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Multi-user MIMO

About: Multi-user MIMO is a research topic. Over the lifetime, 10265 publications have been published within this topic receiving 227206 citations. The topic is also known as: multi user mimo & MU-MIMO.


Papers
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Proceedings ArticleDOI
10 Jun 2012
TL;DR: An energy-efficient proportional-fair scheduling is proposed for downlink multi-user MIMO systems and the optimal power allocation maximizing the performance measure is identified.
Abstract: Multi-user MIMO is the enabling technology for LTE-Advanced systems to meet IMT-Advanced targets. The gain of multi-user MIMO is achieved partially through advanced user-grouping, user-scheduling, and precoding. Traditionally, multiuser MIMO scheduling focuses solely on spectral-efficiency [1]. That is, the scheduler will strike to balance the cell-edge user spectral-efficiency as well as the cell-average spectral-efficiency. Similar to spectral-efficiency, energy-efficiency is becoming increasingly important for wireless communications. The energy efficiency is measured by a classical measure, “throughput per Joule”, while both RF transmit power and device electronic circuit power consumptions are considered. In this paper, an energy-efficient proportional-fair scheduling is proposed for downlink multi-user MIMO systems. To specific, the scheduling algorithm is proposed to balance cell-edge energy-efficiency and the cell-average energy-efficiency. The energy-efficient proportional-fair metric is defined and the optimal power allocation maximizing the performance measure is identified. System level evaluation suggests that multi-user MIMO could improve the energy-efficiency of a wireless communication system significantly.

36 citations

Proceedings ArticleDOI
20 Oct 2014
TL;DR: This paper investigates the performance of the massive MU-MIMO downlink system in a single cell where the base station utilizes linear precoding schemes to serve many users over the Rayleigh fading channel.
Abstract: Nowadays, Multi-user Multiple-In Multiple-Out (MU-MIMO) systems are used in new generation wireless technologies. Due to ongoing improvement in wireless technology, the numbers of users and applications increase rapidly. At the same time, wireless communication need the high data rate and link reliability. Therefore, MU-MIMO improvements have to consider 1) providing the high data rate and link reliability, 2) support all users in the same and frequency resource, and 3) using low power consumption. In practice, inter-user interference has a strong impact when more users access the wireless link. Complicated transmission techniques such as interference cancellation are used to maintain a given desired quality of service. Due to these problems, MU-MIMO systems with very large antenna arrays (known as massive MIMO) are proposed. With massive MU-MIMO systems, we mean a hundred or more serving tens of users. The channel vectors are nearly orthogonal, and the inter-user interference is reduced significantly. Therefore, the users can be served with high data rate simultaneously. In this paper, we investigate the performance of the massive MU-MIMO downlink system in a single cell where the base station utilizes linear precoding schemes to serve many users over the Rayleigh fading channel.

36 citations

Journal ArticleDOI
TL;DR: This paper proposes an efficient joint beam selection and precoding design algorithm based on the innovative penalty dual decomposition method that can converge in a few iterations and achieve near-optimal performance when compared to the fully digital precoding scheme, thus enabling them to outperform the competing methods.
Abstract: Wireless transmission relying on lens antenna arrays is becoming more and more attractive for millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems using a limited number of radio frequency chains due to the lens’ energy-focusing capability. In this paper, we consider the joint design of the beam selection and precoding matrices in order to maximize the sum-rate of a downlink single-sided lens MU-MIMO mmWave system under transmit power constraints. We first formulate the optimization problem into a tractable form using the popular weighted minimum mean squared error (WMMSE) approach. To solve this problem, we then propose an efficient joint beam selection and precoding design algorithm based on the innovative penalty dual decomposition method. To reduce the design complexity, we also propose a simplified algorithm by combining the interference-aware beam selection scheme with the WMMSE approach. Simulation results demonstrate that our proposed algorithms can converge in a few iterations and achieve near-optimal performance when compared to the fully digital precoding scheme, thus enabling them to outperform the competing methods.

36 citations

Journal ArticleDOI
TL;DR: This work proposes a robust leakage-based transmit beamforming design for multi-user MIMO systems by introducing a probabilistic constraint that optimizes the average signal-to-interference-plus-noise ratio (SINR) performance implicitly and achieves good bit-error-rate and reliability of SINR levels as well as robustness against channel uncertainties.
Abstract: Multi-user multiple-input and multiple-output (MU-MIMO) wireless systems have the potential to increase system capacity significantly by separating multiple users in the space domain through appropriate signal processing. These techniques require accurate channel state information at transmitter (CSIT) for their proper operations. With inevitable channel imperfections in practice, robustness has become an important issue in the development of beamforming techniques. In this work, we propose a robust leakage-based transmit beamforming design for multi-user MIMO systems by introducing a probabilistic constraint. In a multi-user system, the main challenge for transmit beamforming is to suppress the co-channel interference (CCI) from other users. Our approach optimizes the average signal-to-interference-plus-noise ratio (SINR) performance implicitly by maximizing the average signal power subject to probabilistic leakage and noise power constraint. Moreover, both the single-stream-per-user and multiple-stream-per-user cases are considered.In the latter case, a hybrid scheme is suggested by incorporating Alamouti code into the proposed design. Simulation results show that under proper control of the probabilistic constraint, both beamformers achieve good bit-error-rate (BER) performances, reliability of SINR levels as well as robustness against channel uncertainties.

36 citations

Proceedings ArticleDOI
02 Jul 2006
TL;DR: This work addresses the joint optimization of transmitter and receivers for a multi-user multiple-input multiple-output (MIMO) broadcast channel (BC) system under the assumption of perfect channel state information (CSI) at both transmitters and receivers with an iterative solution.
Abstract: We address the joint optimization of transmitter and receivers for a multi-user multiple-input multiple-output (MIMO) broadcast channel (BC) system under the assumption of perfect channel state information (CSI) at both transmitter and receivers. Tomlinson Harashima precoding (THP) is employed for interuser interference presubtraction and the mean square error (MSE) is minimized. Since the downlink problem is difficult to handle, we formulate an equivalent uplink problem by exploiting the duality between THP and decision feedback equalization (DFE). We present an iterative solution, which delivers suboptimum transmit and receive matrices as well as a suboptimum precoding order. The performance of the algorithm is studied theoretically and experimentally

36 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202363
2022122
2021170
2020211
2019234
2018263