Semi-Blind Receivers for Joint Symbol and Channel Estimation in Space-Time-Frequency MIMO-OFDM Systems

Liu, Kefei; Costa, João Paulo; So, Hing Cheung; Almeida, André L. F. de

doi:10.1109/tsp.2013.2278512

Cited by 55 publications

(36 citation statements)

References 34 publications

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“…Moreover, the number of antennas, UEs, and time slots is set to N BS = 64, K = 3, and M R = M T = 12, respectively, which may change in the form of variables in subsequent simulations, and we set the variable M P to represent the time slot for better presentation. As in [2,40], the signal-to-noise ratio (SNR) is defined as σ 2 s /σ 2 n , where σ 2 s is the signal power. I denotes the number of Monte Carlo runs, and the normalized mean squared error (NMSE) is defined as:…”

Section: Simulation Resultsmentioning

confidence: 99%

Low-Complexity Joint Channel Estimation for Multi-User mmWave Massive MIMO Systems

et al. 2020

Electronics

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For multi-user millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems, the precise acquisition of channel state information (CSI) is a huge challenge. With the increase of the number of antennas at the base station (BS), the traditional channel estimation techniques encounter the problems of pilot training overhead and computational complexity increasing dramatically. In this paper, we develop a step-length optimization-based joint iterative scheme for multi-user mmWave massive MIMO systems to improve channel estimation performance. The proposed estimation algorithm provides the BS with full knowledge of all channel parameters involved in up-and down-links. Compared with existing algorithms, the proposed algorithm has higher channel estimation accuracy with low complexity. Moreover, the proposed scheme performs well even with a small number of training sequences and a large number of users. Simulation results are shown to demonstrate the performance of the proposed channel estimation algorithm.

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Section: Simulation Resultsmentioning

confidence: 99%

Low-Complexity Joint Channel Estimation for Multi-User mmWave Massive MIMO Systems

et al. 2020

Electronics

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“…On-going work aims at taking non-perfect synchronization also into account. Further extensions to this work will include channels of strong frequency-(not satisfying (2)) and time-(e.g., [3], [13], [39]) selectivity, as well as richer configurations involving precoders and space-time/frequency coding (e.g., [34]).…”

Section: Discussionmentioning

confidence: 99%

Joint channel estimation / data detection in MIMO-FBMC/OQAM systems — A tensor-based approach

Kofidis

Chatzichristos

Almeida

2017

2017 25th European Signal Processing Conference (EUSIPCO)

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Abstract-Filter bank-based multicarrier (FBMC) systems are currently being considered as a prevalent candidate for replacing the long established cyclic prefix (CP)-based orthogonal frequency division multiplexing (CP-OFDM) in the physical layer of next generation communications systems. In particular, FBMC/OQAM has received increasing attention due to, among other features, its potential for maximum spectral efficiency. It suffers, however, from an intrinsic self-interference effect, which complicates signal processing tasks at the receiver, including synchronization, channel estimation and equalization. In a multiple-input multiple-output (MIMO) configuration, the multi-antenna interference has also to be taken into account. (Semi-)blind FBMC/OQAM receivers have been little studied so far and mainly for single-antenna systems. The problem of joint channel estimation and data detection in a MIMO-FBMC/OQAM system, given limited or no training information, is studied in this paper through a tensor-based approach in the light of the success of such techniques in OFDM applications. Simulationbased comparisons with CP-OFDM are included, for realistic transmission models.

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“…A parallel factor (PARAFAC) [7] based receiver is proposed in [8] by using the Khatri-Rao space-time (KRST) coding scheme, which can achieve a flexible tradeoff between error performance and transmission efficiency. In [9], the authors extend the KRST coding scheme by using the linear constellation precoding, and then developing several semi-blind receivers. These semi-blind receivers allow a joint symbol and channel estimation without requiring pilot sequences for the instantaneous channel state information (CSI) acquisition.…”

Section: Introductionmentioning

confidence: 99%

A Robust Semi-Blind Receiver for Joint Symbol and Channel Parameter Estimation in Multiple-Antenna Systems

Han

Yan

et al. 2019

Electronics

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For multiple-antenna systems, the technologies of joint symbol and channel parameter estimation have been developed in recent works. However, existing technologies have a number of problems, such as performance degradation and the large cost of prior information. In this paper, a tensor space-time coding scheme in multiple-antenna systems was considered. This scheme allowed spreading, multiplexing, and allocating information symbols associated with multiple transmitted data streams. We showed that the received signal was formulated as a third-order tensor satisfying a Tucker-2 model, and then a robust semi-blind receiver was developed based on the optimized Levenberg–Marquardt (LM) algorithm. Under the assumption that the instantaneous channel state information (CSI) is unknown at the receiving end, the proposed semi-blind receiver jointly estimates the information symbol and channel parameters efficiently. The proposed receiver had a better estimation performance compared with existing semi-blind receivers, and still performed well when the channel became strongly correlated. Moreover, the proposed semi-blind receiver could be extended to the multi-user massive multiple-input multiple-output (MIMO) system for joint symbol and channel estimation. Computer simulation results were shown to demonstrate the effectiveness of the proposed receiver.

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Semi-Blind Receivers for Joint Symbol and Channel Estimation in Space-Time-Frequency MIMO-OFDM Systems

Cited by 55 publications

References 34 publications

Low-Complexity Joint Channel Estimation for Multi-User mmWave Massive MIMO Systems

Low-Complexity Joint Channel Estimation for Multi-User mmWave Massive MIMO Systems

Joint channel estimation / data detection in MIMO-FBMC/OQAM systems — A tensor-based approach

A Robust Semi-Blind Receiver for Joint Symbol and Channel Parameter Estimation in Multiple-Antenna Systems

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