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Channel and Location Estimation Enabled a Novel BDCNP Network for massive MIMO VLCP Systems

IEEE WIRELESS COMMUNICATIONS LETTERS 2024年第1期13卷 218-222页

作者： Wei, Yifan Liu, Xiaodong Wang, Yuhao Ma, Shuai Zhou, Fuhui Dobre, Octavia A. Nanchang Univ Sch Informat Engn Nanchang 330031 Peoples R China Peng Cheng Lab Dept Strateg & Adv Interdisciplinary Shenzhen 518066 Peoples R China Nanjing Univ Aeronaut & Astronaut Coll Elect & Informat Engn Nanjing 210016 Peoples R China Mem Univ Fac Engn & Appl Sci St John NF A1C 5S7 Canada

massive multiple-input multiple-output (m-MIMO) integrated visible light communication and positioning (VLCP) systems are of paramount importance to achieve the vision of next generation wireless communication networks since they can simultaneously enhance communication and positioning performance. However, since the computational complexity of channel and location estimation increases with the number of transceivers, it becomes intractable to obtain accurate channel state and location information. In turn, this significantly limits the performance gain of m-MIMO VLCP systems. To tackle this issue, a blind denoising convolutional neural and positioning (BDCNP) network is proposed to estimate both channel state information (CSI) and location in the m-MIMO VLCP system. Specifically, the BDCNP is firstly adopted to denoise the channel matrix with unknown and time-varying superimposed noise to obtain accurate CSI. Then, the location information is extracted from the estimated CSI based on the proposed network. Simulation results demonstrated that the proposed BDCNP network can simultaneously obtain accurate channel state and location information, which outperforms the existing benchmark methods with superior convergence and acceptable computational complexity.

关键词： massive multiple-input multiple-output visible light communication and positioning (VLCP) blind denoising and positioning network channel and location estimation

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Channel estimation for pilot contamination in massive MIMO-NOMA system

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JOURNAL OF HIGH SPEED NETWORKS 2024年第3期30卷 355-373页

作者： Gollagi, Shantappa G. Maheswari, S. S. Sapkale, Pallavi, V Poojitha, Sabbineni KLE Soc KLE Coll Engn & Technol Chikodi Karnataka India Prof Panimalar Engn Coll Chennai Tamil Nadu India Ramrao Adik Inst Technol Nerul Navi Mumbai India Mallareddy Univ Sch Management & Commerce Hyderabad 500100 Telangana India

Channel estimation is crucial for massive multiple-input multiple-output (MIMO) systems to scale up multi-user (MU) MIMO, providing great improvement in spectral and energy efficiency. The nature of non-orthogonal cause pilot contamination is experienced only while estimating multi-cell MIMO scheme with the training and it is misplaced while narrowing concentration to multi-cell or one-cell setting, where information of the channel is assumed to be obtainable at no cost. Non-orthogonal multiple access (NOMA) serves numerous users concurrently utilizing channel gain differences. The advancement in massive MIMO-NOMA technology has offered diverse techniques recently for reducing pilot contamination in massive MIMO-NOMA based on pilot allocation. Here, a new approach called War Strategy Chimp Optimization+Deep Neuro-Fuzzy Network (WSChO+DNFN) is designed for the estimation of channels to reduce pilot contamination in a massive MIMO-NOMA system. It takes place in two phases, the transmitter and the receiver phase. The channel estimation is conducted by DNFN that is tuned by devised WSChO. Furthermore, WSChO is an amalgamation of War Strategy Optimization (WSO) and Chimp Optimization Algorithm (ChOA). Additionally, the WSChO+DNFN attained minimal values of BER and normalized MSE of 0.000103 and 0.000074, respectively. The proposed method has achieved a performance gain of 44.39%, 19.26%, 9.17%, 5.22%, 9.92%, and 6.03% compared to the Orthogonal Frequency Division multiplexing (OFDM), Group Successive Interference Cancellation assisted Semi-Blind Channel Estimation Scheme (GSIC_SBCE), Sector-Based Pilot Assignment Scheme (PAS), Convolutional Neural Network (CNN), User Segregation based Channel Estimation (USCE), Optimal Channel Estimation using Hybrid Machine Learning (OCE_HML), respectively.

关键词： massive multiple-input multiple-output War Strategy Optimization (WSO) non-orthogonal multiple access Chimp Optimization Algorithm (ChOA) Deep Neuro-fuzzy network (DNFN)

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Adaptive training-feedback scheme for FDD in massive MIMO systems

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IET COMMUNICATIONS 2023年第5期17卷 565-575页

作者： Huang, Yi Wang, Haiquan Gao, Danbei Zhao, Zhijin Hangzhou Dianzi Univ Sch Elect & Informat Hangzhou Peoples R China Key Lab Data Storage & Transmiss Technol Zhejiang Hangzhou Peoples R China Hangzhou Dianzi Univ Sch Commun Engn Hangzhou Peoples R China Hangzhou Dianzi Univ Sch Commun Engn Hangzhou 310018 Peoples R China Key Lab Data Storage & Transmiss Technol Zhejiang Hangzhou 310018 Peoples R China

Accurate acquisition of channel state information (CSI) is crucial but difficult in frequency division duplex (FDD) massive multiple-input multiple-output (MIMO) systems. To improve the estimation accuracy and to minimize the training consumption, an adaptive training-feedback scheme based on spatial reciprocity in FDD is proposed. The main idea of this scheme is to construct a reference frame that matches the channel structure. Reference vectors with the strongest correlation with the uplink channel are selected to design the pilots. The pilots can adapt to channel changes in this proposed scheme, which lead to substantial reduction of the training and feedback overheads. The simulation results show that under full feedback, the throughput of proposed adaptive training-feedback scheme can approach to the optimal performance, and under finite-bit feedback, the channel utilization is also significantly high with less training.

关键词： channel state information acquisition frequency division duplex massive multiple-input multiple-output reference frame spatial reciprocity

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Multi-Stream Transmission in massive MIMO Systems With Full-Duplex Bi-Directional Communication Links

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2023年第9期72卷 12367-12372页

作者： Antwi-Boasiako, Bridget Durowaa Anokye, Prince Asiedu, Derek Kwaku Pobi Ahiadormey, Roger Kwao Lee, Kyoung-Jae Molisch, Andreas F. Hanbat Natl Univ Dept Elect Engn Daejeon 34158 South Korea Inst Mines Telecom IMT Atlantique Dept Math & Elect Engn F-29238 Brest France Inst Sci & Technol Informat Commun Div Council Sci & Ind Res GA-0382663 Accra Ghana Univ Southern Calif Ming Hsieh Dept Elect & Comp Engn Los Angeles CA 90089 USA

This paper considers a full-duplex (FD) multi-user massive multiple-input multiple-output system where the base station (BS) and user equipment (UE) bi-directionally transmit and receive multiple independent data streams over the same frequency band. The BS and UEs are equipped with a large-scale antenna array. Accounting for imperfect channel state information, we derive the closed-form expressions for the achievable sum-rate and sum spectral efficiency (SE) for the proposed model using maximum-ratio combining and zero-forcing detection. The analytical solutions are verified with simulations. In addition, our analytical results highlight the benefits of multi-stream transmission and show an improved SE for fewer UEs. Moreover, the results show that increasing the antenna array size helps combat self-interference.

关键词： Full-duplex massive multiple-input multiple-output maximum-ratio combining zero-forcing

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Quasi-Synchronous Random Access for massive MIMO-Based LEO Satellite Constellations

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2023年第6期41卷 1702-1722页

作者： Ying, Keke Gao, Zhen Chen, Sheng Zhou, Mingyu Zheng, Dezhi Chatzinotas, Symeon Ottersten, Bjorn Poor, H. Vincent Beijing Inst Technol Sch Informat & Elect Beijing 100081 Peoples R China Beijing Inst Technol MIIT Key Lab Complex Field Intelligent Sensing Beijing 100081 Peoples R China Beijing Inst Technol Jiaxing Yangtze Delta Reg Acad Jiaxing 314019 Peoples R China Beijing Inst Technol Adv Technol Res Inst Jinan 250307 Peoples R China Univ Southampton Sch Elect & Comp Sci Southampton SO17 1BJ England Baicells Technol Co Ltd Beijing 100089 Peoples R China Univ Luxembourg Interdisciplinary Ctr Secur Reliabil & Trust SnT L-1855 Luxembourg City Luxembourg Princeton Univ Dept Elect & Comp Engn Princeton NJ 08544 USA

Low earth orbit (LEO) satellite constellation-enabled communication networks are expected to be an important part of many Internet of Things (IoT) deployments due to their unique advantage of providing seamless global coverage. In this paper, we investigate the random access problem in massive multiple-input multiple-output-based LEO satellite systems, where the multi-satellite cooperative processing mechanism is considered. Specifically, at edge satellite nodes, we conceive a training sequence padded multi-carrier system to overcome the issue of imperfect synchronization, where the training sequence is utilized to detect the devices' activity and estimate their channels. Considering the inherent sparsity of terrestrial-satellite links and the sporadic traffic feature of IoT terminals, we utilize the orthogonal approximate message passing-multiple measurement vector algorithm to estimate the delay coefficients and user terminal activity. To further utilize the structure of the receive array, a two-dimensional estimation of signal parameters via rotational invariance technique is performed for enhancing channel estimation. Finally, at the central server node, we propose a majority voting scheme to enhance activity detection by aggregating backhaul information from multiple satellites. Moreover, multi-satellite cooperative linear data detection and multi-satellite cooperative Bayesian dequantization data detection are proposed to cope with perfect and quantized backhaul, respectively. Simulation results verify the effectiveness of our proposed schemes in terms of channel estimation, activity detection, and data detection for quasi-synchronous random access in satellite systems.

关键词： Index Terms- Internet of Things low earth orbit satellite massive multiple-input multiple-output random access

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Multicarrier-Division Duplex for Solving the Channel Aging Problem in massive MIMO Systems

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2023年第2期72卷 1940-1954页

作者： Li, Bohan Yang, Lie-Liang Maunder, Robert G. G. Sun, Songlin Xiao, Pei Univ Southampton Sch Elect & Comp Sci Southampton SO17 1BJ England Beijing Univ Posts & Telecommun Sch Informat & Commun Engn Beijing 100876 Peoples R China Univ Surrey Inst Commun Syst 5G 6G Innovat Ctr Guildford GU2 7XH England

The separation of training and data transmission as well as the frequent uplink/downlink (UL/DL) switching make time-division duplex (TDD)-based massive multiple-input multiple-output (mMIMO) systems less competent in fast time-varying scenarios due to the resultant severe channel aging. To this end, a multicarrier-division duplex (MDD) mMIMO scheme associated with two types of well-designed frame structures are introduced for combating channel aging when communicating over fast time-varying channels. For comparison, the corresponding TDD frame structures related to the 3 rd Generation Partnership Project (3GPP) standards and their variant forms are presented. The MDD-specific general Wiener predictor and decision-directed Wiener predictor are introduced to predict the channel state information, respectively, in the time domain based on UL pilots and in the frequency domain based on the detected UL data, considering the impact of residual self-interference (SI). Moreover, by applying the zero-forcing precoding and maximum ratio combining, the closed-form approximations for the lower bounded rate achieved by TDD and MDD frame structures over time-varying channels are derived. Our main conclusion from this study is that the MDD, endowed with the capability of full-duplex but less demand on SI cancellation than in-band full-duplex (IBFD), outperforms both the conventional TDD and IBFD in combating channel aging.

关键词： Channel aging full-duplex massive multiple-input multiple-output multicarrier-division duplex performance analysis time-division duplex Wiener predictor

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Cooperative Multistation Secure Transmission in HF Skywave massive MIMO Communications for Wide-Area IoT Applications

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IEEE TRANSACTIONS ON RELIABILITY 2023年第2期72卷 459-471页

作者： Li, Yan Ding, Guoru Wang, Haichao You, Li Yu, Xianglong Army Engn Univ PLA Coll Commun Engn Nanjing 210007 Peoples R China Southeast Univ Natl Mobile Commun Res Lab Nanjing 210096 Peoples R China Purple Mt Labs Nanjing 211100 Peoples R China

This article proposes a framework of cooperative multistation secure transmission in high-frequency skywave communications for wide-area Internet of Things applications by simultaneously exploiting the benefits of massive multiple-input multiple-output and coordinated multiple points communications. In this framework, the original message sent to the user is divided into several submessages by the core network, each of which will be transmitted to the user by the base stations (BSs). A joint optimization problem is established to maximize the user rate by optimally utilizing multiple BSs with multiple antennas for cooperative precoding. Semidefinite programming is introduced for the precoding vector design for the partial channel state information scenario. To solve the mixed-integer optimization problem of selecting BSs, a low complexity algorithm is proposed. Simulation results show that the performance of the proposed algorithm approaches that of exhaustive search, which demonstrates the effectiveness of the proposed algorithm.

关键词： Internet of Things Receivers Symbols massive MIMO Precoding Azimuth Programming Coordinated multipoint high-frequency skywave communications Internet of Things massive multiple-input multiple-output secure communications

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Angle-Domain Hybrid Beamforming-Based mmWave massive MIMO-NOMA Systems

IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY

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IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY 2023年 4卷 684-699页

作者： Khaled, Israa El Falou, Ammar Langlais, Charlotte Jezequel, Michel Elhassan, Bachar IMT Atlantique Lab STICC UMR CNRS 6285 F-29238 Brest France Lebanese Univ Fac Engn Tripoli 1300 Lebanon King Abdullah Univ Sci & Technol CEMSE Thuwal 23955 Saudi Arabia

The millimeter-wave (mmWave) large-scale antenna arrays (LSAAs) systems play a vital role in increasing the beamforming (BF) gain and acquiring highly directional propagation. Recently, non-orthogonal multiple access (NOMA) has been integrated into these systems to manage massive connectivity and achieve spectral-efficient communications. This paper focuses on angle-domain (AD) hybrid beamforming (BF) for mmWave LSAAs and NOMA systems, thanks to the low complexity, power consumption, and channel estimation overhead. However, with limited radio-frequency chains, the hybrid BF-based single-beam (SB)-NOMA scheme generating a single beam to serve the NOMA users fails to exploit the multi-user diversity due to narrow beams with LSAAs. To tackle this limitation, we design schemes offering additional degrees of freedom. More importantly, they require only the knowledge of angular information and are suitable for either linear or rectangular antenna arrays, unlike those proposed in the literature. The first scheme exploits the time-domain resources to schedule groups having high spatial interference within distinct time slots. To minimize the need for fast and precise synchronization when applying time division multiple access (TDMA) with mmWave NOMA, we leverage the multi-beam (MB)-NOMA framework. And we propose a joint SB- and MB-NOMA scheme to benefit from NOMA multi-user diversity, whatever the cell load and the users' positions. Using the New York University channel simulator (NYUSIM), we further validate the performance of the proposed schemes compared to the solution proposed in the literature and others using fully digital BF. Specifically, the proposed TDMA-based scheme achieves a sum-rate gain of up to 83% over the TDMA-based one existing in the literature. Moreover, we verify the superiority of applying both SB- and MB-NOMA instead of only MB-NOMA.

关键词： Millimeter wave communication NOMA Radio frequency Time division multiple access Resource management Interference Complexity theory Millimeter-wave communications massive multiple-input multiple-output hybrid beamforming non-orthogonal multiple access angle-domain information

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Joint BS and RIS Element Selection with Large Arrays for EE Maximization 19

Joint BS and RIS Element Selection with Large Arrays for EE ...

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19th International Symposium on Wireless Communication Systems (ISWCS)

作者： de Souza Junior, Wilson, Jr. dos Santos, Herman Lucas Abrao, Taufik Univ Estadual Londrina Elect Eng Dept Londrina Parana Brazil UTFPR Acad Dept Elect Cornejo Procopio Brazil

ISBN: (纸本)9798350362527;9798350362510

In this work, we investigate the energy efficiency (EE) metric in reconfigurable intelligent surface (RIS)assisted multi-user (MU) massive multiple-input multiple-output (mMIMO) systems. Our analysis involves the optimization of the number of antennas M and reflective elements (REs) N in the base station (BS) and RIS arrays, respectively, along with the optimization of passive beamforming and power allocation. To address this problem, we introduce a novel joint reinforcementanalytical methodology (JRAM) algorithm, utilizing reinforcement learning (RL) for the elements selection in both arrays and subsequently conventional analytical techniques to optimize passive beamforming and power allocation for the selected elements at the BS and RIS. The numerical results underscore the significance of jointly optimizing the number of operative antennas and REs, leading to a remarkable gain of approximately 40.3% compared to optimizing just the operative elements in the BS and passive beamforming optimization.

关键词： Energy Efficiency Reconfigurable Intelligent Surfaces massive multiple-input multiple-output Joint Reinforcement-Analytical Methodology

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A survey on user-centric cell-free massive MIMO systems

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Digital Communications and Networks 2022年第5期8卷 695-719页

作者： Shuaifei Chen Jiayi Zhang Jing Zhang Emil Björnson Bo Ai School of Electronic and Information Engineering Beijing Jiaotong UniversityBeijing100044China Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong UniversityBeijing100044China Department of Computer Science KTH Royal Institute of TechnologySE-16440KistaSweden Department of Electrical Engineering(ISY) Linköping UniversitySE-58183LinköpingSweden State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong UniversityBeijing100044China

The mobile data traffic has been exponentially growing during the last several *** was enabled by the densification of the network infrastructure in terms of increased cell density(i.e.,Ultra-Dense Network(UDN))and/or the increased number of active antennas per Access Point(AP)(i.e.,massive multiple-input multiple-output(mMIMO)).However,neither UDN nor mMIMO will meet the increasing demand for the data rate of the Sixth Generation(6G)wireless communications due to the inter-cell interference and large quality-of-service ***-Free(CF)mMIMO,which combines the best aspects of UDN and mMIMO,is viewed as a key solution to this *** such systems,each User Equipment(UE)is served by a preferred set of surrounding APs *** this paper,we provide a survey of the state-of-the-art literature on CF *** a starting point,the significance and the basic properties of CF mMIMO are *** then present the canonical framework to discuss the essential details(i.e.,transmission procedure and mathematical system model).Next,we provide a deep look at the resource allocation and signal processing problems related to CF mMIMO and survey the up-to-date schemes and *** that,we discuss the practical issues in implementing CF mMIMO and point out the potential future ***,we conclude this paper with a summary of the key lessons learned in this field.

关键词： 6G network User-centric cell-free network massive multiple-input multiple-output

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