Manifold-Based Optimizations for RIS-Aided Massive MIMO Systems

被引:2
作者
De Souza Junior, Wilson [1 ]
Guerra, David William Marques [2 ]
Filho, Jose Carlos Marinello [3 ]
Abrao, Taufik [1 ]
Hossain, Ekram [4 ]
机构
[1] State Univ Londrina UEL, Dept Elect Engn, BR-86057970 Londrina, Brazil
[2] Fed Univ Pernambuco UFPE, Dept Elect & Syst, BR-50670901 Recife, Brazil
[3] Fed Univ Technol Parana UTFPR, Dept Elect Engn, BR-86300000 Cornelio Procopio, Brazil
[4] Univ Manitoba, Dept Elect & Comp Engn, Winnipeg, MB R3T 5V6, Canada
来源
IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY | 2024年 / 5卷
基金
加拿大自然科学与工程研究理事会;
关键词
Optimization; Manifolds; Wireless communication; Array signal processing; Signal processing algorithms; Massive MIMO; Complexity theory; Resource management; Reconfigurable intelligent surfaces; NOMA; Manifold optimization; reconfigurable intelligent surfaces; massive MIMO; energy efficiency; grant-free; random access; RECONFIGURABLE INTELLIGENT SURFACES; IRS; TRANSMIT;
D O I
10.1109/OJCOMS.2024.3512662
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
Manifold optimization (MO) is a powerful mathematical framework that can be applied to optimize functions over complex geometric structures, which is particularly useful in advanced wireless communication systems, such as reconfigurable intelligent surface (RIS)-aided massive MIMO (mMIMO) and extra-large scale massive MIMO (XL-MIMO) systems. MO provides a structured approach to tackling complex optimization problems. By leveraging the geometric properties of the manifold, more efficient and effective solutions can be found compared to conventional optimization methods. This paper provides a tutorial on MO technique and provides some applications of MO in the context of wireless communications systems. In particular, to corroborate the effectiveness of MO methodology, we explore five application examples in RIS-aided mMIMO system, focusing on fairness, energy efficiency (EE) maximization, intra-cell pilot reuse interference mitigation, and grant-free (GF) random access (RA).
引用
收藏
页码:7913 / 7940
页数:28
相关论文
共 37 条
[11]   A Brief Introduction to Manifold Optimization [J].
Hu, Jiang ;
Liu, Xin ;
Wen, Zai-Wen ;
Yuan, Ya-Xiang .
JOURNAL OF THE OPERATIONS RESEARCH SOCIETY OF CHINA, 2020, 8 (02) :199-248
[12]   Reconfigurable Intelligent Surfaces for Energy Efficiency in Wireless Communication [J].
Huang, Chongwen ;
Zappone, Alessio ;
Alexandropoulos, George C. ;
Debbah, Merouane ;
Yuen, Chau .
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2019, 18 (08) :4157-4170
[13]   Interference Nulling Using Reconfigurable Intelligent Surface [J].
Jiang, Tao ;
Yu, Wei .
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2022, 40 (05) :1392-1406
[14]   Downlink Beamforming for Dynamic Metasurface Antennas [J].
Kimaryo, Seraphin F. ;
Lee, Kyungchun .
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2023, 22 (07) :4745-4755
[15]   Exploiting Benefits of IRS in Wireless Powered NOMA Networks [J].
Li, Xingwang ;
Xie, Zhen ;
Chu, Zheng ;
Menon, Varun G. ;
Mumtaz, Shahid ;
Zhang, Jianhua .
IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING, 2022, 6 (01) :175-186
[16]   Joint Symbol-Level Precoding and Reflecting Designs for IRS-Enhanced MU-MISO Systems [J].
Liu, Rang ;
Li, Ming ;
Liu, Qian ;
Swindlehurst, A. Lee .
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2021, 20 (02) :798-811
[17]   Cooperative Beamforming for RIS-Aided Cell-Free Massive MIMO Networks [J].
Ma, Xinying ;
Zhang, Deyou ;
Xiao, Ming ;
Huang, Chongwen ;
Chen, Zhi .
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2023, 22 (11) :7243-7258
[18]   Reconfigurable Intelligent Surfaces-Enabled Intra-Cell Pilot Reuse in Massive MIMO Systems [J].
Marinello Filho, Jose Carlos ;
Abrao, Taufik ;
Hossain, Ekram ;
Mezghani, Amine .
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2024, 23 (08) :9446-9459
[19]   Efficient detectors for MIMO-OFDM systems under spatial correlation antenna arrays [J].
Marques Guerra, David William ;
Fukuda, Rafael Masashi ;
Kobayashi, Ricardo Tadashi ;
Abrao, Taufik .
ETRI JOURNAL, 2018, 40 (05) :570-581
[20]   Manifold Learning: What, How, and Why [J].
Meila, Marina ;
Zhang, Hanyu .
ANNUAL REVIEW OF STATISTICS AND ITS APPLICATION, 2024, 11 :393-417