Dynamic Resource Allocation for cognitive radio based smart grid communication networks CRSGN

23 Feb, 2021
Description of Project:

Cognitive Radio (CR) is an emerging technology which is being considered as one of the best solution to solve the spectrum shortage problems by granting dynamic access to free spectrum holes to the unlicensed users by avoiding interference with the licensed users. Smart Grid (SG) is an advancement of conventional electricity management and distribution by a two way communication, sensors and smart devices which increase the reliability, security and efficiency of system.

There is a huge amount of data associated with SG device that need to be transmitted.  The communication network of SG needs a reasonable share of spectrum to transmit this immense data, in order to maintain efficient working of SG system. Due to scarcity of available spectrum resources, SG communication network face many problems regarding communication of data. Cognitive Radio based Smart Grid Network (CRSGN) is introduced in this project, to dynamically and fairly allocate spectrum resources to the unlicensed users (SG devices) along with maximizing the max-sum reward by using nature inspired computational techniques (Heuristic approaches), such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Cat Swarm Optimization (CSO), Differential Evolution (DE) and Hybrid GA-PSO algorithms. A lot of work has been done for spectrum allocation based on fairness by using game theory, graph theory etc. in underlay mode.

A new technique for single cell scenario is proposed in interweave mode to achieve the fairness of the SG system and the results shows that the proposed techniques achieve the desired results both in terms of fairness and max-sum reward.The simulations are done on MATLAB for each algorithm and the results show that the CSO outperforms as compared to the other techniques.