Markovian Model Based Channel Allocation in Cognitive Radio Networks

Teotia, Vinesh; Dhurandher, Sanjay Kumar; Woungang, Isaac; Obaidat, Mohammad S.

doi:10.1109/dsdis.2015.124

Cited by 6 publications

(3 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This paper further optimized the sensing duration to achieve the maximum throughput for SUs. Teotia et al 34 proposed a Markov based spectrum assignment approach and also discussed the role of Signal to Interference and Noise Ratio (SINR) in channel allocation problem for the CRNs. Through simulation results authors showed a significant performance improvement of network as compared to the conventional SINR based spectrum assignment approaches.…”

Section: Related Workmentioning

confidence: 99%

A hybrid spectrum access approach for efficient channel allocation and power control in cognitive radio networks

Dhurandher

Kumar

2021

Int J Communication

View full text Add to dashboard Cite

Summary Radio spectrum is the backbone for wireless communication. Many recent studies show that most of the available spectrum has already been allocated. Cognitive radio (CR) provides a new dimension in the field of wireless communication and is considered as a life line for the spectrum scarcity problem as seen all around the world nowadays. CR enables the use of dynamic spectrum access, where secondary users (SUs) or unlicensed users are allowed to opportunistically use the spectrum when it is not being used by the primary users (PUs) or licensed users. Medium Access Control (MAC) protocols use the sensing capability and the primary users behavior to generate the transmission opportunities for SUs. This article proposes two Markov based hybrid access methods namely Hybrid‐P1 and Hybrid‐P2, where a secondary user (SU) dynamically decides it's transmission mode between overlay and underlay depending upon the primary users's (PU's) past and present behavior. Analytical results based on the Markov chain concept are very encouraging and verified through OMNeT++ simulator. This work also analyses the performance of overlay only and underlay only methods, which are well known data transmission techniques in the cognitive radio networks (CRNs). Simulation results show the 47% and 59% performance improvement in Hybrid‐P1 access method, when compared to the overlay only and underlay only access methods respectively. Furthermore simulation results also show the 54% and 65% performance improvement in Hybrid‐P2 access method, when compared to the overlay only and underlay only access methods respectively.

show abstract

Section: Related Workmentioning

confidence: 99%

A hybrid spectrum access approach for efficient channel allocation and power control in cognitive radio networks

Dhurandher

Kumar

2021

Int J Communication

View full text Add to dashboard Cite

show abstract

“…The proposed work in this paper is along the line of previous research on channel allocation in cognitive radio networks using Markov model by (Teotia et al, 2015) and Multi Objective optimization Techniques by (Kumar, 2015). Here, we presented Nondominated set of solutions based channel allocation using multi objectives.…”

Section: Related Work and Backgroundmentioning

confidence: 99%

“…Let the primary user change the state with probability P 11 . (Teotia et al, 2015) presented a Markov model based approach for channel allocation with the use of a Markov chain to calculate the probability of SINR at each state.…”

Section: Proposed System Modelmentioning

confidence: 99%

Channel Allocation in Cognitive Radio Networks using Evolutionary Technique

Kumar

Dhurandher

Tushir

et al. 2016

Proceedings of the 13th International Joint Conference on E-Business and Telecommunications

Self Cite

View full text Add to dashboard Cite

Cognitive radio technology provides a platform at which licensed and unlicensed user share the spectrum. In spectrum sharing, interference plays an important role. Therefore, in this work, interference is considered as a parameter for spectrum sharing between licensed and unlicensed users. The authors in this work proposed a novel channel allocation technique using Non-dominated set of solutions according to following objectives: maximum SINR, probability for maximum SINR and maximum free time of channels. The Non-dominated set of solutions has been calculated using Naive and Slow method. The simulation analysis further shows that the proposed technique outperforms the existing technique in terms of throughput and utilization by 65.47% and 47.31% respectively.

show abstract

On-Line Learning-Based Allocationof Base Stations and Channels in Cognitive Radio Networks

Liu

et al. 2020

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Markovian Model Based Channel Allocation in Cognitive Radio Networks

Cited by 6 publications

References 10 publications

A hybrid spectrum access approach for efficient channel allocation and power control in cognitive radio networks

A hybrid spectrum access approach for efficient channel allocation and power control in cognitive radio networks

Channel Allocation in Cognitive Radio Networks using Evolutionary Technique

On-Line Learning-Based Allocationof Base Stations and Channels in Cognitive Radio Networks

Contact Info

Product

Resources

About