot overhead, which saves the spectrum and energy resources. Simulation results show that the proposed algorithm has improved channel performance compared with the existing algorithm, in both low SNR and low pilot overhead.

Stage-Determined Matching Pursuit for Sparse Channel Estimation in OFDM Systems

2019 ◽  
Vol 13 (3) ◽  
pp. 2240-2251 ◽  
Author(s):  
Anthony Ngozichukwuka Uwaechia ◽  
Nor Muzlifah Mahyuddin
Keyword(s):  
Channel Estimation ◽  
Matching Pursuit ◽  
Ofdm Systems ◽  
Sparse Channel Estimation ◽  
Sparse Channel

scholarly journals Sliding-MOMP Based Channel Estimation Scheme for ISDB-T Systems

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Ziji Ma ◽  
Shuaifeng Guo ◽  
Hongli Liu ◽  
Minoru Okada
Keyword(s):  
Channel Estimation ◽  
Matching Pursuit ◽  
Computational Cost ◽  
Fast Time ◽  
Ofdm Systems ◽  
Sliding Windows ◽  
Practical Applications ◽  
Sampling Window ◽  
Estimation Scheme ◽  
Digital Broadcasting

Compressive sensing based channel estimation has shown its advantage of accurate reconstruction for sparse signal with less pilots for OFDM systems. However, high computational cost requirement of CS method, due to linear programming, significantly restricts its implementation in practical applications. In this paper, we propose a reduced complexity channel estimation scheme of modified orthogonal matching pursuit with sliding windows for ISDB-T (Integrated Services Digital Broadcasting for Terrestrial) system. The proposed scheme can reduce the computational cost by limiting the searching region as well as making effective use of the last estimation result. In addition, adaptive tracking strategy with sliding sampling window can improve the robustness of CS based methods to guarantee its accuracy of channel matrix reconstruction, even for fast time-variant channels. The computer simulation demonstrates its impact on improving bit error rate and computational complexity for ISDB-T system.

Channel Estimation and Symbol Detection with ICI Cancellation Based on Superimposed Training for OFDM Systems

2012 ◽  
Vol E95.B (9) ◽  
pp. 2926-2930
Author(s):  
Qinjuan ZHANG ◽  
Muqing WU ◽  
Qilin GUO ◽  
Rui ZHANG ◽  
Chao Yi ZHANG
Keyword(s):  
Channel Estimation ◽  
Ofdm Systems ◽  
Superimposed Training ◽  
Symbol Detection ◽  
Ici Cancellation
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