scholarly journals Precise Channel Estimation Approach for a mmWave MIMO System

2020 ◽  
Vol 10 (12) ◽  
pp. 4397 ◽  
Author(s):  
Prateek Saurabh Srivastav ◽  
Lan Chen ◽  
Arfan Haider Wahla
Keyword(s):  
Channel Estimation ◽  
Mean Squared Error ◽  
Mimo Systems ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Low Rank ◽  
High Signal ◽  
Formidable Challenge ◽  
Input Multiple Output ◽  
Efficient Recovery

Channel estimation is a formidable challenge in mmWave Multiple Input Multiple Output (MIMO) systems due to the large number of antennas. Therefore, compressed sensing (CS) techniques are used to exploit channel sparsity at mmWave frequencies to calculate fewer dominant paths in mmWave channels. However, conventional CS techniques require a higher training overhead for efficient recovery. In this paper, an efficient extended alternation direction method of multipliers (Ex-ADMM) is proposed for mmWave channel estimation. In the proposed scheme, a joint optimization problem is formulated to exploit low rank and channel sparsity individually in the antenna domain. Moreover, a relaxation factor is introduced which improves the proposed algorithm’s convergence. Simulation experiments illustrate that the proposed algorithm converges at lower Normalized Mean Squared Error (NMSE) with improved spectral efficiency. The proposed algorithm also ameliorates NMSE performance at low, mid and high Signal to Noise (SNR) ranges.

scholarly journals Compressive Sensing Based Channel Estimation for High-order MIMO Systems

2018 ◽  
Vol 14 (07) ◽  
pp. 30
Author(s):  
Zhiguo Lv ◽  
Ying Li
Keyword(s):  
Channel Estimation ◽  
Compressive Sensing ◽  
Narrow Band ◽  
Mimo Systems ◽  
Mimo System ◽  
Estimation Error ◽  
Multiple Input Multiple Output ◽  
High Order ◽  
Error Performance ◽  
Input Multiple Output

The high-order multiple-input multiple-output (MIMO) system can remarkably increase the data rate or enhance the reliability. However, it is difficult to perform channel estimation because of the massive number of antennas. The Narrow Band Estimation Antenna Processing (NBEAP) scheme is used to deal with this issue. Nevertheless, the accuracy of the channel estimation needs to be improved. In this paper, a compressive sensing based scheme named Narrow Band Estimation Fixed Antenna Processing (NBEFAP) is proposed to estimate the channel state information (CSI) for high-order MIMO systems. A simple pilot structure is designed to decrease the computation complexity. In addition, the pilot length is adjusted according to the time-varying sparsity level of the CSI. Compared with NBEAP scheme, NBEFAP scheme can improve the estimation error performance. Simulation results verify the effectiveness of the NBEFAP scheme.

scholarly journals Location-Aided Uplink Transmission for User-Centric Cell-Free Massive MIMO Systems: A Fairness Priority Perspective

2022 ◽  
Author(s):  
Chen Wei ◽  
Kui Xu ◽  
Zhexian Shen ◽  
Xiaochen Xia ◽  
Wei Xie ◽  
...  
Keyword(s):  
Large Scale ◽  
Mean Squared Error ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Access Point ◽  
Estimation Accuracy ◽  
Minimum Mean Squared Error ◽  
Input Multiple Output ◽  
User Centric ◽  
Assignment Scheme

Abstract In this paper, we investigate the uplink transmission for user-centric cell-free massive multiple-input multiple-output (MIMO) systems. The largest-large-scale-fading-based access point (AP) selection method is adopted to achieve a user-centric operation. Under this user-centric framework, we propose a novel inter-cluster interference-based (IC-IB) pilot assignment scheme to alleviate pilot contamination. Considering the local characteristics of channel estimates and statistics, we propose a location-aided distributed uplink combining scheme based on a novel proposed metric representing inter-user interference to balance the relationship among the spectral efficiency (SE), user equipment (UE) fairness and complexity, in which the normalized local partial minimum mean-squared error (LP-MMSE) combining is adopted for some APs, while the normalized maximum ratio (MR) combining is adopted for the remaining APs. A new closed-form SE expression using the normalized MR combining is derived and a novel metric to indicate the UE fairness is also proposed. Moreover, the max-min fairness (MMF) power control algorithm is utilized to further ensure uniformly good service to the UEs. Simulation results demonstrate that the channel estimation accuracy of our proposed IC-IB pilot assignment scheme outperforms that of the conventional pilot assignment schemes. Furthermore, although the proposed location-aided uplink combining scheme is not always the best in terms of the per-UE SE, it can provide the more fairness among UEs and can achieve a good trade-off between the average SE and computational complexity.

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.

scholarly journals Performance Analysis of Rate Splitting in Massive MIMO Systems with Low Resolution ADCs/DACs

2021 ◽  
Vol 11 (20) ◽  
pp. 9409
Author(s):  
Roger Kwao Ahiadormey ◽  
Kwonhue Choi
Keyword(s):  
Mimo Systems ◽  
Mimo System ◽  
Signal To Noise Ratio ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Quantization Noise ◽  
High Signal ◽  
Low Resolution ◽  
Rate Splitting ◽  
Noise Ratio

In this paper, we propose rate-splitting (RS) multiple access to mitigate the effects of quantization noise (QN) inherent in low-resolution analog-to-digital converters (ADCs) and digital-to-analog converters (DACs). We consider the downlink (DL) of a multiuser massive multiple-input multiple-output (MIMO) system where the base station (BS) is equipped with low-resolution ADCs/DACs. The BS employs the RS scheme for data transmission. Under imperfect channel state information (CSI), we characterize the spectral efficiency (SE) and energy efficiency (EE) by deriving the asymptotic signal-to-interference-and-noise ratio (SINR). For 1-bit resolution, the QN is very high, and the RS scheme shows no rate gain over the non-RS scheme. As the ADC/DAC resolution increases (i.e., 2–3 bits), the RS scheme achieves higher SE in the high signal-to-noise ratio (SNR) regime compared to that of the non-RS scheme. For a 3-bit resolution, the number of antennas can be reduced by 27% in the RS scheme to achieve the same SE as the non-RS scheme. Low-resolution DACs degrades the system performance more than low-resolution ADCs. Hence, it is preferable to equip the system with low-resolution ADCs than low-resolution DACs. The system achieves the best SE/EE tradeoff for 4-bit resolution ADCs/DACs.

Precoding for Multiuser MIMO

2012 ◽  
pp. 130-156 ◽  
Author(s):  
Elsadig Saeid ◽  
Varun Jeoti ◽  
Brahim Belhaouari Samir
Keyword(s):  
Mimo Systems ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Achievable Rate ◽  
Multiple Access Channels ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Single User ◽  
A New Technique ◽  
Improved Technique

Future Wireless Networks are expected to adopt multi-user multiple input multiple output (MU-MIMO) systems whose performance is maximized by making use of precoding at the transmitter. This chapter describes the recent advances in precoding design for MU-MIMO and introduces a new technique to improve the precoder performance. Without claiming to be comprehensive, the chapter gives deep introduction on basic MIMO techniques covering the basics of single user multiple input multiple output (SU-MIMO) links, its capacity, various transmission strategies, SU-MIMO link precoding, and MIMO receiver structures. After the introduction, MU-MIMO system model is defined and maximum achievable rate regions for both MU-MIMO broadcast and MU-MIMO multiple access channels are explained. It is followed by critical literature review on linear precoding design for MU-MIMO broadcast channel. This paves the way for introducing an improved technique of precoding design that is followed by its performance evaluation.

scholarly journals Adaptive Threshold-Aided K-Best Sphere Decoding for Large MIMO Systems

2019 ◽  
Vol 9 (21) ◽  
pp. 4624
Author(s):  
Uzokboy Ummatov ◽  
Kyungchun Lee
Keyword(s):  
Mimo Systems ◽  
Signal To Noise Ratio ◽  
Multiple Input Multiple Output ◽  
Threshold Value ◽  
Adaptive Threshold ◽  
Sphere Decoding ◽  
High Signal ◽  
Signal To Noise ◽  
Multiple Input ◽  
Input Multiple Output

This paper proposes an adaptive threshold-aided K-best sphere decoding (AKSD) algorithm for large multiple-input multiple-output systems. In the proposed scheme, to reduce the average number of visited nodes compared to the conventional K-best sphere decoding (KSD), the threshold for retaining the nodes is adaptively determined at each layer of the tree. Specifically, we calculate the adaptive threshold based on the signal-to-noise ratio and index of the layer. The ratio between the first and second smallest accumulated path metrics at each layer is also exploited to determine the threshold value. In each layer, in addition to the K paths associated with the smallest path metrics, we also retain the paths whose path metrics are within the threshold from the Kth smallest path metric. The simulation results show that the proposed AKSD provides nearly the same bit error rate performance as the conventional KSD scheme while achieving a significant reduction in the average number of visited nodes, especially at high signal-to-noise ratios.

scholarly journals On the Performance of Efficient Channel Estimation Strategies for Hybrid Millimeter Wave MIMO System

Entropy ◽  
2020 ◽  
Vol 22 (10) ◽  
pp. 1121
Author(s):  
Prateek Saurabh Srivastav ◽  
Lan Chen ◽  
Arfan Haider Wahla
Keyword(s):  
Channel Estimation ◽  
Millimeter Wave ◽  
Optimization Problem ◽  
Mimo Systems ◽  
Mimo System ◽  
Low Rank ◽  
Potential Candidate ◽  
Alternating Direction ◽  
The Individual ◽  
Joint Channel

Millimeter wave (mmWave) relying upon the multiple output multiple input (MIMO) is a new potential candidate for fulfilling the huge emerging bandwidth requirements. Due to the short wavelength and the complicated hardware architecture of mmWave MIMO systems, the conventional estimation strategies based on the individual exploitation of sparsity or low rank properties are no longer efficient and hence more modern and advance estimation strategies are required to recapture the targeted channel matrix. Therefore, in this paper, we proposed a novel channel estimation strategy based on the symmetrical version of alternating direction methods of multipliers (S-ADMM), which exploits the sparsity and low rank property of channel altogether in a symmetrical manner. In S-ADMM, at each iteration, the Lagrange multipliers are updated twice which results symmetrical handling of all of the available variables in optimization problem. To validate the proposed algorithm, numerous computer simulations have been carried out which straightforwardly depicts that the S-ADMM performed well in terms of convergence as compared to other benchmark algorithms and also able to provide global optimal solutions for the strictly convex mmWave joint channel estimation optimization problem.

scholarly journals Statistical Beamforming for Massive MIMO Systems with Distinct Spatial Correlations

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6255
Author(s):  
Taehyoung Kim ◽  
Sangjoon Park
Keyword(s):  
Massive Mimo ◽  
Degrees Of Freedom ◽  
Mimo Systems ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
High Signal ◽  
Spatial Correlations ◽  
Channel Correlation ◽  
Low Correlation ◽  
Noise Ratio

In this paper, we propose a novel statistical beamforming (SBF) method called the partial-nulling-based SBF (PN-SBF) to serve a number of users that are undergoing distinct degrees of spatial channel correlations in massive multiple-input multiple-output (MIMO) systems. We consider a massive MIMO system with two user groups. The first group experiences a low spatial channel correlation, whereas the second group has a high spatial channel correlation, which can happen in massive MIMO systems that are based on fifth-generation networks. By analyzing the statistical signal-to-interference-plus-noise ratio, it can be observed that the statistical beamforming vector for the low-correlation group should be designed as the orthogonal complement for the space spanned by the aggregated channel covariance matrices of the high-correlation group. Meanwhile, the spatial degrees of freedom for the high-correlation group should be preserved without cancelling the interference to the low-correlation group. Accordingly, a group-common pre-beamforming matrix is applied to the low-correlation group to cancel the interference to the high-correlation group. In addition, to deal with the intra-group interference in each group, the post-beamforming vector for each group is designed in the manner of maximizing the signal-to-leakage-and-noise ratio, which yields additional performance improvements for the PN-SBF. The simulation results verify that the proposed PN-SBF outperforms the conventional SBF schemes in terms of the ergodic sum rate for the massive MIMO systems with distinct spatial correlations, without the rate ceiling effect in the high signal-to-noise ratio region unlike conventional SBF schemes.

scholarly journals Diversity and Multiplexing Technologies by 3D Beams in Polarized Massive MIMO Systems

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Xin Su ◽  
KyungHi Chang
Keyword(s):  
Mobile Communications ◽  
Mimo Systems ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Scale Up ◽  
Beam Width ◽  
System Architectures ◽  
Selection Scheme ◽  
Input Multiple Output ◽  
3D Beamforming

Massive multiple input, multiple output (M-MIMO) technologies have been proposed to scale up data rates reaching gigabits per second in the forthcoming 5G mobile communications systems. However, one of crucial constraints is a dimension in space to implement the M-MIMO. To cope with the space constraint and to utilize more flexibility in 3D beamforming (3D-BF), we propose antenna polarization in M-MIMO systems. In this paper, we design a polarized M-MIMO (PM-MIMO) system associated with 3D-BF applications, where the system architectures for diversity and multiplexing technologies achieved by polarized 3D beams are provided. Different from the conventional 3D-BF achieved by planar M-MIMO technology to control the downtilted beam in a vertical domain, the proposed PM-MIMO realizes 3D-BF via the linear combination of polarized beams. In addition, an effective array selection scheme is proposed to optimize the beam-width and to enhance system performance by the exploration of diversity and multiplexing gains; and a blind channel estimation (BCE) approach is also proposed to avoid pilot contamination in PM-MIMO. Based on the Long Term Evolution-Advanced (LTE-A) specification, the simulation results finally confirm the validity of our proposals.

scholarly journals Neural NetworkL1Adaptive Control of MIMO Systems with Nonlinear Uncertainty

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Hong-tao Zhen ◽  
Xiao-hui Qi ◽  
Jie Li ◽  
Qing-min Tian
Keyword(s):  
Mimo Systems ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Adaptive Controller ◽  
Rbf Neural Networks ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Input Multiple Output ◽  
Low Pass ◽  
Nonlinear Uncertainties

An indirect adaptive controller is developed for a class of multiple-input multiple-output (MIMO) nonlinear systems with unknown uncertainties. This control system is comprised of anL1adaptive controller and an auxiliary neural network (NN) compensation controller. TheL1adaptive controller has guaranteed transient response in addition to stable tracking. In this architecture, a low-pass filter is adopted to guarantee fast adaptive rate without generating high-frequency oscillations in control signals. The auxiliary compensation controller is designed to approximate the unknown nonlinear functions by MIMO RBF neural networks to suppress the influence of uncertainties. NN weights are tuned on-line with no prior training and the project operator ensures the weights bounded. The global stability of the closed-system is derived based on the Lyapunov function. Numerical simulations of an MIMO system coupled with nonlinear uncertainties are used to illustrate the practical potential of our theoretical results.

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