scholarly journals Joint Channel Tracking and Data Detection for Massive MIMO Uplink Over Time-Varying Channel

2021 ◽  
Author(s):  
Yuya Akiba ◽  
Shinya Sugiura
Keyword(s):  
Multiple Input Multiple Output ◽  
Data Detection ◽  
Time Varying ◽  
Data Frame ◽  
Detection Scheme ◽  
Channel Tracking ◽  
Continuous Output ◽  
Input Multiple Output ◽  
Time Varying Channel ◽  
Joint Channel

In this letter, we propose a novel joint channel estimation and data detection scheme for massive multiple-input multiple-output (MIMO) uplink, which operates in a time-varying fading channel. More specifically, at the receiver of the proposed scheme, a data frame is divided into multiple blocks, and in each block, a demodulated data block is used for updating channel state information (CSI) in an iterative manner. Furthermore, the initial CSI in the block of interest is given by the estimated CSI in the previous block, hence allowing accurate tracking of CSI in a time-varying channel without imposing additional pilot insertion inside the data frame. Since the length of the divided blocks affects both the achievable channel tracking and data detection performances, it is optimized so as to maximize the discrete-input continuous-output memoryless channel's (DCMC) capacity derived in this letter. It is demonstrated that the DCMC capacity of the proposed scheme is capable of nearly achieving those of the perfect CSI counterpart without imposing any substantial pilot overhead.

scholarly journals Joint Channel Tracking and Data Detection for Massive MIMO Uplink Over Time-Varying Channel

2021 ◽  
Author(s):  
Yuya Akiba ◽  
Shinya Sugiura
Keyword(s):  
Multiple Input Multiple Output ◽  
Data Detection ◽  
Time Varying ◽  
Data Frame ◽  
Detection Scheme ◽  
Channel Tracking ◽  
Continuous Output ◽  
Input Multiple Output ◽  
Time Varying Channel ◽  
Joint Channel

In this letter, we propose a novel joint channel estimation and data detection scheme for massive multiple-input multiple-output (MIMO) uplink, which operates in a time-varying fading channel. More specifically, at the receiver of the proposed scheme, a data frame is divided into multiple blocks, and in each block, a demodulated data block is used for updating channel state information (CSI) in an iterative manner. Furthermore, the initial CSI in the block of interest is given by the estimated CSI in the previous block, hence allowing accurate tracking of CSI in a time-varying channel without imposing additional pilot insertion inside the data frame. Since the length of the divided blocks affects both the achievable channel tracking and data detection performances, it is optimized so as to maximize the discrete-input continuous-output memoryless channel's (DCMC) capacity derived in this letter. It is demonstrated that the DCMC capacity of the proposed scheme is capable of nearly achieving those of the perfect CSI counterpart without imposing any substantial pilot overhead.

scholarly journals The Downlink Performance for Cell-Free Massive MIMO with Instantaneous CSI in Slowly Time-Varying Channels

Entropy ◽  
2021 ◽  
Vol 23 (11) ◽  
pp. 1552
Author(s):  
Tongzhou Han ◽  
Danfeng Zhao
Keyword(s):  
Power Control ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Time Varying ◽  
Input Multiple Output ◽  
Efficiency Performance ◽  
A Cell ◽  
Time Varying Channel

In centralized massive multiple-input multiple-output (MIMO) systems, the channel hardening phenomenon can occur, in which the channel behaves as almost fully deterministic as the number of antennas increases. Nevertheless, in a cell-free massive MIMO system, the channel is less deterministic. In this paper, we propose using instantaneous channel state information (CSI) instead of statistical CSI to obtain the power control coefficient in cell-free massive MIMO. Access points (APs) and user equipment (UE) have sufficient time to obtain instantaneous CSI in a slowly time-varying channel environment. We derive the achievable downlink rate under instantaneous CSI for frequency division duplex (FDD) cell-free massive MIMO systems and apply the results to the power control coefficients. For FDD systems, quantized channel coefficients are proposed to reduce feedback overhead. The simulation results show that the spectral efficiency performance when using instantaneous CSI is approximately three times higher than that achieved using statistical CSI.

Joint Channel Estimation and Data Detection for STBC MIMO-OFDM Wireless Communication System

2015 ◽  
Vol 24 (04) ◽  
pp. 1550059 ◽  
Author(s):  
Gajanan R. Patil ◽  
Vishwanath K. Kokate
Keyword(s):  
Channel Estimation ◽  
Orthogonal Frequency Division Multiplexing ◽  
Multiple Input Multiple Output ◽  
Data Detection ◽  
Channel Estimate ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Mimo Ofdm ◽  
The Cost ◽  
Joint Channel

This paper presents a joint channel estimation and data detection technique for multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) system. Initial estimate of the channel is obtained using semi-blind channel estimation (SBCE). The whitening rotation (WR)-based orthogonal pilot maximum likelihood (OPML) method is used to obtain the channel estimate. The estimate is further enhanced by extracting information through the received data symbols. The performance of the proposed estimator is studied under various channel models. The simulation study shows that this approach gives better performance over training-based channel estimation (TBCE) and OPML SBCE methods but at the cost of higher computational complexity.

Depth-First QRD-M Detection Algorithm for MIMO Systems

2013 ◽  
Vol 347-350 ◽  
pp. 3478-3481
Author(s):  
Li Liu ◽  
Jin Kuan Wang ◽  
Xin Song ◽  
Yin Hua Han ◽  
Yu Huan Wang
Keyword(s):  
Ordered Set ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Detection Algorithm ◽  
Qr Decomposition ◽  
Detection Performance ◽  
Detection Scheme ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Ml Detection

Maximum likelihood (ML) detection algorithm for multiple input multiple output (MIMO) systems provided the best bit error rate (BER) performance with heavy calculating complexity. The use of QR decomposition with M-algorithm (QRD-M) had been proposed to provide near-ML detection performance and lower calculating complexity. However, its complexity still grew exponentially with increasing dimension of the transmitted signal. To reduce the problem, an improved detection scheme was proposed here. After constructing the tree detecting model of MIMO systems, the ML search of one layer was done, the branch metrics were calculated and sorted, which gave an ordered set of the layer, then depth-first search were used to search the left layers with termination methods. The proposed algorithm provides near QRD-M detection performance.

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