scholarly journals Cognitive Radio Spectrum Allocation Strategy Based on Improved Genetic Algorithm

2013 ◽  
Vol 05 (03) ◽  
pp. 22-26 ◽  
Author(s):  
Bin Hou ◽  
Yunxiao Zu ◽  
Weihai Li ◽  
Gang Liu ◽  
Junjie Ding
Keyword(s):  
Genetic Algorithm ◽  
Cognitive Radio ◽  
Radio Spectrum ◽  
Spectrum Allocation ◽  
Allocation Strategy ◽  
Improved Genetic Algorithm

scholarly journals Multi-Winner Spectrum Allocation in Cognitive Radio Networks: A Single-Sided Auction Theoretic Modelling Approach with Sequential Bidding

Electronics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 602
Author(s):  
Monisha Devi ◽  
Nityananda Sarma ◽  
Sanjib K. Deka
Keyword(s):  
Cognitive Radio ◽  
Communication Networks ◽  
Spectrum Sharing ◽  
Single Channel ◽  
Group Formation ◽  
Radio Spectrum ◽  
Spectrum Allocation ◽  
Allocation Mechanism ◽  
Sealed Bid ◽  
Sequential Bidding

Cognitive radio (CR) has evolved as a novel technology for overcoming the spectrum-scarcity problem in wireless communication networks. With its opportunistic behaviour for improving the spectrum-usage efficiency, CR enables the desired secondary users (SUs) to dynamically utilize the idle spectrum owned by primary users. On sensing the spectrum to identify the idle frequency bands, proper spectrum-allocation mechanisms need to be designed to provide an effectual use of the radio resource. In this paper, we propose a single-sided sealed-bid sequential-bidding-based auction framework that extends the channel-reuse property in a spectrum-allocation mechanism to efficiently redistribute the unused channels. Existing auction designs primarily aim at maximizing the auctioneer’s revenue, due to which certain CR constraints remain excluded in their models. We address two such constraints, viz. the dynamics in spectrum opportunities and varying availability time of vacant channels, and formulate an allocation problem that maximizes the utilization of the radio spectrum. The auctioneer strategises winner determination based on bids collected from SUs and sequentially leases the unused channels, while restricting the channel assignment to a single-channel-multi-user allocation. To model the spectrum-sharing mechanism, we initially developed a group-formation algorithm that enables the members of a group to access a common channel. Furthermore, the spectrum-allocation and pricing algorithms are operated under constrained circumstances, which guarantees truthfulness in the model. An analysis of the simulation results and comparison with existing auction models revealed the effectiveness of the proposed approach in assigning the unexploited spectrum.

Genetic Algorithms for Decision-Making in Cognitive Radio Networks

2013 ◽  
pp. 247-263
Author(s):  
Tommy Hult ◽  
Abbas Mohammed
Keyword(s):  
Genetic Algorithm ◽  
Decision Making ◽  
Genetic Algorithms ◽  
Cognitive Radio ◽  
Search Space ◽  
Radio Spectrum ◽  
Dynamic Decision Making ◽  
Optimal Point ◽  
Optimization Search

Efficient use of the available licensed radio spectrum is becoming increasingly difficult as the demand and usage of the radio spectrum increases. This usage of the spectrum is not uniform within the licensed band but concentrated in certain frequencies of the spectrum while other parts of the spectrum are inefficiently utilized. In cognitive radio environments, the primary users are allocated licensed frequency bands while secondary cognitive users dynamically allocate the empty frequencies within the licensed frequency band according to their requested QoS (Quality of Service) specifications. This dynamic decision-making is a multi-criteria optimization problem, which the authors propose to solve using a genetic algorithm. Genetic algorithms traverse the optimization search space using a multitude of parallel solutions and choosing the solution that has the best overall fit to the criteria. Due to this parallelism, the genetic algorithm is less likely than traditional algorithms to get caught at a local optimal point.

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