A Spectrum Handoff Scheme based on Joint Location and Channel State Prediction in Cognitive Radio

Jaffar, Jasrina; Yusof, Sharifah Kamilah Syed; Ahmad, Norulhusna; Mustapha, Jawahir Che

doi:10.1109/tafgen.2018.8580478

Cited by 3 publications

(2 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This method also takes into account mobile network velocity and its effect on spectrum handoff and was tested in a dynamic network environment. In [8], the authors propose a spectrum handoff method based on activity pattern of PU in the past while also acknowledging CR user movements. This data is used to design an HMM based spectrum handoff.…”

Section: Review Of Related Workmentioning

confidence: 99%

Spectrum Handoff by Baum-Welch algorithm for services in Cognitive Radio Networks

Nandakumar

2019

IJITEE

View full text Add to dashboard Cite

Cognitive Radio Networks (CRN) is the upcoming future prospect in 5G networks. Lack of available spectrum is a serious problem in the networking industry nowadays since, for each individual organization only a limited spectrum bandwidth is offered by National Telecommunications and Information Administration (NTIA). The problem arises due to the increase in the number of users who are supposed to use a limited amount of available bandwidth. Using spectrum handoff allows a cognitive user to access the available licensed spectrum in the absence of the primary user in that particular channel. Efficient spectrum sensing has to be done to check the availability of unused spectrum holes. Machine learning models such as Markov model and Hidden Markov model are used to predict the probabilities. In this paper we have presented a model for efficient sensing using Baum-Welch algorithm, a neural network algorithm which can train inner layer channel traits for given sequence of switching services to yield accurate results without huge datasets. Following emission probabilities are obtained for the channels that are trained from transition probabilities of channel services such as video, voice and data. From the obtained probability values each channel can be offered with best suited services.

show abstract

Section: Review Of Related Workmentioning

confidence: 99%

Spectrum Handoff by Baum-Welch algorithm for services in Cognitive Radio Networks

Nandakumar

2019

IJITEE

View full text Add to dashboard Cite

show abstract

“…In the spectrum handoff, when the PUs reappear, the SUs leave the channel and look for another channel, if available, to complete its unfinished transmission. The selection of a new channel depends on the channel availability and capacity when a handoff decision is made [6][7][8]. Spectrum handoff in a CRN may also be required when the SU experiences the degradation of the quality of service [9,10].…”

Section: Introductionmentioning

confidence: 99%

Efficient Channel Allocation using Matching Theory for QoS Provisioning in Cognitive Radio Networks

Rahim

Alfakeeh

Hussain

et al. 2020

Sensors

View full text Add to dashboard Cite

The focus of research efforts in cognitive radio networks (CRNs) has primarily remained confined to maximizing the utilization of the discovered resources. However, it is also important to enhance the user satisfaction in CRNs by finding a suitable match between the secondary users and the idle channels available from the primary network while taking into consideration not only the quality of service (QoS) requirements of the secondary users but the quality of the channels as well. In this work, the Gale Shapley matching theory was applied to find the best match, so that the most suitable channels from the available pool were allocated that satisfy the QoS requirements of the secondary users. Before applying matching theory, two objective functions were defined from the secondary user’s perspective as well as from the channel’s perspective. The objective function of secondary users is the weighted sum of the data rate of the secondary users and the probability of reappearance of the primary user on the channel. Whereas, the objective function of the channel is the maximum utilization of the channel. The weight factors included in the objective functions allow for diverse service classes of secondary users (SUs) or varying channel quality characteristics. The objective functions were used in developing the preference lists for the secondary users and the idle channels. The preference lists were then used by the Gale Shapely matching algorithm to determine the most suitably matched SU-channel pairs. The performance of the proposed scheme was evaluated using Monte–Carlo simulations. The results show significant improvement in the overall satisfaction of the secondary users with the proposed scheme in comparison to other contemporary techniques. Further, the impact of changing the weight factors in the objective functions on the secondary user’s satisfaction and channel utilization was also analyzed.

show abstract

Paper Spectrum-Aware Transitive Multicast on Demand Distance Vector Routing for Military Cognitive Radio Ad Hoc Networks

Phaswana

Velempini

2019

2019 Ieee Africon

View full text Add to dashboard Cite

A Spectrum Handoff Scheme based on Joint Location and Channel State Prediction in Cognitive Radio

Cited by 3 publications

References 19 publications

Spectrum Handoff by Baum-Welch algorithm for services in Cognitive Radio Networks

Spectrum Handoff by Baum-Welch algorithm for services in Cognitive Radio Networks

Efficient Channel Allocation using Matching Theory for QoS Provisioning in Cognitive Radio Networks

Paper Spectrum-Aware Transitive Multicast on Demand Distance Vector Routing for Military Cognitive Radio Ad Hoc Networks

Contact Info

Product

Resources

About