Multiobjective optimization based on self-organizing Particle Swarm Optimization algorithm for massive MIMO 5G wireless network

被引：16

作者：

Purushothaman, Kesavalu Elumalai ^{[1
]}

Nagarajan, Velmurugan ^{[1
]}

机构：

[1] Adhiparasakthi Engn Coll, Dept Elect & Commun Engn, Melmaruvathur 603319, India

来源：

INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS | 2021年 / 34卷 / 04期

关键词：

massive MIMO; multiple objective optimization; objective functions; self‐ organizing map; spectral efficiency; EVOLUTIONARY ALGORITHMS; ENERGY EFFICIENCY; SYSTEMS;

D O I：

10.1002/dac.4725

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The development of future fifth-generation (5G) wireless networks (WNs) is an active research area worldwide. The 5G network grants significantly upgraded necessities contrasted with those in present wireless systems. Although massive MIMO (mMIMO) incorporation in WN empowers one to encounter 5G network technical necessities, it should handle different challenges to increase the performance. In this paper, a novel multiple objective self-organizing particle swarm optimizer (SOMPSO) is used to solve multiple objective functions such as user data rate, energy efficiency, spectral efficiency, and average area rate of 5G WN with mMIMO. Furthermore, a fuzzy decision maker is utilized to select a solution vector for getting the best compromising result. Our experimental outputs demonstrate that this SOMPSO is an efficient and promising method to solve multiple objective problems in 5G networks.

引用

页数：15

共 34 条

[1]

Amin O., 2015, IEEE T VEH TECHNOL, V65, P1975

[2] Energy-Spectral Efficiency Tradeoffs in 5G Multi-Operator Networks With Heterogeneous Constraints [J].

Aydin, Osman ;

Jorswieck, Eduard Axel ;

Aziz, Danish ;

Zappone, Alessio .

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2017, 16 (09) :5869-5881

[3] A Multiobjective Optimization Approach for Optimal Link Adaptation of OFDM-Based Cognitive Radio Systems with Imperfect Spectrum Sensing [J].

Bedeer, Ebrahim ;

Dobre, Octavia A. ;

Ahmed, Mohamed H. ;

Baddour, Kareem E. .

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2014, 13 (04) :2339-2351

[4] Multiobjective Signal Processing Optimization [The way to balance conflicting metrics in 5G systems] [J].

Bjoernson, Emil ;

Jorswieck, Eduard ;

Debbah, Merouane ;

Ottersten, Bjoern .

IEEE SIGNAL PROCESSING MAGAZINE, 2014, 31 (06) :14-23

[5] Massive MIMO Systems With Non-Ideal Hardware: Energy Efficiency, Estimation, and Capacity Limits [J].

Bjornson, Emil ;

Hoydis, Jakob ;

Kountouris, Marios ;

Debbah, Merouane .

IEEE TRANSACTIONS ON INFORMATION THEORY, 2014, 60 (11) :7112-7139

[6] Massive MIMO and mmWave for 5G Wireless HetNet Potential Benefits and Challenges [J].

Bogale, Tadilo Endeshaw ;

Le, Long Bao .

IEEE VEHICULAR TECHNOLOGY MAGAZINE, 2016, 11 (01) :64-75

[7] Multi-Objective Optimization for Edge Device Placement and Reliable Broadcasting in 5G NFV-Based Small Cell Networks [J].

Chantre, Hernani D. ;

da Fonseca, Nelson L. S. .

IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2018, 36 (10) :2304-2317

[8]

Coello CAC, 2002, IEEE C EVOL COMPUTAT, P1051, DOI 10.1109/CEC.2002.1004388

[9] Big Data Analytics for Large-scale Wireless Networks: Challenges and Opportunities [J].

Dai, Hong-Ning ;

Wong, Raymond Chi-Wing ;

Wang, Hao ;

Zheng, Zibin ;

Vasilakos, Athanasios V. .

ACM COMPUTING SURVEYS, 2019, 52 (05)

[10] A fast and elitist multiobjective genetic algorithm: NSGA-II [J].

Deb, K ;

Pratap, A ;

Agarwal, S ;

Meyarivan, T .

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2002, 6 (02) :182-197

← 1 2 3 4 →