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Dynamic Spectrum Sharing for Future Wireless Systems
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Dynamic Spectrum Sharing for Future Wireless Systems

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Communications".

Deadline for manuscript submissions: closed (30 July 2023) | Viewed by 4036

Special Issue Editors

Prof. Dr. Wei Wang

E-Mail Website
Guest Editor
College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Interests: wireless communication; communication system security; intelligent communication and intelligent network; electromagnetic spectrum security; blockchain
Special Issues, Collections and Topics in MDPI journals
Dr. Qiang Ye

E-Mail Website
Guest Editor
Department of Computer Science, Memorial University of Newfoundland, St. John’s, NL A1B 3X5, Canada
Interests: network slicing for 5G; AI-assisted 5G/6G networking; SDN/NFV; autonomous vehicular networking; edge intelligence; networking protocols for Internet-of-Things (IoT)
Dr. Yiliang Liu

E-Mail Website
Guest Editor
Department of Electronics and Information, School of Cyberspace Security, Xi’an Jiaotong University, Xi’an 710049, China
Interests: wireless communication;information security; physical layer security; blockchain
Dr. Yanyu Cheng

E-Mail Website
Guest Editor
School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore City, Singapore 637332, Singapore
Interests: 5G/6G networks; cybersecurity; cloud computing; machine learning
Dr. Matthew Hamilton

E-Mail Website
Guest Editor
Department of Computer Science, Memorial University of Newfoundland, St. John’s, NL A1B 3X5, Canada
Interests: data visualization; scientific computing; computer graphics; computational imaging; artificial intelligence

Special Issue Information

Dear Colleagues,

With the commercialization of the fifth generation (5G) communication system, wireless networks are evolving toward the sixth generation (6G), aiming at supporting ubiquitous connectivity with space–air–ground (SAG) integrated networking and revolutionizing customer experience via the Internet of Intelligence. However, 6G requires far more spectrum resources for capacity-hungry applications and massive connectivity. Moreover, highly dynamic network topology associated with moving satellites and aerial platforms causes more complex interference patterns than those in terrestrial standalone networks, posing challenges for efficient and secure dynamic spectrum sharing (DSS).

Artificial Intelligence (AI) and blockchain are two emerging technologies in the 5G and beyond era, and thus, incorporating AI and blockchain for DSS has been a consensus in both academia and industry. AI is a powerful tool for decision making on spectrum prediction and spectrum allocation in complicated environments where traditional model-based approaches may not be efficient. Blockchain is a decentralized, immutable, and transparent distributed ledger and is regarded as a promising technology to improve efficiency, reduce cost, and mitigate security and privacy threats in 6G systems. Blockchain can offer benefits for tracking property rights and assets for DSS and also facilitates efficient data and resource utilization in trustless environments, as operators can establish trust relationships without any third party. Thus, blockchain offers tremendous potential for future wireless communication systems.

To better support efficient and secure DSS in future wireless systems, more technical solutions are required from both academia and industry. This Special Issue aims at attracting the latest high-quality research outcomes regarding DSS for future wireless communication systems. It solicits new fundamentals, architectures, advanced methodologies, and promising use cases that promote DSS. Topics include but not limited to

  • Advanced DSS architectures for future wireless systems;
  • Blockchain framework design and optimization for DSS;
  • Blockchain-enabled crowd spectrum sensing for DSS;
  • Blockchain-assisted spectrum regulation;
  • Big spectrum data processing for DSS;
  • Digital-twin-assisted DSS;
  • Edge-computing-assisted blockchain for DSS;
  • Learning-assisted spectrum prediction for DSS;
  • Incentive mechanism design for DSS;
  • Intelligent spectrum resource management for DSS;
  • Security and privacy preservation for DSS.

If you want to learn more information or need any advice, you can contact the Special Issue Editor Penelope Wang via <[email protected]> directly.

Dr. Wei Wang
Dr. Qiang Ye
Dr. Yiliang Liu
Dr. Yanyu Cheng
Dr. Matthew Hamilton
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. Sensors 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 2600 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.

Published Papers (3 papers)

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Research

15 pages, 332 KiB  
Article
Spectrum Allocation and User Scheduling Based on Combinatorial Multi-Armed Bandit for 5G Massive MIMO
by Jian Dou, Xuan Liu, Shuang Qie, Jiayi Li and Chaoliang Wang
Sensors 2023, 23(17), 7512; https://doi.org/10.3390/s23177512 - 29 Aug 2023
Viewed by 640
Abstract
As a key 5G technology, massive multiple-input multiple-output (MIMO) can effectively improve system capacity and reduce latency. This paper proposes a user scheduling and spectrum allocation method based on combinatorial multi-armed bandit (CMAB) for a massive MIMO system. Compared with traditional methods, the [...] Read more.
As a key 5G technology, massive multiple-input multiple-output (MIMO) can effectively improve system capacity and reduce latency. This paper proposes a user scheduling and spectrum allocation method based on combinatorial multi-armed bandit (CMAB) for a massive MIMO system. Compared with traditional methods, the proposed CMAB-based method can avoid channel estimation for all users, significantly reduce pilot overhead, and improve spectral efficiency. Specifically, the proposed method is a two-stage method; in the first stage, we transform the user scheduling problem into a CMAB problem, with each user being referred to as a base arm and the energy of the channel being considered a reward. A linear upper confidence bound (UCB) arm selection algorithm is proposed. It is proved that the proposed user scheduling algorithm experiences logarithmic regret over time. In the second stage, by grouping the statistical channel state information (CSI), such that the statistical CSI of the users in the angular domain in different groups is approximately orthogonal, we are able to select one user in each group and allocate a subcarrier to the selected users, so that the channels of users on each subcarrier are approximately orthogonal, which can reduce the inter-user interference and improve the spectral efficiency. The simulation results validate that the proposed method has a high spectral efficiency. Full article
(This article belongs to the Special Issue Dynamic Spectrum Sharing for Future Wireless Systems)
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19 pages, 1064 KiB  
Article
Improved Spectrum Coexistence in 2.4 GHz ISM Band Using Optimized Chaotic Frequency Hopping for Wi-Fi and Bluetooth Signals
by Ashraf A. Eltholth
Sensors 2023, 23(11), 5183; https://doi.org/10.3390/s23115183 - 30 May 2023
Cited by 4 | Viewed by 1646
Abstract
Efficiently managing coexistence is crucial for achieving high-quality wireless communication in the Industrial, Scientific, and Medical (ISM) band where multiple wireless communication systems operate. Coexistence problems between Wi-Fi and Bluetooth Low Energy (BLE) signals are especially significant due to their shared frequency band, [...] Read more.
Efficiently managing coexistence is crucial for achieving high-quality wireless communication in the Industrial, Scientific, and Medical (ISM) band where multiple wireless communication systems operate. Coexistence problems between Wi-Fi and Bluetooth Low Energy (BLE) signals are especially significant due to their shared frequency band, which often leads to interference and a reduced performance for both systems. Therefore, effective coexistence management strategies are essential for ensuring the optimal performance of Wi-Fi and Bluetooth signals in the ISM band. In this paper, the authors conducted a study to investigate coexistence management in the ISM band by evaluating four frequency hopping techniques: random, chaotic, adaptive, and an optimized chaotic technique proposed by the authors. The optimized chaotic technique aimed to minimize interference and ensure zero self-interference among hopping BLE nodes by optimizing the update coefficient. Simulations were conducted in an environment with existing Wi-Fi signal interference and interfering Bluetooth nodes. The authors compared several performance metrics, including the total interference rate, total successful connection rate, and trial execution time for channel selection processing time. The results indicated that the proposed optimized chaotic frequency hopping technique achieved a better balance between reducing interference with Wi-Fi signals, achieving a high success rate for connecting BLE nodes, and requiring minimal trial execution time. This makes it a suitable technique for managing interference in wireless communication systems. While the proposed technique had a higher interference than the adaptive technique for small numbers of BLE nodes, for larger numbers of nodes it had a much lower interference than the adaptive technique. The proposed optimized chaotic frequency hopping technique provides a promising solution for effectively managing coexistence in the ISM band, particularly between Wi-Fi and BLE signals. It has the potential to improve the performance and quality of wireless communication systems. Full article
(This article belongs to the Special Issue Dynamic Spectrum Sharing for Future Wireless Systems)
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17 pages, 676 KiB  
Article
Electromagnetic Spectrum Allocation Method for Multi-Service Irregular Frequency-Using Devices in the Space–Air–Ground Integrated Network
by Yongchao Meng, Peihan Qi, Qian Lei, Zhengyu Zhang, Jinyang Ren and Xiaoyu Zhou
Sensors 2022, 22(23), 9227; https://doi.org/10.3390/s22239227 - 27 Nov 2022
Viewed by 980
Abstract
The management and allocation of electromagnetic spectrum resources is the inner driving force of the construction of the space–air–ground integrated network. Existing spectrum allocation methods are difficult to adapt to the scenario where the working bandwidth of multi-service frequency-using devices is irregular and [...] Read more.
The management and allocation of electromagnetic spectrum resources is the inner driving force of the construction of the space–air–ground integrated network. Existing spectrum allocation methods are difficult to adapt to the scenario where the working bandwidth of multi-service frequency-using devices is irregular and the working priorities are different. In this paper, an orthogonal genetic algorithm based on the idea of mixed niches is proposed to transform the problem of frequency allocation into the optimization problem of minimizing the electromagnetic interference between frequency-using devices in the integrated network. At the same time, a system model is constructed that takes the minimum interference effect of low-priority-to-high-priority devices as the objective function and takes the protection frequency and natural frequency as the constraint conditions. In this paper, we not only introduce the thought of niches to improve the diversity of the population but also use an orthogonal uniform crossover operator to improve the search efficiency. At the same time, we use a standard genetic algorithm and a micro genetic algorithm to optimize the model. The global searchability and local search precision of the proposed algorithm are all improved. Simulation results show that compared with the existing methods, the proposed algorithm has the advantages of fast convergence, strong stability and good optimization effect. Full article
(This article belongs to the Special Issue Dynamic Spectrum Sharing for Future Wireless Systems)
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