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5G and 6G Wireless Systems: Challenges, Insights, and Opportunities

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A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Microwave and Wireless Communications".

Deadline for manuscript submissions: 15 July 2024 | Viewed by 6280

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Special Issue Editor

Prof. Dr. Xiongwen Zhao

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Guest Editor

School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China
Interests: 5G/6G; channel modeling; space‒air‒ground integrated network

Special Issue Information

Dear Colleagues,

With the rapid evolution of wireless communication technology, 5G mobile communication has become one of the hottest topics in recent years. In the near future, 5G or 6G networks are expected to provide performance superiority and satisfy emerging services and applications.

This Special Issue aims to showcase the latest research and innovation in 5G/6G, as well as their opportunities and challenges.

Topics of interest include but are not limited to:

Reconfigurable antennas for 5G/6G communications;
EMC in mobile 5G/6G systems;
Fog and Edge for 5G/6G;
Key enabling technologies and standards for 5G and beyond;
Extreme mobile communications for 5G and beyond;
AI for 5G/6G;
Use cases and testbeds beyond the 5G context.

Prof. Dr. Xiongwen Zhao
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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Keywords

5G/6G communications
beyond 5G
massive MIMO
mmWave communications
next-generation radio access networks
mobile edge computing
network
5G and 6G network architecture
5G and 6G network protocol
communication-sense computing integration
NOMA for 5G/6G
channel modeling for future communication

Published Papers (7 papers)

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Research

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21 pages, 2816 KiB

Open AccessArticle

Reinforcement Learning-Based Resource Allocation and Energy Efficiency Optimization for a Space–Air–Ground-Integrated Network

by Zhiyu Chen, Hongxi Zhou, Siyuan Du, Jiayan Liu, Luyang Zhang and Qi Liu

Electronics 2024, 13(9), 1792; https://doi.org/10.3390/electronics13091792 - 6 May 2024

Viewed by 501

Abstract

With the construction and development of the smart grid, the power business puts higher requirements on the communication capability of the network. In order to improve the energy efficiency of the space–air–ground-integrated power three-dimensional fusion communication network, we establish an optimization problem for joint air platform (AP) flight path selection, ground power facility (GPF) association, and power control. In solving the problem, we decompose the problem into two subproblems, one is the AP flight path selection subproblem and the other is the GPF association and power control subproblem. Firstly, based on the GPF distribution and throughput weights, we model the AP flight path selection subproblem as a Markov Decision Process (MDP) and propose a multi-agent iterative optimization algorithm based on the comprehensive judgment of GPF positions and workload. Secondly, we model the GPF association and power control subproblem as a multi-agent, time-varying K-armed bandit model and propose an algorithm based on multi-agent Temporal Difference (TD) learning. Then, by alternately iterating between the two subproblems, we propose a reinforcement learning (RL)-based joint optimization algorithm. Finally, the simulation results indicate that compared to the three baseline algorithms (random path, average transmit power, and random device association), the proposed algorithm improves an overall energy efficiency of the system of 16.23%, 86.29%, and 5.11% under various conditions (including different noise power levels, GPF bandwidth, and GPF quantities), respectively. Full article

(This article belongs to the Special Issue 5G and 6G Wireless Systems: Challenges, Insights, and Opportunities)

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13 pages, 720 KiB

Open AccessArticle

High Accuracy Localization Scheme Using 1-Bit Side Information: Achievability from a GDoP Perspective

by Suah Park, Jiyoung Hwang, Ilmu Byun and Sang Won Choi

Electronics 2024, 13(8), 1574; https://doi.org/10.3390/electronics13081574 - 20 Apr 2024

Viewed by 465

Abstract

In this paper, we provide a novel methodology for high-precision positioning that utilizes 1-bit additional information, which applies to various positioning techniques. The proposed approach leverages binary information to indicate if a user is within a specified space of interest and refines the estimated location information outside this area. By matching the estimated locations outside the area of interest with the valid location information within, this methodology corrects the positional data obtained through any arbitrary positioning technique, aligning the estimated positions with the intended spatial boundaries. Performance analysis metrics, such as Average Positioning Error (APE) and Cumulative Distribution Function for positioning coverage, were employed to assess the effectiveness of the proposed methods. Numerical simulations demonstrate how the proposed method enhances the averaged positioning accuracy, significantly outperforming the conventional time of arrival method. Furthermore, the proposed positioning correction methodology demonstrates validated feasibility applicable to an arbitrary existing positioning method. Full article

(This article belongs to the Special Issue 5G and 6G Wireless Systems: Challenges, Insights, and Opportunities)

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15 pages, 644 KiB

Open AccessArticle

Enhancing Small-Cell Capacity with Wireless Backhaul

by Ran Tao and Wuling Liu

Electronics 2024, 13(4), 797; https://doi.org/10.3390/electronics13040797 - 19 Feb 2024

Viewed by 552

Abstract

Recently, hyperdense small cells have been proposed to meet the challenge of the tremendous increment in cellular data service requirements. To reduce the deployment cost, as well as operated cost, these small cells are usually connected to limited backhauls, in which case the backhaul capacity may become a bottleneck in busy hours. In this paper, we propose an optimal scheme for the small cells to utilize the macrocell links as its wireless backhaul. Based on stochastic geometry, the analytical expressions of network capacity with in-band and out-band wireless backhaul are derived and validated using simulation results. The optimized results show that our proposed scheme can significantly improve the network performance in scenarios with a high traffic load. Full article

(This article belongs to the Special Issue 5G and 6G Wireless Systems: Challenges, Insights, and Opportunities)

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13 pages, 498 KiB

Open AccessArticle

An Efficient Block Successive Upper-Bound Minimization Algorithm for Caching a Reconfigurable Intelligent Surface-Assisted Downlink Non-Orthogonal Multiple Access System

by Xuan Zhou

Electronics 2024, 13(4), 791; https://doi.org/10.3390/electronics13040791 - 18 Feb 2024

Viewed by 456

Abstract

With the booming rollout of 5G communication, abundant new technologies have been proposed for quality of service requirements. In terms of the betterment in transmission coverage, mobile edge caching (MEC) has shown potential in reducing the transmission outage. The performance of MEC, meanwhile, can be promisingly enhanced by reconfigurable intelligent surfaces (RIS). Under this context, we explore a system comprising a small base-station (SBS) with limited cache capacity, two users, and one RIS. The SBS transmits the contents from the cache or fetches them from the remote backhaul hub to communicate with users through directional and possibly reflective channels. In this point-to-multipoint connection, non-orthogonal multiple access (NOMA) is applied, improving the capacity of the system. To minimize the outage probability, we first propose a caching policy from entropy perspective, based on which we investigate the beamforming and power allocation problem. The issue, however, is non-convex and involves multi-dimensional optimization. To address this, we introduce an efficient block successive upper-bound minimization algorithm, grounded in Gershgorin’s circle theorem. This algorithm aims to find the globally optimal solution for power allocation and RIS beamformer, considering both the channel condition and content popularity. Numerical studies are performed to verify the effectiveness of the proposed algorithm. Full article

(This article belongs to the Special Issue 5G and 6G Wireless Systems: Challenges, Insights, and Opportunities)

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15 pages, 1697 KiB

Open AccessArticle

A Light-Weighted Machine Learning Approach to Channel Estimation for New-Radio Systems

by Hyun Woo Lee and Sang Won Choi

Electronics 2023, 12(23), 4740; https://doi.org/10.3390/electronics12234740 - 22 Nov 2023

Viewed by 661

Abstract

In this paper, we provide a light-weighted Machine Learning (ML) approach to channel estimation for New-Radio (NR) systems. Specifically, based on the equivalence between the Channel Impulse Response (CIR) in the time domain and its corresponding Channel Frequency Response (CFR) in the frequency domain, the light-weighted ML model for the channel estimation is shown to be established in comparison to the existing ML-based channel estimator. Furthermore, for practical use, the quantized weights for the light-weighted ML-based estimator are shown to be feasible without significant performance degradation in the sense of mean square error (MSE), which shows the effectiveness of the proposed approach from the perspective of memory overhead. Consequently, we show that there exists Signal to Noise Ratio (SNR) gain in comparison with the existing ML-based estimator, which is validated by numerical results considering the Sounding Reference Signal (SRS) for NR in the 3rd Generation Partnership Project (3GPP). Full article

(This article belongs to the Special Issue 5G and 6G Wireless Systems: Challenges, Insights, and Opportunities)

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22 pages, 6977 KiB

Open AccessArticle

Optimizing Autonomous Vehicle Communication through an Adaptive Vehicle-to-Everything (AV2X) Model: A Distributed Deep Learning Approach

by Radwa Ahmed Osman

Electronics 2023, 12(19), 4023; https://doi.org/10.3390/electronics12194023 - 24 Sep 2023

Cited by 1 | Viewed by 1693

Abstract

Autonomous intelligent transportation systems consistently require effective and secure communication through vehicular networks, enabling autonomous vehicle communication. The reduction of traffic congestion, the alerting of approaching emergency vehicles, and assistance in low visibility traffic are all made possible by effective communication between autonomous vehicles and everything (AV2X). Therefore, a new adaptive AV2X model is proposed in this paper to improve the connectivity of vehicular networks. This proposed model is based on the optimization method and a distributed deep learning model. The presented approach optimizes the inter-vehicle location if required for ensuring effective communication between the autonomous vehicle (AV) and everything (X) using the Lagrange optimization algorithm. Furthermore, the system is evaluated in terms of energy efficiency and achievable data rate based on the optimal inter-vehicle position to show the significance of the proposed approach. To meet the stated goals, the ideal inter-vehicle position is predicted using a distributed deep learning model by learning from mathematically generated data and defined as a restricted optimization problem using the Lagrange optimization technique to improve communication between AV2X under various environmental conditions. To demonstrate the efficiency of the suggested model, the following characteristics are considered: vehicle dispersion, vehicle density, vehicle mobility, and speed. The simulation results show the significance of the proposed model in terms of energy efficiency and achievable data rate compared with other proposed models. Full article

(This article belongs to the Special Issue 5G and 6G Wireless Systems: Challenges, Insights, and Opportunities)

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Review

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25 pages, 2482 KiB

Open AccessReview

Key Technologies for 6G-Enabled Smart Sustainable City

by Nahyun Kim, Gayeong Kim, Sunghoon Shim, Sukbin Jang, Jiho Song and Byungju Lee

Electronics 2024, 13(2), 268; https://doi.org/10.3390/electronics13020268 - 7 Jan 2024

Viewed by 1147

Abstract

With the advancement of information and communication technologies (ICTs), the way we live and communicate with each other is changing rapidly. As urban environments continue to evolve, the smart sustainable city (SSC) has sparked considerable attention. We are hoping for a new era in which numerous devices and machines including vehicles, sensors, and robots are all connected to communicate, respond, and operate in real time. The next-generation communication system, the sixth generation (6G), is expected to play a crucial role in improving the efficiency of urban operations and services. In this paper, we first provide the recent trends and key features of standardization in the SSC. To make the future SSC, we highlight key candidate technologies of 6G such as non-terrestrial networks, advanced mobile edge computing, vision-aided wireless communication, artificial intelligence (AI)-based wireless communication, and integrated sensing and communication. We put forth the main technical challenges given to each prime technology along with the potential benefits to pave the way for 6G-enabled SSC. We further address how the potential benefits of prime technologies enable various urban practice cases for 6G-enabled SSC. Full article

(This article belongs to the Special Issue 5G and 6G Wireless Systems: Challenges, Insights, and Opportunities)

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