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Electronics
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Cognitive Radio Applications in Wireless Communication System
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Cognitive Radio Applications in Wireless Communication System

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

Deadline for manuscript submissions: closed (15 October 2021) | Viewed by 6357

Special Issue Editors

Prof. Dr. Ke Xiong

E-Mail Website
Guest Editor
1. School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China
2. Engineering Research Center of Network Management Technology for High Speed Railway of Ministry of Education, Beijing Jiaotong University, Beijing 100044, China
3. Collaborative Innovation Center of Railway Traffic Safety, Beijing Jiaotong University, Beijing 100044, China
4. National Engineering Research Center of Advanced Network Technologies, Beijing Jiaotong University, Beijing 100044, China
Interests: IoT; wireless cooperative networks; wireless powered networks; AI-based network optimization and network information theory
Special Issues, Collections and Topics in MDPI journals
Dr. Bo Gao

E-Mail Website
Guest Editor
School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China
Interests: wireless networking; multi-agent systems; Internet of Things; mobile/edge computing; machine learning
Special Issues, Collections and Topics in MDPI journals
Dr. Huacheng Zeng

E-Mail Website
Guest Editor
Department of Computer Science and Engineering, College of Engineering, Michigan State University, East Lansing, MI 48824, USA
Interests: computer networks; cyber physical systems; internet of things; wireless networking; wireless sensing; network security
Prof. Dr. Qiang Ni

E-Mail Website
Guest Editor
School of Computing and Communications, Lancaster University, Lancaster LA1 4YW, UK
Interests: wireless networks; communications; IoT; data analytics and machine learning techniques

Special Issue Information

Dear Colleagues,

Cognitive radio (CR) is an advanced technology that can change its transmitter parameters by interacting with its operating environment. It can improve the utilization of the spectrum, especially allowing unauthorized users to use the spectrum of authorized users. It also can complete a fast search of the frequency spectrum and cause fast physical layer reactions to changes in the local environment.

The idea of CR has been applied in many fields of wireless communication. For example, the IEEE 802.11a network working in the 5 GHz frequency band adopts dynamic frequency selection and transmits power control mechanisms to avoid interference to radar signals. High-speed downlink packet access (HSDPA) and CDMA 1x EV-DO networks adopt the cognitive modulation process to identify the best environment for the user to work by confirming the service that the user needs, and then set the most effective modulation scheme, data rate, and transmission power to meet the user’s QoS requirements.

This Special Issue focuses on the applications of CR in wireless systems. The purpose is to report the latest achievements and progress in related theories and technologies, but not limited to:

  1. Dynamic spectrum sensing in CR;
  2. Resource scheduling in CR;
  3. Ad Hoc network based on CR;
  4. Security of CR networks;
  5. Application of artificial intelligence technology in CR system design;
  6. CR-based IoT systems;
  7. Spectrum sensing in CR;
  8. Application of CR in 5G networks.

Prof. Dr. Ke Xiong
Dr. Bo Gao
Dr. Huacheng Zeng
Prof. Dr. Qiang Ni
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. Electronics 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

  • wireless communications
  • intelligent cognitive radio
  • dynamic spectrum sensing
  • resource management of cognitive radio
  • security in cognitive radio
  • cognitive radio applications

Published Papers (3 papers)

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14 pages, 4702 KiB  
Article
Improved Salp Swarm Optimization Algorithm: Application in Feature Weighting for Blind Modulation Identification
by Sarra Ben Chaabane, Akram Belazi, Sofiane Kharbech, Ammar Bouallegue and Laurent Clavier
Electronics 2021, 10(16), 2002; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10162002 - 19 Aug 2021
Cited by 9 | Viewed by 1780
Abstract
In modulation identification issues, like in any other classification problem, the performance of the classification task is significantly impacted by the feature characteristics. Feature weighting boosts the performance of machine learning algorithms, particularly the class of instance-based learning algorithms such as the Minimum [...] Read more.
In modulation identification issues, like in any other classification problem, the performance of the classification task is significantly impacted by the feature characteristics. Feature weighting boosts the performance of machine learning algorithms, particularly the class of instance-based learning algorithms such as the Minimum Distance (MD) classifier, in which the distance measure is highly sensitive to the magnitude of features. In this paper, we propose an improved version of the Salp Swarm optimization Algorithm (SSA), called ISSA, that will be applied to optimize feature weights for an MD classifier. The aim is to improve the performance of a blind digital modulation detection approach in the context of multiple-antenna systems. The improvements introduced to SSA mainly rely on the opposition-based learning technique. Computer simulations show that the ISSA outperforms the SSA as well as the algorithms that derive from it. The ISSA also exhibits the best performance once it is applied for feature weighting in the above context. Full article
(This article belongs to the Special Issue Cognitive Radio Applications in Wireless Communication System)
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19 pages, 9222 KiB  
Article
An Active and Passive Reputation Method for Secure Wideband Spectrum Sensing Based on Blockchain
by Xinyu Xie, Zhuhua Hu, Min Chen, Yaochi Zhao and Yong Bai
Electronics 2021, 10(11), 1346; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10111346 - 04 Jun 2021
Cited by 10 | Viewed by 2110
Abstract
Spectrum is a kind of non-reproducible scarce strategic resource. A secure wideband spectrum sensing technology provides the possibility for the next generation of ultra-dense, ultra-large-capacity communications to realize the shared utilization of spectrum resources. However, for the open collaborative sensing in cognitive radio [...] Read more.
Spectrum is a kind of non-reproducible scarce strategic resource. A secure wideband spectrum sensing technology provides the possibility for the next generation of ultra-dense, ultra-large-capacity communications to realize the shared utilization of spectrum resources. However, for the open collaborative sensing in cognitive radio networks, the collusion attacks of malicious users greatly affect the accuracy of the sensing results and the security of the entire network. To address this problem, this paper proposes a weighted fusion decision algorithm by using the blockchain technology. The proposed algorithm divides the single-node reputation into active reputation and passive reputation. Through the proposed token threshold concept, the active reputation is set to increase the malicious cost of the node; the passive reputation of the node is determined according to the historical data and recent performance of the blockchain. The final node weight is obtained by considering both kinds of reputation. The proposed scheme can build a trust-free platform for the cognitive radio collaborative networks. Compared with the traditional equal-gain combination algorithm and the centralized sensing algorithm based on the beta reputation system, the simulation results show that the proposed algorithm can obtain reliable sensing results with a lower number of assistants and sampling rate, and can effectively resist malicious users’ collusion attacks. Therefore, the security and the accuracy of cooperative spectrum sensing can be significantly improved in cognitive radio networks. Full article
(This article belongs to the Special Issue Cognitive Radio Applications in Wireless Communication System)
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13 pages, 2384 KiB  
Article
Quantized Cooperative Spectrum Sensing in Bandwidth-Constrained Cognitive V2X Based on Deep Learning
by Jingxian Li and Bin-Jie Hu
Electronics 2021, 10(11), 1315; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10111315 - 30 May 2021
Cited by 2 | Viewed by 1794
Abstract
The output of the network in a deep learning (DL) based single-user signal detector, which is a normalized 2 × 1 class score vector, needs to be transmitted to the fusion center (FC) by occupying a large amount of the communication channel (CCH) [...] Read more.
The output of the network in a deep learning (DL) based single-user signal detector, which is a normalized 2 × 1 class score vector, needs to be transmitted to the fusion center (FC) by occupying a large amount of the communication channel (CCH) bandwidth in the cooperative spectrum sensing (CSS). Obviously, in cognitive radio for vehicle to everything (CR-V2X), it is particularly important to propose a method that makes full use of the bandwidth-constrained CCH to obtain the optimal detection performance. In this paper, we firstly propose a novel single-user spectrum sensing method based on modified-ResNeXt in CR-V2X. The simulation results show that our proposed method performs better than two advanced DL based spectrum sensing methods with shorter inference time. We then introduce a quantization-based cooperative spectrum sensing (QBCSS) algorithm based on DL in CR-V2X, and the impact of the number of reported bits on the sensing results is also discussed. Through the experimental results, we conclude that the QBCSS algorithm reaches the optimal detection performance when the number of bits for quantizing local sensing data is 4. Finally, according to the conclusion, a bandwidth-constrained QBCSS scheme based on DL is proposed to make full use of the CCH with limited capacity to achieve the optimal detection performance. Full article
(This article belongs to the Special Issue Cognitive Radio Applications in Wireless Communication System)
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