Submit to Sensors Review for Sensors Propose a Special Issue

Journal Browser

► Journal Browser

Cognitive Radio Applications and Spectrum Management II

Special Issue Editors
Special Issue Information
Related Special Issue
Published Papers

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

Deadline for manuscript submissions: closed (31 January 2023) | Viewed by 14712

Share This Special Issue

Special Issue Editor

Prof. Ingrid Moerman

E-Mail Website
Guest Editor

IDLab, Department of Information Technology, Ghent University - imecGhentBelgium, Ghent, Belgium
Interests: wireless networks; time-sensitive networks; deterministic wireless networks; cognitive and cooperative radio; 5G/xG
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Wireless communication networks suffer from capacity bottlenecks because the amount of available spectrum remains fixed while wireless traffic demand keeps growing by approximately 50% each year. This is particularly the case in the lower spectrum bands (<7 GHz), which exhibit the most favorable propagation properties, but mmWave bands are also becoming more crowded with both terrestrial and satellite communications. Since the early days of wireless communication, the wireless spectrum has been allocated according to a static frequency plan, leading to numerous fixed frequency bands. Most of these bands are licensed for exclusive use by specific services or radio technologies, and the process for changing spectrum allocation is extremely slow (cf. spectrum allocation for 5G taking many years). Fixed, exclusive spectrum allocation is further characterized by severe overprovisioning and underutilization both in time and geographically, hence leading to immense wastage of precious resources. Static frequency planning is obviously not a sustainable spectrum allocation model, leaving no room for future wireless services and new wireless actors.

There is no doubt that to increase spectrum utilization, allocation has to become more dynamic, and the spectrum needs to be shared across wireless networks and network operators not only in unlicensed but also in licensed spectrum bands. To this end, new mechanisms need to be explored for more dynamic spectrum allocation. Such techniques do not only involve cognitive radio and spectrum management capabilities but also require strategies for the verification of spectrum usage, ensuring the interference-free operation of multiple networks sharing the same spectrum and avoiding inappropriate or unauthorized use of the spectrum.

Prof. Ingrid Moerman
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.

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.

Related Special Issue

Cognitive Radio Applications and Spectrum Management in Sensors (10 articles)

Published Papers (7 papers)

Download All Papers

Research

Jump to: Review

21 pages, 1093 KiB

Open AccessArticle

A Novel Prediction Model for Malicious Users Detection and Spectrum Sensing Based on Stacking and Deep Learning

by Salma Benazzouza, Mohammed Ridouani, Fatima Salahdine and Aawatif Hayar

Sensors 2022, 22(17), 6477; https://doi.org/10.3390/s22176477 - 28 Aug 2022

Cited by 7 | Viewed by 1383

Abstract

Cooperative network is a promising concept for achieving a high-accuracy decision of spectrum sensing in cognitive radio networks. It enables a collaborative exchange of the sensing measurements among the network users to monitor the primary spectrum occupancy. However, the presence of malicious users leads to harmful interferences in the system by transmitting incorrect local sensing observations.To overcome this security related problem and to improve the accuracy decision of spectrum sensing in cooperative cognitive radio networks, we proposed a new approach based on two machine learning solutions. For the first solution, a new stacking model-based malicious users detection is proposed, using two innovative techniques, including chaotic compressive sensing technique-based authentication for feature extraction with a minimum of measurements and an ensemble machine learning technique for users classification. For the second solution, a novel deep learning technique is proposed, using scalogram images as inputs for the primary user spectrum’s classification. The simulation results show the high efficiency of both proposed solutions, where the accuracy of the new stacking model reaches 97% in the presence of 50% of malicious users, while the new scalogram technique-based spectrum sensing is fast and achieves a high probability of detection with a lower number of epochs and a low probability of false alarm. Full article

(This article belongs to the Special Issue Cognitive Radio Applications and Spectrum Management II)

► Show Figures

Figure 1

12 pages, 2021 KiB

Open AccessArticle

Energy Efficient Multicast Communication in Cognitive Radio Wireless Mesh Network

by Imran Baig, Najam Ul Hasan, Prajoona Valsalan and Manaf Zghaibeh

Sensors 2022, 22(15), 5601; https://doi.org/10.3390/s22155601 - 27 Jul 2022

Cited by 2 | Viewed by 1354

Abstract

Multicasting is a basic networking primitive used in a wide variety of applications that is also true for cognitive radio-based networks. Although cognitive radio technology is considered to be the most promising technology to deal with spectrum scarcity, it relates to completely different aspects of networking and presents new challenges. For cognitive radio-based multicast sessions, it is important to use the spectrum efficiently by reducing the number of channels used as well as engaging fewer nodes in data relaying. This will benefit the network in three ways. First, it will decrease the number of transmissions. Second, it will help to reduce energy usage. Third, it will spare more channels and relay nodes for simultaneous multicast sessions. To achieve these advantages, efficient channel selection and relay nodes are required based on hop-to-hop communication. In this paper an algorithm has been developed that attempts to minimize energy consumption by selecting the minimum possible number of relay nodes and channels for a multicast session, taking into account the sporadic availability of the spectrum. The proposed method performs effectively compared to the flooding method in terms of energy consumption for the provided examples in multicasting. Full article

(This article belongs to the Special Issue Cognitive Radio Applications and Spectrum Management II)

► Show Figures

Figure 1

20 pages, 5819 KiB

Open AccessArticle

Machine Learning Techniques Based on Primary User Emulation Detection in Mobile Cognitive Radio Networks

by Ernesto Cadena Muñoz, Luis Fernando Pedraza and Cesar Augusto Hernández

Sensors 2022, 22(13), 4659; https://doi.org/10.3390/s22134659 - 21 Jun 2022

Cited by 6 | Viewed by 1559

Abstract

Mobile cognitive radio networks (MCRNs) have arisen as an alternative mobile communication because of the spectrum scarcity in actual mobile technologies such as 4G and 5G networks. MCRN uses the spectral holes of a primary user (PU) to transmit its signals. It is essential to detect the use of a radio spectrum frequency, which is where the spectrum sensing is used to detect the PU presence and avoid interferences. In this part of cognitive radio, a third user can affect the network by making an attack called primary user emulation (PUE), which can mimic the PU signal and obtain access to the frequency. In this paper, we applied machine learning techniques to the classification process. A support vector machine (SVM), random forest, and K-nearest neighbors (KNN) were used to detect the PUE in simulation and emulation experiments implemented on a software-defined radio (SDR) testbed, showing that the SVM technique detected the PUE and increased the probability of detection by 8% above the energy detector in low values of signal-to-noise ratio (SNR), being 5% above the KNN and random forest techniques in the experiments. Full article

(This article belongs to the Special Issue Cognitive Radio Applications and Spectrum Management II)

► Show Figures

Figure 1

11 pages, 561 KiB

Open AccessArticle

Dynamic Spectrum Allocation Using Multi-Source Context Information in OpenRAN Networks

by Łukasz Kułacz and Adrian Kliks

Sensors 2022, 22(9), 3515; https://doi.org/10.3390/s22093515 - 05 May 2022

Cited by 3 | Viewed by 1597

Abstract

Bearing in mind the stringent problem of limited and inefficiently used radio resources, a multi-source mechanism for the dynamic adjustment of occupied frequency bands is proposed. Instead of relying only on radio-related information, the system that collects data from various sources is discussed. Mainly, using the ubiquitous sources of information about the presence of users (such as city monitoring), it is possible to identify areas that have high or low expected traffic with high probabilities. Consequently, in low-traffic areas, it is not necessary to allocate all available spectrum resources while maintaining the quality of service. This leads to the improved spectral efficiency of the network. As the level of trust in certain information sources may differ among various operators, we propose to implement such functionality in the form of an application. Our contribution is a proposal for an algorithm that limits the use of radio resources through fuzzy and soft connections of multiple sources of contextual information. The simulation results presented in this paper show that it is possible to reduce the spectrum used with a slight and simultaneous reduction in user bitrate, which increases the spectral efficiency of the entire system. Hence, following the concept of an open radio access network, various policies for information merging may be specified. Full article

(This article belongs to the Special Issue Cognitive Radio Applications and Spectrum Management II)

► Show Figures

Figure 1

27 pages, 2002 KiB

Open AccessArticle

The CODYSUN Approach: A Novel Distributed Paradigm for Dynamic Spectrum Sharing in Satellite Communications

by Irfan Jabandžić, Fadhil Firyaguna, Spilios Giannoulis, Adnan Shahid, Atri Mukhopadhyay, Marco Ruffini and Ingrid Moerman

Sensors 2021, 21(23), 8052; https://doi.org/10.3390/s21238052 - 02 Dec 2021

Viewed by 3665

Abstract

With a constant increase in the number of deployed satellites, it is expected that the current fixed spectrum allocation in satellite communications (SATCOM) will migrate towards more dynamic and flexible spectrum sharing rules. This migration is accelerated due to the introduction of new terrestrial services in bands used by satellite services. Therefore, it is important to design dynamic spectrum sharing (DSS) solutions that can maximize spectrum utilization and support coexistence between a high number of satellite and terrestrial networks operating in the same spectrum bands. Several DSS solutions for SATCOM exist, however, they are mainly centralized solutions and might lead to scalability issues with increasing satellite density. This paper describes two distributed DSS techniques for efficient spectrum sharing across multiple satellite systems (geostationary and non-geostationary satellites with earth stations in motion) and terrestrial networks, with a focus on increasing spectrum utilization and minimizing the impact of interference between satellite and terrestrial segments. Two relevant SATCOM use cases have been selected for dynamic spectrum sharing: the opportunistic sharing of satellite and terrestrial systems in (i) downlink Ka-band and (ii) uplink Ka-band. For the two selected use cases, the performance of proposed DSS techniques has been analyzed and compared to static spectrum allocation. Notable performance gains have been obtained. Full article

(This article belongs to the Special Issue Cognitive Radio Applications and Spectrum Management II)

► Show Figures

Figure 1

Review

Jump to: Research

33 pages, 1240 KiB

Open AccessReview

Spectrum Sharing in the Sky and Space: A Survey

by Ling Zhang, Zhiqing Wei, Lin Wang, Xin Yuan, Huici Wu and Wenyan Xu

Sensors 2023, 23(1), 342; https://doi.org/10.3390/s23010342 - 29 Dec 2022

Cited by 3 | Viewed by 2122

Abstract

In order to achieve the vision of seamless wireless communication coverage, a space–air–ground integrated network is proposed as a key component of the sixth-generation (6G) mobile communication system. However, the spectrum used by aerial networks has become gradually crowded with the increase in wireless devices. Space networks are also in dire need of developing new bands to address spectrum shortages. As an effective way to solve the spectrum shortage problem, spectrum sharing between aerial/space networks and ground networks has been extensively studied. This article summarizes state-of-the-art studies on spectrum sharing between aerial/space networks and ground networks. First, this article provides an overview of aerial networks and space networks and introduces the main application scenarios of aerial networks and space networks. Then, this article summarizes the spectrum sharing techniques between aerial/space networks and ground networks, including existing spectrum utilization rules, spectrum sharing modes and key technologies. Finally, we summarize the challenges of spectrum sharing between aerial/space networks and ground networks. This article provides guidance for spectrum allocation and spectrum sharing of space–air–ground integrated networks. Full article

(This article belongs to the Special Issue Cognitive Radio Applications and Spectrum Management II)

► Show Figures

Figure 1

47 pages, 1402 KiB

Open AccessReview

Graph-Based Resource Allocation for Integrated Space and Terrestrial Communications

by Antoni Ivanov, Krasimir Tonchev, Vladimir Poulkov, Agata Manolova and Nikolay N. Neshov

Sensors 2022, 22(15), 5778; https://doi.org/10.3390/s22155778 - 02 Aug 2022

Cited by 7 | Viewed by 2299

Abstract

Resource allocation (RA) has always had a prominent place in wireless communications research due to its significance for network throughput maximization, and its inherent complexity. Concurrently, graph-based solutions for RA have also grown in importance, providing opportunities for higher throughput and efficiency due to their representational capabilities, as well as challenges for realizing scalable algorithms. This article presents a comprehensive review and analysis of graph-based RA methods in three major wireless network types: cellular homogeneous and heterogeneous, device-to-device, and cognitive radio networks. The main design characteristics, as well as directions for future research, are provided for each of these categories. On the basis of this review, the concept of Graph-based Resource allocation for Integrated Space and Terrestrial communications (GRIST) is proposed. It describes the inter-connectivity and coexistence of various terrestrial and non-terrestrial networks via a hypergraph and its attributes. In addition, the implementation challenges of GRIST are explained in detail. Finally, to complement GRIST, a scheme for determining the appropriate balance between different design considerations is introduced. It is described via a simplified complete graph-based design process for resource management algorithms. Full article

(This article belongs to the Special Issue Cognitive Radio Applications and Spectrum Management II)

► Show Figures