Cognitive radio networks spectrum allocation: An ACS perspective

Koroupi, Faroukh; Talebi, Siamak; Salehinejad, Hojjat

doi:10.1016/j.scient.2011.04.029

Cited by 33 publications

(14 citation statements)

References 18 publications

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“…The work finds that PSO with simulated annealing performs better than graph coloring and greedy algorithms in terms of solution quality. Spectrum allocation using graph coloring and ant colony optimization (ACO) has been presented Koroupi et al in [11]. ACO is found to perform better than PSO and CSGC in terms of solution quality.…”

Section: Spectrum Allocation Using Population-based Metaheuristic Algmentioning

confidence: 99%

Comparison of Hybrid Firefly Algorithms for Binary and Continuous Optimization Problems in a TV White Space Network

Ronoh

Kamucha

2020

Wseas Transactions on Communications

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TV white spaces (TVWS) can be used by Secondary Users (SUs) through Dynamic Spectrum Access (DSA) as long as they do not cause harmful interference to Primary Users (PUs). Due to spectrum scarcity, there is increasing demand for DSA. When there is a high density of SUs in a TVWS network such as cellular access to TVWS, problem of interference among SUs will arise. Possibility of harmful interference to PUs may also arise. Power and spectrum allocation optimization is therefore necessary to reduce the level of interference among SUs and to protect PUs against harmful interference. In this paper different hybrid firefly algorithms with particle swarm optimization and genetic algorithm for optimization of spectrum allocation in a TVWS network as a discrete optimization problem and that of power allocation as a continuous optimization problem are compared. Simulation was done using Matlab. Simulation results show that hybrid firefly algorithm with genetic algorithm outperforms other hybrid firefly algorithms for spectrum allocation. On the other hand, hybrid firefly algorithm with genetic algorithm and particle swarm optimization outperforms all other algorithms for power allocation as continuous optimization problem

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Section: Spectrum Allocation Using Population-based Metaheuristic Algmentioning

confidence: 99%

Comparison of Hybrid Firefly Algorithms for Binary and Continuous Optimization Problems in a TV White Space Network

Ronoh

Kamucha

2020

Wseas Transactions on Communications

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“…Koroupi et al [8] have approached the problem using the ACO technique. This method has worked well for dynamic networks, providing a fast and low-cost solution.…”

Section: Literature Surveymentioning

confidence: 99%

“…This problem has been re-casted to a NP-hard problem and suitable approaches have been designed to solve it, like game theory, graph coloring, etc. [8].…”

Section: Problem Descriptionmentioning

confidence: 99%

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Spectrum Allocation in Cognitive Radio: A PSO-based Approach

Mishra

Sagnika

Singh

et al. 2019

Period. Polytech. Elec. Eng. Comp. Sci.

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Cognitive radio systems have taken a fore-running position in the wireless communication technology. With most of the communication taking place through multi-carrier systems, the allocation of available spectrum to various carriers is a prominent issue. Since cognitive systems provide an environment of dynamic spectrum allocation, it becomes necessary to perform dynamic spectrum allocation swiftly with due consideration of parameters, like power consumption, fair distribution and minimal error. This paper considers a Particle Swarm Optimization-based approach, popularly used for solving large problems involving complex solution spaces to reach an optimal solution within feasible time. The mentioned spectrum allocation problem has been solved using PSO with a view to maximize the total transfer rate of the system, within specified constraints of maximum error rate, maximum power consumption and minimum transfer rate per user. The results have been compared with the existing Genetic Algorithm-based approach and have proved to be more effective.

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“…This is also an iterative algorithm. The ant colony system is described in [9]. The genetic algorithm is used in [10]- [11].…”

Section: Introductionmentioning

confidence: 99%

Optimal Spectrum Sensor Assignment in Multi-channel Multi-user Cognitive Radio Networks

Nandini¹,

Hariprasad²

2018

JTIT

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Accurate detection of spectrum holes is the most important and critical task in any cognitive radio (CR) communication system. When a single spectrum sensor is assigned to detect a speciﬁc primary channel, then the detection may be unreliable because of noise, random multipath fading and shadowing. Also, even when the primary channel is invisible at the CR transmitter, it may be visible at the CR receiver (the hidden primary channel problem). With a single sensor per channel, a high and consistently uniform level of sensitivity is required for reliable detection. These problems are solved by deploying multiple heterogeneous sensors at distributed locations. The proposed spectrum hole detection method uses cooperative sensing, where the challenge is to properly assign sensors to diﬀerent primary channels in order to achieve the best reliability, a minimum error rate and high eﬃciency. Existing methods use particle swarm optimization, the ant colony system, the binary ﬁreﬂy algorithm, genetic algorithms and non-linear mixed integer programming. These methods are complex and require substantial pre-processing. The aim of this paper is to provide a simpler solution by using simpler binary integer programming for optimal assignment. Optimal assignment minimizes the probability of interference which is a non-linear function of decision variables. We present an approach used to linearize the objective function. Since multiple spectrum sensors are used, the optimal constrained assignment minimizes the maximum of interferences. While performing the optimization, the proposed method also takes care of the topological layout concerned with channel accessibility. The proposed algorithm is easily scalable and ﬂexible enough to adapt to diﬀerent practical scenarios.

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Cognitive radio networks spectrum allocation: An ACS perspective

Cited by 33 publications

References 18 publications

Comparison of Hybrid Firefly Algorithms for Binary and Continuous Optimization Problems in a TV White Space Network

Comparison of Hybrid Firefly Algorithms for Binary and Continuous Optimization Problems in a TV White Space Network

Spectrum Allocation in Cognitive Radio: A PSO-based Approach

Optimal Spectrum Sensor Assignment in Multi-channel Multi-user Cognitive Radio Networks

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