scholarly journals Energy Efficiency Optimization for Massive MIMO Non-Orthogonal Unicast and Multicast Transmission with Statistical CSI

Electronics ◽  
2019 ◽  
Vol 8 (8) ◽  
pp. 857 ◽  
Author(s):  
Wang ◽  
Huang ◽  
You ◽  
Xiong ◽  
Li ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Power Allocation ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Maximization Problem ◽  
Multicast Transmission ◽  
Deterministic Equivalent ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Vector Valued

We study the energy efficiency (EE) optimization problem in non-orthogonal unicast and multicast transmission for massive multiple-input multiple-output (MIMO) systems with statistical channel state information of all receivers available at the transmitter. Firstly, we formulate the EE maximization problem. We reduce the number of variables to be solved and simplify this large-dimensional-matrix-valued problem into a real-vector-valued problem. Next, we lower the computational complexity significantly by replacing the objective with its deterministic equivalent to avoid the high-complex expectation operation. With guaranteed convergence, we propose an iterative algorithm on beam domain power allocation using the minorize maximize algorithm and Dinkelbach’s transform and derive the locally optimal power allocation strategy to achieve the optimal EE. Finally, we illustrate the significant EE performance gain of our EE maximization algorithm compared with the conventional approach through conducting numerical simulations.

A Comparison of Norm Based Antenna Selection and Random Antenna Selection with Regard to Energy Efficiency in Wireless System with Large Number of Users

2020 ◽  
Vol 10 (2) ◽  
pp. 189-196
Author(s):  
Ashu Taneja ◽  
Nitin Saluja
Keyword(s):  
Energy Efficiency ◽  
Mimo Systems ◽  
Antenna Selection ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Transmit Antenna Selection ◽  
Wireless System ◽  
Multiple Input ◽  
Input Multiple Output

Background: The paper considers the wireless system with large number of users (more than 50 users) and each user is assigned large number of antennas (around 200) at the Base Station (BS). Objective: The challenges associated with the defined system are increased power consumption and high complexity of associated circuitry. The antenna selection is introduced to combat these problems while the usage of linear precoding reduces computational complexity. The literature suggests number of antenna selection techniques based on statistical properties of signal. However, each antenna selection technique suits well to specific number of users. Methods: In this paper, the random antenna selection is compared with norm-based antenna selection. It is analysed that the random antenna selection leads to inefficient spectral efficiency if the number of users are more than 50 in Multi-User Multiple-Input Multiple Output (MU-MIMO) system. Results: The paper proposes the optimization of Energy-Efficiency (EE) with random transmit antenna selection for large number of users in MU-MIMO systems. Conclusion: Also the computation leads to optimization of number of transmit antennas at the BS for energy efficiency. The proposed algorithm results in improvement of the energy efficiency by 27% for more than 50 users.

scholarly journals Massive MIMO Techniques for 5G and Beyond—Opportunities and Challenges

Electronics ◽  
2021 ◽  
Vol 10 (14) ◽  
pp. 1667
Author(s):  
David Borges ◽  
Paulo Montezuma ◽  
Rui Dinis ◽  
Marko Beko
Keyword(s):  
Energy Efficiency ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Spatial Multiplexing ◽  
Existing Problems ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Mimo Transmission ◽  
Diversity Gains

Telecommunications have grown to be a pillar to a functional society and the urge for reliable and high throughput systems has become the main objective of researchers and engineers. State-of-the-art work considers massive Multiple-Input Multiple-Output (massive MIMO) as the key technology for 5G and beyond. Large spatial multiplexing and diversity gains are some of the major benefits together with an improved energy efficiency. Current works mostly assume the application of well-established techniques in a massive MIMO scenario, although there are still open challenges regarding hardware and computational complexities and energy efficiency. Fully digital, analog, and hybrid structures are analyzed and a multi-layer massive MIMO transmission technique is detailed. The purpose of this article is to describe the most acknowledged transmission techniques for massive MIMO systems and to analyze some of the most promising ones and identify existing problems and limitations.

PROBLEM STATEMENT OF JOINT ANTENNA SELECTION AND PRECODING IN MASSIVE MIMO COMMUNICATION SYSTEMS

2021 ◽  
Author(s):  
В.Б. КРЕЙНДЕЛИН ◽  
М.В. ГОЛУБЕВ
Keyword(s):  
Massive Mimo ◽  
Communication Systems ◽  
Mimo Systems ◽  
Antenna Selection ◽  
Multiple Input Multiple Output ◽  
Research Areas ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Legal Restrictions ◽  
Multiple Transmission

Совместный с прекодингом автовыбор антенн на приемной и передающей стороне - одно из перспективных направлений исследований для реализации технологий Multiple Transmission and Reception Points (Multi-TRP, множество точек передачи и приема) в системах со многими передающими и приемными антеннами Massive MIMO (Multiple-Input-Multiple-Output), которые активно развиваются в стандарте 5G. Проанализированы законодательные ограничения, влияющие на применимость технологий Massive MIMO, и специфика реализации разрабатываемого алгоритма в миллиметровомдиапа -зоне длин волн. Рассмотрены алгоритмы формирования матриц автовыбора антенн как на передающей, так и на приемной стороне. Сформулирована строгая математическая постановка задачи для двух критериев работы алгоритма: максимизация взаимной информации и минимизация среднеквадратичной ошибки. Joint precoding and antenna selection both on transmitter and receiver sides is one of the promising research areas for evolving toward the Multiple Transmission and Reception Points (Multi-TRP) concept in Massive MIMO systems. This technology is under active development in the coming 5G 3GPP releases. We analyze legal restrictions for the implementation of 5G Massive MIMO technologies in Russia and the specifics of the implementation of the developed algorithm in the millimeter wavelength range. Algorithms of antenna auto-selection matrices formation on both transmitting and receiving sides are considered. Two criteria are used for joint antenna selection and precoding: maximizing mutual information and minimizing mean square error.

scholarly journals Beam division multiple access for millimeter wave massive MIMO: Hybrid zero-forcing beamforming with user selection

2022 ◽  
Vol 12 (1) ◽  
pp. 445
Author(s):  
Hong Son Vu ◽  
Kien Truong ◽  
Minh Thuy Le
Keyword(s):  
Multiple Access ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Zero Forcing ◽  
Multiuser Interference ◽  
Novel Approach ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Promising Solution

<p>Massive multiple-input multiple-output (MIMO) systems are considered a promising solution to minimize multiuser interference (MUI) based on simple precoding techniques with a massive antenna array at a base station (BS). This paper presents a novel approach of beam division multiple access (BDMA) which BS transmit signals to multiusers at the same time via different beams based on hybrid beamforming and user-beam schedule. With the selection of users whose steering vectors are orthogonal to each other, interference between users is significantly improved. While, the efficiency spectrum of proposed scheme reaches to the performance of fully digital solutions, the multiuser interference is considerably reduced.</p>

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 An Evaluation of Successive Pilot Decontamination in Massive MIMO

2018 ◽  
Vol 39 (2) ◽  
pp. 107
Author(s):  
Victor Croisfelt Rodrigues ◽  
Taufik Abrão
Keyword(s):  
Spectral Efficiency ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Pilot Training ◽  
Pilot Contamination ◽  
Fundamental Issue ◽  
Data Rates ◽  
Multiple Input ◽  
Input Multiple Output

The demand for higher data rates can be satisfied by the spectral efficiency (SE) improvement offered by Massive multiple-input multiple-output (M-MIMO) systems. However, the pilot contamination remains as a fundamental issue to obtain the paramount SE in such systems. This propitiated the research of several methods to mitigate pilot contamination. One of these procedures is based on the coordination of the cells, culminating in proposals with multiple pilot training phases. This paper aims to expand the results of the original paper, whereby the concepts of large pilot training phases were offered. The evaluation of such method was conducted through more comprehensible numerical results, in which a large number of antennas were assumed and more rigorous SE expressions were used. The channel estimation approaches relying on multiple pilot training phases were considered cumbersome for implementation and an uninteresting solution to overcome pilot contamination; contradicting the results presented in the genuine paper.

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