scholarly journals User Oriented Transmit Antenna Selection in Massive Multi-User MIMO SDR Systems

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4867 ◽  
Author(s):  
Shida Zhong ◽  
Haogang Feng ◽  
Peichang Zhang ◽  
Jiajun Xu ◽  
Lei Huang ◽  
...  
Keyword(s):  
Software Defined Radio ◽  
Mimo Systems ◽  
Antenna Selection ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Main Idea ◽  
Transmit Antenna Selection ◽  
Mimo Communication ◽  
Input Multiple Output ◽  
Hardware Costs

A transmit antenna selection (TxAS) aided multi-user multiple-input multiple-output (MU-MIMO) system is proposed for operating in the MIMO downlink channel environments, which shows significant improvement in terms of higher data rate when compared to the conventional MU-MIMO systems operating without adopting TxAS, while maintaining low hardware costs. We opt for employing a simple yet efficient zero-forcing beamforming (ZFBF) linear precoding scheme at the transmitter in order to reduce the decoding complexity when considering users’ side. Moreover, considering that users within the same cell may require various qualities of service (QoS), we further propose a novel user-oriented smart TxAS (UOSTxAS) scheme, of which the main idea is to carry out AS based on the QoS requirements of different users. At last, we implement the proposed UOSTxAS scheme in the software defined radio (SDR) MIMO communication hardware platform, which is the first prototype hardware system that runs the UOSTxAS MU-MIMO scheme. Our results show that, by employing TxAS, the proposed UOSTxAS scheme is capable of offering higher data rates for priority users, while reasonably ensuring the performance of the common users requiring lower rates both in simulation and in the implemented SDR MIMO communication platform.

scholarly journals A Fast Adaptive Receive Antenna Selection Method in MIMO System

2013 ◽  
Vol 2013 ◽  
pp. 1-8
Author(s):  
Chaowei Wang ◽  
Weidong Wang ◽  
Cheng Wang ◽  
Shuai Wang ◽  
Yang Yu
Keyword(s):  
Mimo Systems ◽  
Antenna Selection ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
System Capacity ◽  
Adaptive Antenna ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Hardware Costs ◽  
Receive Antenna

Antenna selection has been regarded as an effective method to acquire the diversity benefits of multiple antennas while potentially reduce hardware costs. This paper focuses on receive antenna selection. According to the proportion between the numbers of total receive antennas and selected antennas and the influence of each antenna on system capacity, we propose a fast adaptive antenna selection algorithm for wireless multiple-input multiple-output (MIMO) systems. Mathematical analysis and numerical results show that our algorithm significantly reduces the computational complexity and memory requirement and achieves considerable system capacity gain compared with the optimal selection technique in the same time.

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 Performance Analysis of TAS/SC as well as TAS/MRC MIMO Techniques under α-μ Fading Channels

2019 ◽  
Vol 8 (3) ◽  
pp. 3272-3277
Keyword(s):  
Fading Channels ◽  
Mimo Systems ◽  
Antenna Selection ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Maximal Ratio Combining ◽  
Selection Combining ◽  
Transmit Antenna Selection ◽  
Multiple Input ◽  
Input Multiple Output

Multiple-Input-Multiple-Output (MIMO) system improves performance as well as the capacity of the wireless system. The use of large number of antennas in a MIMO system increases the hardware complexities and also its price. To overcome this, MIMO systems that activate single transmit antenna at a time, namely transmit antenna selection (TAS) is considered in this paper. Selection combining (SC) and Maximal ratio combining (MRC) are carried out at the receiver over    fading channels. Expressions for outage probability and average bit error rate (ABER) are derived considering TAS/SC as well as TAS/MRC MIMO systems. All the derived expressions are validated by Monte-Carlo simulation results.

scholarly journals Deep Learning Based Antenna Selection for MIMO SDR System

Sensors ◽  
2020 ◽  
Vol 20 (23) ◽  
pp. 6987
Author(s):  
Shida Zhong ◽  
Haogang Feng ◽  
Peichang Zhang ◽  
Jiajun Xu ◽  
Huancong Luo ◽  
...  
Keyword(s):  
Decision Making ◽  
Deep Learning ◽  
Software Defined Radio ◽  
Antenna Selection ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Input Multiple Output ◽  
Set Up ◽  
Time Division

In this paper, we propose and implement a novel framework of deep learning based antenna selection (DLBAS)-aided multiple-input–multiple-output (MIMO) software defined radio (SDR) system. The system is constructed with the following three steps: (1) a MIMO SDR communication platform is first constructed, which is capable of achieving uplink communication from users to the base station via time division duplex (TDD); (2) we use the deep neural network (DNN) from our previous work to construct a deep learning decision server to assist the MIMO SDR platform for making intelligent decision for antenna selection, which transforms the optimization-driven decision making method into a data-driven decision making method; and (3) we set up the deep learning decision server as a multithreading server to improve the resource utilization ratio. To evaluate the performance of the DLBAS-aided MIMO SDR system, a norm-based antenna selection (NBAS) scheme is selected for comparison. The results show that the proposed DLBAS scheme performed equally to the NBAS scheme in real-time and out-performed the MIMO system without AS with up to 53% improvement on average channel capacity gain.

scholarly journals Low-Complexity Transmit Antenna Selection in Large-Scale Spatial Modulation Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Peng Wei ◽  
Lu Yin ◽  
Yue Xiao ◽  
Xu He ◽  
Shaoqian Li
Keyword(s):  
Computational Complexity ◽  
System Performance ◽  
Large Scale ◽  
Antenna Selection ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Spatial Modulation ◽  
Transmit Antenna Selection ◽  
Input Multiple Output

Transmit antenna selection (TAS) is an efficient way for improving the system performance of spatial modulation (SM) systems. However, in the case of large-scale multiple-input multiple-output (MIMO) configuration, the computational complexity of TAS in large-scale SM will be extremely high, which prohibits the application of TAS-SM in a real large-scale MIMO system for future 5G wireless communications. For solving this problem, in this paper, two novel low-complexity TAS schemes, named as norm-angle guided subset division (NAG-SD) and threshold-based NAG-SD ones, are proposed to offer a better tradeoff between computational complexity and system performance. Simulation results show that the proposed schemes can achieve better performance than traditional TAS schemes, while effectively reducing the computational complexity in large-scale spatial modulation systems.

scholarly journals An Analytical Study of the Impact of Arbitrary Receive Antenna Correlation in TAS/MRC

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Juan P. Peña-Martín ◽  
Juan M. Romero-Jerez
Keyword(s):  
Closed Form ◽  
Channel Capacity ◽  
Antenna Selection ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Maximal Ratio Combining ◽  
Closed Form Expression ◽  
Transmit Antenna Selection ◽  
Input Multiple Output ◽  
The Impact

Novel closed-form expressions are derived for the performance analysis of a multiple-input multiple-output (MIMO) system in Rayleigh fading using transmit antenna selection (TAS) at the transmitter and maximal ratio combining (MRC) at the receiver. Receive antennas are assumed to be arbitrarily correlated, as no restriction is imposed on the correlation matrix. General exact and asymptotic expressions to evaluate the bit error rate (BER) of different modulation schemes are presented for uncoded transmission, and a closed-form expression is presented for the channel capacity. It is demonstrated that channel capacity may improve due to correlation at the receive antennas if the transmit array size is large enough as a result of a higher signal variability and the antenna selection performed at the transmitter. Monte Carlo simulations have been carried out to validate the analysis, showing an excellent agreement with the theoretical results.

scholarly journals Measurement-Based Analysis of Transmit Antenna Selection for In-Cabin Distributed MIMO System

2012 ◽  
Vol 2012 ◽  
pp. 1-6 ◽  
Author(s):  
Yan Zhang ◽  
Zhenghui Li ◽  
Fengyu Luan ◽  
Limin Xiao ◽  
Shidong Zhou ◽  
...  
Keyword(s):  
Antenna Selection ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Transmit Antenna Selection ◽  
Channel Response ◽  
Channel Sounder ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Capacity Gain ◽  
Reasonable Choice

Aircraft seems to be the last isolated island where the wireless access is still not available. In this paper, we consider the distributed multiple-input multiple-output (D-MIMO) system application based on measurements in aircraft cabin. The channel response matrices of in-cabin D-MIMO system are collected by using a wideband channel sounder. Channel capacities with optimum transmit antenna selections (TASs) are calculated from the measured data at different receiver positions. Then the optimum capacity results are compared to those without selection in different transmit SNR. It is shown that the TAS can lead obvious capacity gain, especially in the front and back of cabin. The capacity gain represents a decreasing trend with the transmit SNR increasing. The optimal transmit antenna subset is closely related to the transmit SNR. With the SNR increasing, more transmit antennas will be chosen for higher performance. The subset of those transmit antennas near the receiver is a reasonable choice in practical application of D-MIMO system.

scholarly journals Dynamic Range Consideration in MIMO Systems with Hybrid Antenna Selection

2011 ◽  
Vol 2011 ◽  
pp. 1-6
Author(s):  
Javad Ahmadi-Shokouh
Keyword(s):  
Dynamic Range ◽  
Mimo Systems ◽  
Antenna Selection ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Three Dimensional ◽  
Spatial Multiplexing ◽  
Linear Network ◽  
Input Multiple Output ◽  
Diversity Transmission

A Hybrid Antenna Selection (HAS), also called Soft Antenna Selection (SAS), method is basically implemented by a Linear Network (LN) located in RF domain of Multiple Input Multiple Output (MIMO) systems. In this paper, we evaluate the SAS-MIMO system, which is optimally tuned based on spatial multiplexing/diversity transmissions, in terms of receiver dynamic range issue. To this end, an SNR analysis is first performed for a reference point that is the input of Receiver Chain Block (RCB). Different systems are then compared based on a standard receiver, that is, WLAN 802.11 b. A three Dimensional (3D) ray-tracing modeling is applied to assist this evaluation. The simulation results for a case study show that although the optimum post-LNA SAS works like a full-complexity MIMO in the spatial multiplexing/diversity transmission strategies, it provides even a better SNR to the baseband, that is, it reveals a receiver dynamic range improvement.

Transmit Antenna Selection Methods For Mimo Systems In Wireless Communications

2021 ◽  
Vol 23 (08) ◽  
pp. 523-531
Author(s):  
Mehak Saini ◽  
◽  
Surender K. Grewal ◽  
Keyword(s):  
Communication Network ◽  
Wireless Communication ◽  
Mimo Systems ◽  
Antenna Selection ◽  
Multiple Input Multiple Output ◽  
Optimal Number ◽  
Selection Methods ◽  
Transmit Antenna Selection ◽  
Wireless Communication Network ◽  
Input Multiple Output

Though MIMO systems improve performance of a wireless communication network by the usage of multiple antennas, demand of distinct set of RF chain (i.e., electronic components required for antenna transmission and reception, in wireless communication) for all the antennas leads to an increase in complexity and cost. Antenna selection technique of MIMO has proved to be a good means to solve this issue. Antenna Selection methods find optimal number of antennas required out of the total antennas present in the MIMO (Multiple Input Multiple Output) system. The selection of antenna can be performed at both ends of the communication network i.e., transmitter or receiver. In this paper, an overview of various Transmit Antenna Selection techniques for various MIMO systems is presented.

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.

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