scholarly journals On Matrix Completion-Based Channel Estimators for Massive MIMO Systems

Symmetry ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 1377
Author(s):  
Mingjun Ding ◽  
Xiaodong Yang ◽  
Rui Hu ◽  
Zhitao Xiao ◽  
Jun Tong ◽  
...  
Keyword(s):  
Computational Complexity ◽  
Massive Mimo ◽  
Communication Systems ◽  
Large Scale ◽  
Hybrid Methods ◽  
Mimo Systems ◽  
Low Cost ◽  
Matrix Completion ◽  
Spectrum Efficiency ◽  
Robust Solution

Large-scale symmetric arrays such as uniform linear arrays (ULA) have been widely used in wireless communications for improving spectrum efficiency and reliability. Channel state information (CSI) is critical for optimizing massive multiple-input multiple-output(MIMO)-based wireless communication systems. The acquisition of CSI for massive MIMO faces challenges such as training shortage and high computational complexity. For millimeter wave MIMO systems, the low-rankness of the channel can be utilized to address the challenge of training shortage. In this paper, we compared several channel estimation schemes based on matrix completion (MC) for symmetrical arrays. Performance and computational complexity are discussed and compared. By comparing the performance in different scenarios, we concluded that the generalized conditional gradient with alternating minimization (GCG-Alt) estimator provided a low-cost, robust solution, while the alternating direction method of multipliers (ADMM)-based hybrid methods achieved the best performance when the array response was perfectly known.

scholarly journals An Efficient Precoding Scheme for Millimeter-Wave Massive MIMO Systems

Electronics ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 927 ◽  
Author(s):  
Alemaishat ◽  
Saraereh ◽  
Khan ◽  
Affes ◽  
Li ◽  
...  
Keyword(s):  
Computational Complexity ◽  
Millimeter Wave ◽  
Massive Mimo ◽  
Communication Systems ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Beam Control ◽  
Low Computational Complexity ◽  
Multiple Input ◽  
Input Multiple Output

Aiming at the problem of high computational complexity due to a large number of antennas deployed in mmWave massive multiple-input multiple-output (MIMO) communication systems, this paper proposes an efficient algorithm for optimizing beam control vectors with low computational complexity based on codebooks for millimeter-wave massive MIMO systems with split sub-arrays hybrid beamforming architecture. A bidirectional method is adopted on the beam control vector of each antenna sub-array both at the transmitter and receiver, which utilizes the idea of interference alignment (IA) and alternating optimization. The simulation results show that the proposed algorithm has low computational complexity, fast convergence, and improved spectral efficiency as compared with the state-of-the-art algorithms.

scholarly journals BER and Spectrum Efficiency Analysis of Massive MIMO Systems for IoT Application

2019 ◽  
Vol 8 (4) ◽  
pp. 10587-10591
Keyword(s):  
Channel Estimation ◽  
Massive Mimo ◽  
Large Scale ◽  
Mimo Systems ◽  
Efficiency Analysis ◽  
Spatial Multiplexing ◽  
Spectrum Efficiency ◽  
Estimation Technique ◽  
Information Request ◽  
Factual Data

The fifth era of portable correspondence frameworks (5G) guarantees uncommon degrees of availability and nature of administration (QoS) to fulfill the unremitting development in the quantity of versatile savvy gadgets and the colossal increment in information request. One of the essential ways 5G organize innovation will be practiced is through arrange densification, to be specific expanding the quantity of radio wires per site and sending littler and littler cells. Gigantic MIMO, where MIMO represents numerous info various yield, is generally expected to be a key empowering agent of 5G. This innovation use a forceful spatial multiplexing, from utilizing countless transmitting/accepting reception apparatuses, to duplicate the limit of a remote channel. Such an appropriated engineering gives extra large scale decent variety, and the co-handling at numerous APs completely smothers the between cell obstruction. Contingent upon moderate/quick channel blurring conditions, a few creators recommended versatile LMS, RLS and NLMS based channel estimators, which either require factual data of the channel or are not proficient enough as far as execution or calculations. So as to conquer the above impacts, the work centers around the QR-RLS based channel estimation technique for Massive MIMO frameworks with various regulation plan.

REDUCING THE COMPUTATIONAL COMPLEXITY OF SIGNAL DETECTION IN MIMO SYSTEMS

2021 ◽  
Author(s):  
М.Г. БАКУЛИН ◽  
Т.Б.К. БЕН РАЖЕБ ◽  
В.Б. КРЕЙНДЕЛИН ◽  
А.Э. СМИРНОВ
Keyword(s):  
Computational Complexity ◽  
Signal Detection ◽  
Massive Mimo ◽  
Communication Systems ◽  
Noise Immunity ◽  
Mimo Systems ◽  
Detection Algorithm ◽  
Wireless Communication Systems ◽  
Detection Algorithms ◽  
Mimo Technology

С развитием технологии MIMO и появлением технологии massive MIMO возросла сложность обработки сигнала на приемной стороне. Применение известных алгоритмов детектирования сигнала на приемной стороне становится трудно реализуемым из-за высокой вычислительной сложности. Предлагается новая реализация известного алгоритма МСКО, которая позволяет снизить вычислительную сложность детектирования без потерь в помехоустойчивости в системах беспроводной связи, использующих технологию massive MIMO. With the development of MIMO technology and the appearance of the massive MIMO technology, the computational complexity of signal processing on the receiving side has increased. The application of known signal detection algorithms used in MIMO systems becomes difficult or even impossible to implement in massive MIMO systems because of computational complexity. We offer a new realization technique of the well-known MMSE detection algorithm with less computational complexity and without any loss in noise immunity in wireless communication systems using massive MIMO technology.

User grouping and optimization-based pilot scheduling for mitigating the pilot contamination in massive multi cell MIMO systems

2020 ◽  
pp. 2050057
Author(s):  
Ambala Pradeep Kumar ◽  
Tadisetty Srinivasulu
Keyword(s):  
Massive Mimo ◽  
Communication Systems ◽  
Large Scale ◽  
Mimo Systems ◽  
Spider Monkey ◽  
Achievable Rate ◽  
Pilot Contamination ◽  
User Grouping ◽  
Spider Monkey Optimization ◽  
The Impact

Massive multiple-input multiple-output (massive MIMO) is a promising approach in wireless communication systems for providing improved link reliability and spectral efficiency and it helps several users. The main aim is to solve pilot contamination issue in massive MIMO systems; this research paper utilizes two approaches for reducing the contamination. This paper presents the user grouping approach based on sparse fuzzy C-means clustering (sparse FCM), which groups user parameters based on parameters such as large-scale fading factor, SINR, and user distance. Here, same pilot sequences are assigned to center users in which the impact of pilot contamination is limited, while the algorithm assigns orthogonal pilot sequences to the edge users that suffer severely from pilot contamination. Therefore, the proposed user grouping keeps away from the inappropriate grouping of users, enabling effective grouping even under the worst situations of the channel. Secondly, pilot scheduling is done based on elephant spider monkey optimization (ESMO), which is designed by integrating elephant herding optimization (EHO) into spider monkey optimization (SMO). The performance of pilot scheduling based on grouping-based ESMO is evaluated based on achievable rate and SINR. The proposed method achieves maximal achievable rate of 41.29[Formula: see text]bps/Hz and maximal SINR of 124.31[Formula: see text]dB.

scholarly journals Low Complexity Angular-Domain Detection for the Uplink of Multi-User mmWave Massive MIMO Systems

Electronics ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 795
Author(s):  
Xiaoxuan Xia ◽  
Wence Zhang ◽  
Yinkai Fu ◽  
Xu Bao ◽  
Jing Xia
Keyword(s):  
Energy Efficiency ◽  
Computational Complexity ◽  
Massive Mimo ◽  
Communication Systems ◽  
Mimo Systems ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Digital Processing ◽  
Low Complexity ◽  
Angular Domain

To compromise between the system performance and hardware cost, millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems have been regarded as an enabling technology for the fifth generation of mobile communication systems (5G). This paper considers a low-complexity angular-domain compressing based detection (ACD) for uplink multi-user mmWave massive MIMO systems, which involves hybrid analog and digital processing. In analog processing, we perform angular-domain compression on the received signal by exploiting the sparsity of the mmWave channel to reduce the dimension of the signal space. In digital processing, the proposed ACD scheme works well with zero forcing (ZF)/maximum ratio combining (MRC)/minimum mean square error (MMSE) detection schemes. The performance analysis of the proposed ACD scheme is provided in terms of achievable rates, energy efficiency and computational complexity. Simulations are carried out and it shows that compared with existing works, the proposed ACD scheme not only reduces the computational complexity by more than 50 % , but also improves the system’s achievable rates and energy efficiency.

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.

Новый критерий оптимальности пространственно-временных матриц

2020 ◽  
Author(s):  
A.A. Reznev ◽  
V.B. Kreyndelin
Keyword(s):  
Computational Complexity ◽  
Large Scale ◽  
Noise Immunity ◽  
Optimality Criterion ◽  
Mimo Systems ◽  
Optimality Criteria ◽  
Space Time ◽  
Space Time Codes ◽  
Golden Code ◽  
New Criterion

The application of optimality criteria for the study of space-time codes is considered. Known rank and determinant criteria are described. The computational complexity of determinant criteria is presented taking into account some estimation of the real CPUs specifications. An algorithm for calculating a new optimality criterion is described. The computational complexity of the new optimality criterion is evaluated. The new criterion is applied to the study of the space-time Golden matrix. The obtained criterion value is used to modify the Golden code. The modeling for Golden code demonstrates that criterion works and gives us better levels for noise immunity. The proposed optimality criterion is acceptable in terms of computational complexity even for a large number of antennas, which is typical for large-scale MIMO systems. Рассматривается применение критериев оптимальности для исследования пространственно-временных кодов.Описаны известные ранговый и детерминантный критерии. Для детерминантного критерия оценена вычислительная сложность с учетом определения специальных высокопроизводительных процессоров. Описан алгоритм расчета нового критерия оптимальности. Проведена оценка вычислительной сложности нового критерия оптимальности. Новый критерий применен для исследования пространственно-временной матрицы Голден. Полученное значение критерия использовано для модификациикода Голден. Продемонстрированы кривые помехоустойчивости для кода Голден и кода Голден с модифицированным параметром, получен энергетический выигрыш. Предложенный критерий оптимальности приемлем с точки зрения вычислительнойсложности даже при большом числе антенн, характерном для систем широкомасштабного MIMO.

scholarly journals Channel Estimation for Extremely Large-Scale Massive MIMO Systems

2020 ◽  
Vol 9 (5) ◽  
pp. 633-637 ◽  
Author(s):  
Yu Han ◽  
Shi Jin ◽  
Chao-Kai Wen ◽  
Xiaoli Ma
Keyword(s):  
Channel Estimation ◽  
Massive Mimo ◽  
Large Scale ◽  
Mimo Systems
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