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Wireless and Mobile Communication Networks: Latest Advances and Prospects

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".

Deadline for manuscript submissions: closed (31 January 2024) | Viewed by 6132

Special Issue Editors

School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
Interests: satellite and terrestrial integrated communication; network optimization

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Guest Editor
National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, China
Interests: future mobile communication; wireless communication

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Guest Editor
Key Laboratory of Modern Measurement and Control Technology, Ministry of Education, Beijing Information Science and Technology University, Beijing 100101, China
Interests: intelligent communication system

Special Issue Information

Dear Colleagues,

With the great commercial success of 5G networks, the focus of the research community is on future wireless and mobile communication networks. Software-defined networks have proven their high efficiency in core network implementations; however, their reliance on physical layers hinders the application of artificial intelligence and machine learning. Higher frequency bands (e.g., THz-domain) are essential in coping with high traffic-volume demands; new antenna technologies such as fluid antenna or phased-array antenna and related beamforming algorithms are still not yet capable of supporting such frequencies. We are also witnessing the growth of emerging unmanned aerial vehicles (UAVs) and low-earth orbit (LEO) satellite constellations, which create novel challenges in 3D network design and resource allocation. Furthermore, ensuring the end-to-end security with high energy efficiency in the heterogenous mobile networks calls for deeper exploration. 

To this end, this Special Issue aims to collect high-quality research papers and review articles on the latest advances and prospects in wireless and mobile communication networks, including 5G and B5G, and miniaturization platform (such as IoT, VR) integration. This Special Issue solicits original papers that contribute to the scientific community with solid ideas that have not been published before and are not under review by other journals or conferences. Theoretical investigations, simulations, and practical experiments are welcome. 

Dr. Ke Wang
Prof. Dr. Wenjin Wang
Prof. Dr. Xuehua Li
Guest Editors

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.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • machine learning and AI wireless communication
  • cognitive and dynamic spectrum access/sharing
  • communication sensing integration
  • THz wireless communication and antenna technologies
  • 3D networks of terrestrial, UAV and LEO satellite constellation
  • network softwarization and virtualization
  • heterogenous network security and network anomaly detection
  • miniaturization platform integration
  • future carbon-neutral wireless communication networks
  • applications and services driving future network development

Published Papers (4 papers)

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Research

16 pages, 567 KiB  
Article
High Reliable Uplink Transmission Methods in GEO–LEO Heterogeneous Satellite Network
by Guoyan Li, Tian Li, Xinwei Yue, Tianwei Hou and Bin Dai
Appl. Sci. 2023, 13(15), 8611; https://doi.org/10.3390/app13158611 - 26 Jul 2023
Cited by 2 | Viewed by 972
Abstract
As a significant component of non-terrestrial networks, satellite communication has gradually evolved into a heterogeneous topology where the network nodes are classified as low Earth orbit (LEO) and geostationary Earth orbit (GEO) nodes. Considering the advantage of low transmission delay of LEO satellites [...] Read more.
As a significant component of non-terrestrial networks, satellite communication has gradually evolved into a heterogeneous topology where the network nodes are classified as low Earth orbit (LEO) and geostationary Earth orbit (GEO) nodes. Considering the advantage of low transmission delay of LEO satellites in a heterogeneous network, ground users are arranged to access LEO satellites in the first priority. By fully understanding the equivalent channel gain difference in the beam-edge and beam-center users, we develop non-orthogonal multiple access (NOMA) in an LEO network where different users are allocated in the same resource block. As a complementary strategy, the beam-edge user has the ability to connect the GEO satellite if the LEO links are not available. That is, the two users are served cooperatively by LEO and GEO satellites in an orthogonal manner. In this paper, we provide deep insights for the uplink transmission performance of NOMA and cooperative orthogonal multiple access methods. As a general metric, the analytical expressions of outage probability are derived and the diversity orders are also provided. The simulation results show that NOMA is capable of providing remarkable performance in low signal-to-noise ratio regions and is more promising when the channels are assumed to be ordered. Full article
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15 pages, 829 KiB  
Article
Ergodic Rate and Outage Performance of Full-Duplex NOMA Relaying with Channel Estimation Errors and Low-Resolution ADCs
by Siye Wang, Yeqin Huang and Yong Yang
Appl. Sci. 2023, 13(12), 6950; https://doi.org/10.3390/app13126950 - 8 Jun 2023
Viewed by 739
Abstract
In this paper, we analyze the performance of a full-duplex (FD) cooperative non-orthogonal multiple access (C-NOMA) relaying system with an amplify-and-forward (AF) protocol in the presence of loopback interference in FD transceivers. Particularly, by considering channel estimation errors and quantization noise in low-resolution [...] Read more.
In this paper, we analyze the performance of a full-duplex (FD) cooperative non-orthogonal multiple access (C-NOMA) relaying system with an amplify-and-forward (AF) protocol in the presence of loopback interference in FD transceivers. Particularly, by considering channel estimation errors and quantization noise in low-resolution analog-to-digital converters (ADCs), the accurate approximation expression for the ergodic rate and closed-form solution for the outage probability are derived, respectively. The validity of the theoretical results is verified by Monte Carlo simulations, which show that both channel estimation errors and quantization noise have deleterious effects on ergodic rate and outage performance for moderate and high signal-to-noise ratios (SNR). In the second phase of the C-NOMA system, both the outage performance and ergodic sum rate decrease at high SNRs due to the effects of loop interference. When the ADC dynamic range reaches a certain level, the system performance is more affected by loopback interference and channel estimation errors compared to the quantization noise of the ADCs. Full article
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24 pages, 831 KiB  
Article
Federated Deep Reinforcement Learning for Energy-Efficient Edge Computing Offloading and Resource Allocation in Industrial Internet
by Xuehua Li, Jiuchuan Zhang and Chunyu Pan
Appl. Sci. 2023, 13(11), 6708; https://doi.org/10.3390/app13116708 - 31 May 2023
Cited by 3 | Viewed by 1995
Abstract
Industrial Internet mobile edge computing (MEC) deploys edge servers near base stations to bring computing resources to the edge of industrial networks to meet the energy-saving requirements of Industrial Internet terminal devices. This paper considers a wireless MEC system in an intelligent factory [...] Read more.
Industrial Internet mobile edge computing (MEC) deploys edge servers near base stations to bring computing resources to the edge of industrial networks to meet the energy-saving requirements of Industrial Internet terminal devices. This paper considers a wireless MEC system in an intelligent factory that has multiple edge servers and mobile smart industrial terminal devices. In this paper, the terminal device has the choice of either offloading the task in whole or in part to the edge server, or performing it locally. Through combined optimization of the task offload ratio, number of subcarriers, transmission power, and computing frequency, the system can achieve minimum total energy consumption. A computing offloading and resource allocation approach that combines federated learning (FL) and deep reinforcement learning (DRL) is suggested to address the optimization problem. According to the simulation results, the proposed algorithm displays fast convergence. Compared with baseline algorithms, this algorithm has significant advantages in optimizing the performance of energy consumption. Full article
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18 pages, 477 KiB  
Article
Performance Analysis of Ambient Backscatter NOMA Systems
by Ce Zhang, Xinwei Yue, Yuanyuan Yao and Xuehua Li
Appl. Sci. 2023, 13(10), 6166; https://doi.org/10.3390/app13106166 - 18 May 2023
Cited by 1 | Viewed by 1003
Abstract
This paper analyzed the performance of an ambient-backscatter-(AmBC)-assisted non-orthogonal multiple access (NOMA) system, where a backscatter device (BD) broadcasts its signal to numerous users. More specifically, the realistic assumptions of imperfect successive interference cancellation (ipSIC) and residual hardware impairments (RHIs) for AmBC–NOMA systems [...] Read more.
This paper analyzed the performance of an ambient-backscatter-(AmBC)-assisted non-orthogonal multiple access (NOMA) system, where a backscatter device (BD) broadcasts its signal to numerous users. More specifically, the realistic assumptions of imperfect successive interference cancellation (ipSIC) and residual hardware impairments (RHIs) for AmBC–NOMA systems were taken into consideration. We further derived the closed-form and asymptotic expressions of outage probability for the BD and the d-th user. Based on the asymptotic expressions, the diversity orders of the BD and the d-th user were obtained in the high SNR regime. Furthermore, throughput and energy efficiency are further discussed for AmBC-assisted orthogonal multiple access (OMA) systems in the delay-limited transmission model. The numerical results revealed that: (i) AmBC–NOMA systems have the ability to achieve better outage behavior than AmBC–OMA; (ii) due to the existence of the backscatter link, the error floors of outage probability for the BD and the d-th user appear at a high signal-to-noise ratio; (iii) AmBC–NOMA systems are able to achieve higher energy efficiency and throughput than AmBC–OMA systems. Full article
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