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Book ChapterDOI

Review: Effective Solutions for Challenges in Cognitive Radio Networks

TL;DR: This chapter undertake a comprehensive analysis of 30 peer-reviewed scientific publications collated from 2017 to 2018 April that examine cognitive radio networks to identify practical solutions proposed to overcome critical challenges in this field.
Abstract: Cognitive radio technology (CRNs) will be the fundamental driving force behind the next generation (5G) mobile communication systems as it provides the optimal solution for the problem of spectrum scarcity via dynamic spectrum usage. The CRNs, however, pose several key challenges such as network management, spectrum allocation, and access, energy efficiency, interference, cost, spectrum sensing, security, and quality of service (QoS). In this chapter, the authors undertake a comprehensive analysis of 30 peer-reviewed scientific publications collated from 2017 to 2018 April that examine cognitive radio networks to identify practical solutions proposed to overcome critical challenges in this field. Nine distinct challenges were considered: network management, spectrum allocation, and access, energy efficiency, interference, cost, spectrum sensing, security, and QoS. The analysis demonstrates that the majority of research work related to CRN focuses on approaches to improve network management and, specifically, optimization of networks.
References
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Journal ArticleDOI
TL;DR: The goal is to incorporate the results of the learning engine into a predicate calculus-based reasoning engine so that radios can remember lessons learned in the past and act quickly in the future.
Abstract: Cognitive radio offers the promise of intelligent radios that can learn from and adapt to their environment. To date, most cognitive radio research has focused on policy-based radios that are hard-coded with a list of rules on how the radio should behave in certain scenarios. Some work has been done on radios with learning engines tailored for very specific applications. This article describes a concrete model for a generic cognitive radio to utilize a learning engine. The goal is to incorporate the results of the learning engine into a predicate calculus-based reasoning engine so that radios can remember lessons learned in the past and act quickly in the future. We also investigate the differences between reasoning and learning, and the fundamentals of when a particular application requires learning, and when simple reasoning is sufficient. The basic architecture is consistent with cognitive engines seen in AI research. The focus of this article is not to propose new machine learning algorithms, but rather to formalize their application to cognitive radio and develop a framework from within which they can be useful. We describe how our generic cognitive engine can tackle problems such as capacity maximization and dynamic spectrum access.

340 citations

Journal ArticleDOI
TL;DR: The SpecPSO is proposed for optimizing handovers using supervised machine learning technique for performing dynamic handover by adapting to the environment and make smart decisions compared to the traditional cooperative spectrum sensing (CSS) techniques.
Abstract: Cognitive communication model perform the investigation and surveillance of spectrum in cognitive radio networks abetment in advertent primary users (PUs) and in turn help in allocation of transmission space for secondary users (SUs). In effective performance of regulation of wireless channel handover strategy in cognitive computing systems, new computing models are desired in operating set of tasks to process business model, and interact naturally with humans or machine rather being programmed. Cognitive wireless network are trained via artificial intelligence (AI) and machine learning (ML) algorithms for dynamic processing of spectrum handovers. They assist human experts in making enhanced decisions by penetrating into the complexity of the handovers. This paper focuses on learning and reasoning features of cognitive radio (CR) by analyzing primary user (PU) and secondary user (SU) data communication using home location register (HLR) and visitor location register (VLR) database respectively. The SpecPSO is proposed for optimizing handovers using supervised machine learning technique for performing dynamic handover by adapting to the environment and make smart decisions compared to the traditional cooperative spectrum sensing (CSS) techniques.

287 citations

Journal ArticleDOI
TL;DR: A comprehensive survey of CR technology is conducted and the key enabling technologies that may be closely related to the study of 5G in the near future are presented in terms of full-duplex spectrum sensing, spectrum-database based Spectrum sensing, auction based spectrum allocation, carrier aggregation based spectrum access.
Abstract: With the development of wireless communication technology, the need for bandwidth is increasing continuously, and the growing need makes wireless spectrum resources more and more scarce. Cognitive radio (CR) has been identified as a promising solution for the spectrum scarcity, and its core idea is the dynamic spectrum access. It can dynamically utilize the idle spectrum without affecting the rights of primary users, so that multiple services or users can share a part of the spectrum, thus achieving the goal of avoiding the high cost of spectrum resetting and improving the utilization of spectrum resources. In order to meet the critical requirements of the fifth generation (5G) mobile network, especially the Wider-Coverage , Massive-Capacity , Massive-Connectivity , and Low-Latency four application scenarios, the spectrum range used in 5G will be further expanded into the full spectrum era, possibly from 1 GHz to 100 GHz. In this paper, we conduct a comprehensive survey of CR technology and focus on the current significant research progress in the full spectrum sharing towards the four scenarios. In addition, the key enabling technologies that may be closely related to the study of 5G in the near future are presented in terms of full-duplex spectrum sensing, spectrum-database based spectrum sensing, auction based spectrum allocation, carrier aggregation based spectrum access. Subsequently, other issues that play a positive role for the development research and practical application of CR, such as common control channel, energy harvesting, non-orthogonal multiple access, and CR based aeronautical communication are discussed. The comprehensive overview provided by this survey is expected to help researchers develop CR technology in the field of 5G further.

249 citations

Journal ArticleDOI
TL;DR: A secure blockchain verification protocol is proposed as a method for enabling and securing spectrum sharing in moving cognitive radio (CR) networks and outperforms the conventional system in moderate cases of small-scale fading, and in the case of severe small- scale fading, the blockchain protocol will outperform theventional system if multipath diversity is not used.
Abstract: In this article, we propose a blockchain verification protocol as a method for enabling and securing spectrum sharing in moving cognitive radio (CR) networks. The spectrum-sharing mechanism is used as a medium-access protocol for accessing wireless bandwidth among competing CRs. We introduce a virtual currency, called Specoins, for payment to access the spectrum. An auction mechanism based on a first-come-first-served queue is used, with the price for the spectrum advertised by each primary user in a decentralized fashion. The blockchain protocol facilitates the transactions between primary and secondary users and is used to validate and save each user's virtual wallet. Also important for mobile networks, the blockchain serves as a distributed database that is visible by all participating parties, and any node can volunteer to update the blockchain. The volunteer nodes are called miners, and they are awarded with Specoins. We propose diverse methods to exchange the Specoins to make leasing possible even by CRs that are not miners. We show the improvement of the proposed algorithm compared with the conventional Aloha medium-access protocol in terms of spectrum usage. This difference is investigated using small-scale fading variation in the wireless channel to compare the performance of our secure method with the conventional medium access used in vehicular communications. The secure blockchain verification protocol is not only secure but also outperforms the conventional system in moderate cases of small-scale fading. In the case of severe small-scale fading, the blockchain protocol will outperform the conventional system if multipath diversity is not used.

122 citations

Journal ArticleDOI
TL;DR: This work has investigated the cooperative relaying technique in the context of the overlay spectrum access scheme aiming for allowing the PUs to transmit at a lower power and/or at a higher throughput, while at the same time enabling the CUs to communicate using the bandwidth released.
Abstract: In order to mitigate the shortage of wireless spectrum, the appealing concepts of cooperative communication techniques and cognitive radio (CR) networks have been combined for the sake of improving the spectral efficiency and hence the overall system throughput. We mainly survey the overlay spectrum access scheme in this novel cooperative CR (CCR) network context. Therefore, the interference between the licensed users/primary users (PUs) and the unlicensed users/cognitive users (CUs) can be offset by relying on some of the CUs to act as relay nodes. More specifically, we have investigated the cooperative relaying technique in the context of the overlay spectrum access scheme aiming for allowing the PUs to transmit at a lower power and/or at a higher throughput, while at the same time enabling the CUs to communicate using the bandwidth released. Additionally, gaming techniques can be employed for negotiating between the PUs and the CUs for determining the specific fraction of relaying and active transmission time. Therefore, we will consider two main schemes in the overlay spectrum access scheme based on the CCR network, which are the frequency division-based channel as well as the time-division based channel. Moreover, we have surveyed the relevant advances concerning the game-based model of the overlay-based CR network. Specifically, both the family of non-cooperative and cooperative games as well as matching games have been reviewed. Furthermore, we will review the joint design of coding, modulation, user-cooperation, and CCR techniques, which leads to significant mutual benefits for both the PUs and CUs.

114 citations

Trending Questions (1)
What are the challenges faced by CRM?

The challenges faced by cognitive radio networks (CRNs) include network management, spectrum allocation and access, energy efficiency, interference, cost, spectrum sensing, security, and quality of service (QoS).