Spectrum mobility in cognitive radio network using spectrum prediction and monitoring techniques

Thakur, Prabhat; Kumar, Alok; Pandit, Shweta; Singh, Ghanshyam; Satashia, S. N.

doi:10.1016/j.phycom.2017.04.005

Cited by 49 publications

(20 citation statements)

References 26 publications

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“…Similarly, the ever-increasing demands for radio spectrum for high-speed internet and multimedia services aggravated by the fixed spectrum allocation policy leads to a huge competition for available spectrum. 120 Moreover, the competition for available spectrum is more pervasive in the industrial environment. This is as a result of noise and interference effects which leads to data loss, false alarm and commands, transmission delay, jitters, and loss of synchronization.…”

Section: Interweaved Transmission In Iwsnsmentioning

confidence: 99%

A review of industrial wireless communications, challenges, and solutions: A cognitive radio approach

Oyewobi

Djouani

Kurien

2020

Trans Emerging Tel Tech

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Integral and crucial to performance of wireless sensor networks (WSNs), and specifically industrial wireless sensor network (IWSN) is stable, robust, reliable, and ubiquitous communications system. Though, wired communications system is suitable for industrial communications and is resilient to shadowing and multipath fading effects of industrial‐WSN environments, yet its wireless counterpart is a much preferred industrial communications technology due to reduced cost and high flexibility which it offers in comparison to wired communications. However, overcrowding of the industrial, scientific, and medical band, where IWSN is deployed together with other heterogeneous technologies, as well as resultant scarcity of usable frequency spectrum has restrained exclusive application of wireless technology for industrial communications. Nonetheless, cognitive radio (CR) has ability to increase spectrum utilization efficiency and channel capacity for industrial wireless communications (IWC) through opportunistic/dynamic spectrum access (DSA) technique. In this review article, we examine how DSA can benefit IWC through exploitation of new perspectives of white space definitions in the licensed bands as well as unlicensed bands. While discussing the potential of DSA for IWC, we have considered the unique characteristics of IWC as well as technical challenges and issues imposed by industrial‐WSN. Accordingly, we have suggested and proffered appropriate CR‐based solutions in mitigating some of the challenges where necessary.

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Section: Interweaved Transmission In Iwsnsmentioning

confidence: 99%

A review of industrial wireless communications, challenges, and solutions: A cognitive radio approach

Oyewobi

Djouani

Kurien

2020

Trans Emerging Tel Tech

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“…In [8], the authors proposed a new technique for SH aimed at reducing unnecessary handoff by taking into account the time limit requirement. First, the expected delay of application packets is calculated based on the queue associated with the channel.…”

Section: Related Workmentioning

confidence: 99%

Intelligent Process of Spectrum Handoff/Mobility in Cognitive Radio Networks

Yawada

Dong

2019

Journal of Electrical and Computer Engineering

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Cognitive radio is an innovative technology in the field of wireless communication systems, aimed at significantly improving the use of the radio spectrum while allowing secondary users to access the spectral band opportunistically. Spectrum management mechanism ensures the transmission of data by controlling the efficiency of operation between the primary and secondary networks. The main task of spectrum management is to ensure that secondary users benefit from the spectrum without interfering with primary users. This paper deals with some of the important characteristics of spectrum mobility in the cognitive radio networks. The new management approaches of the mobility and the connection are designed to reduce the latency and loss of information during spectrum handoff, a list of channel safeguard is maintained in this effect, but the maintenance and update are a challenge. In this paper, we describe the reasons and mechanisms of spectrum handoff. Protocols have been developed to illustrate this handoff mechanism. We also make a comparison between the different methods of spectrum handoff. The simulation results obtained confirm that the protocols developed and the proposed method performed better than the pure reactive handoff method.

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“…[212] Space Sensing Spatial inference is invoked as a complimentary method of spectrum sensing for enabling efficient TV white space database construction with a 2-6 dB gain in terms of root square error, compared with the traditional approach. [175] Time Mobility Spectrum prediction and monitoring are jointly used via OR/AND fusion to improve the perform of spectrum mobility/handoff, which brings 5-25% throughput improvement by reducing the resource wastage. [205] Space Mobility Moderate accuracy predictors improve routing reliability and bandwidth efficiency by 11% and 8%, respectively.…”

Section: A Spectrum Inference For Sensingmentioning

confidence: 99%

“…Huang et al [174] propose a Bayesian inference-based prediction algorithm for spotting the specific channel that is most likely to be available for the CR-aided vehicular ad-hoc networks, where the most critical challenges are the high-speed mobility of vehicles and the dynamically-fluctuating channel availability. As a further advance, P. Thakur et al [175] propose a proactive spectrum prediction technique, where the emergence of PU is predicted before its true emergence, in order to avoid dropping even a single packet.…”

Section: Spectrum Inference For Mobilitymentioning

confidence: 99%

Spectrum Inference in Cognitive Radio Networks: Algorithms and Applications

Ding

Jiao

Wang

et al. 2018

IEEE Commun. Surv. Tutorials

159

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Abstract-Spectrum inference, also known as spectrum prediction in the literature, is a promising technique of inferring the occupied/free state of radio spectrum from already known/measured spectrum occupancy statistics by effectively exploiting the inherent correlations among them. In the past few years, spectrum inference has gained increasing attention owing to its wide applications in cognitive radio networks (CRNs), ranging from adaptive spectrum sensing, and predictive spectrum mobility, to dynamic spectrum access and smart topology control, to name just a few. In this paper, we provide a comprehensive survey and tutorial on the recent advances in spectrum inference. Specifically, we first present the preliminaries of spectrum inference, including the sources of spectrum occupancy statistics, the models of spectrum usage, and characterize the predictability of spectrum state evolution. By introducing the taxonomy of spectrum inference from a time-frequency-space perspective, we offer an in-depth tutorial on the existing algorithms. Furthermore, we provide a comparative analysis of various spectrum inference algorithms and discuss the metrics of evaluating the efficiency of spectrum inference. We also portray the various potential applications of spectrum inference in CRNs and beyond, with an outlook to the 5th generation mobile communications (5G) and next generation high frequency (HF) communications systems. Last but not least, we highlight the critical research challenges and open issues ahead.

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Spectrum mobility in cognitive radio network using spectrum prediction and monitoring techniques

Cited by 49 publications

References 26 publications

A review of industrial wireless communications, challenges, and solutions: A cognitive radio approach

A review of industrial wireless communications, challenges, and solutions: A cognitive radio approach

Intelligent Process of Spectrum Handoff/Mobility in Cognitive Radio Networks

Spectrum Inference in Cognitive Radio Networks: Algorithms and Applications

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