scholarly journals Optimal Transmit Antenna Selection using Hybrid Algorithm for Massive MIMO Technology

2021 ◽  
Author(s):  
Charanjeet Singh ◽  
P.C.Kishore Raja
Keyword(s):  
Optimization Algorithm ◽  
Mimo Systems ◽  
Antenna Selection ◽  
Multipath Propagation ◽  
Radio Channel ◽  
Multiple Input Multiple Output ◽  
Sea Lion ◽  
Transmit Antenna Selection ◽  
Whale Optimization ◽  
Lion Optimization Algorithm

Abstract “Massive Multiple Input Multiple Output (M-MIMO) systems specifically refers to a practical technique for sending and receiving more than one data signal simultaneously over the same radio channel by exploiting multipath propagation”. It depends on several antennas for transferring varied data streams simultaneously. With the increase in count of antennas, the energy or power utilization also gets increased. Thus, it becomes necessary to select optimal transmit antennas that exist as the great challenge in M-MIMO systems. This work introduces a new “Hybrid Sea Lion-Whale Algorithm (HS-WA)” for selecting the optimal transmit antenna by considering the multi-objectives, which increases both capacity and efficiency. The adopted scheme is the combination of both “Whale Optimization Algorithm (WOA) and Sea Lion Optimization Algorithm (SLnO)” that optimizes the antenna’s count and moreover, it finds out “which antenna to be selected”. At last, the supremacy of presented model is confirmed over existing models in terms EE and capacity analysis.

scholarly journals Efficient Capacity-Based Joint Quantized Precoding and Transmit Antenna Selection Using Cross-Entropy Method for Multiuser MIMO Systems

2012 ◽  
Vol 2012 ◽  
pp. 1-7 ◽  
Author(s):  
Jung-Chieh Chen ◽  
Min-Han Chiu ◽  
Yi-Syun Yang ◽  
Kuan-Yuen Liao ◽  
Chih-Peng Li
Keyword(s):  
Computational Complexity ◽  
Mimo Systems ◽  
Antenna Selection ◽  
Random Search ◽  
Multiple Input Multiple Output ◽  
Entropy Method ◽  
Cross Entropy ◽  
Transmit Antenna Selection ◽  
Cross Entropy Method ◽  
Optimum Solution

The current paper considers the joint precoding and transmit antenna selection to reduce hardware cost, such as radio-frequency chains, associated with antennas in the downlink of multiuser multiple-input multiple-output systems with limited feedback. The joint precoding and transmit antenna selection algorithm requires an exhaustive search of all possible combinations and permutations to find the optimum solution at the transmitter, thus resulting in extremely high computational complexity. To reduce the computational load while still maximizing channel capacity, the cross-entropy (CE) method is adopted to determine the suboptimum solution. Compared with the conventional genetic algorithm and random search method, the CE method provides better performance under the same computational complexity, as shown by the simulation results.

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.

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.

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.

scholarly journals Enhanced Image Security using New Sea Lion Optimization Algorithm

2020 ◽  
Vol 9 (7) ◽  
pp. 22-25
Keyword(s):  
Optimization Algorithm ◽  
Electronic Communication ◽  
Digital Data ◽  
Sea Lion ◽  
Image Security ◽  
Encryption And Decryption ◽  
Recent Developments ◽  
Encryption Algorithms ◽  
Lion Optimization Algorithm ◽  
Audio Video

Protection of digital data is the utmost requirement of the day. Everything in the world is being upgraded to electronic communication and which requires protection against data fraud. Data is nowadays not only text but image, audio video individually and sometimes together as multimedia files. Encryption algorithms protect data against attacks and hackers. This paper proposes a new Sealion Optimization algorithm for enhanced image security, analyses several recent developments in encryption and decryption algorithms and summarizes different approaches, their benefits and limitations.

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