Improved Resource Allocation for TV White Space Network Based on Modified Firefly Algorithm

There is continued increased demand for dynamic spectrum access of TV White Spaces (TVWS) due to growing need for wireless broadband. Some of the use cases such as cellular (2G/3G/4G/5G) access to TVWS may have a high density of users that want to make use of TVWS. When there is a high density of secondary users (SUs) in a TVWS network, there is possibility of high interference among SUs that exceeds the desired threshold and also harmful interference to primary users (PUs). Optimization of resource allocation (power and spectrum allocation) is therefore necessary so as to protect PUs against harmful interference and to reduce the level of interference among SUs. Existing resource allocation optimization algorithms for a TVWS network ignore adjacent channel interference, interference among SUs or apply greedy algorithms which result in sub-optimal resource allocation. In this paper we propose an improved resource allocation algorithm based on continuous-binary firefly algorithm. Simulation is done using Matlab. Simulation results show that the proposed algorithm improves the SU sum throughput and SU signal to interference noise(SINR) ratio in the secondary network

Novel Resource Allocation Algorithm for TV White Space Networks Using Hybrid Firefly Algorithm

There is continued increased demand for dynamic spectrum access of TV White Spaces (TVWS) due to growing need for wireless broadband. Some of the use cases such as cellular (2G/3G/4G/5G) access to TVWS may have a high density of users that want to make use of TVWS. When there is a high of density secondary users (SUs) in a TVWS network, there is possibility of high interference among SUs that exceeds the desired threshold and also harmful interference to primary users (PUs). Optimization of resource allocation (power and spectrum allocation) is therefore necessary so as to protect the PUs against the harmful interference and to reduce the level of interference among SUs. In this paper, a novel and improved resource allocation algorithm based on hybrid firefly algorithm, genetic algorithm  and particle swarm optimization (FAGAPSO) has been designed and applied for joint power and spectrum allocation. Computer simulations have been done using Matlab to validate the performance of the proposed algorithm.   Simulation results show that compared to firefly algorithm (FA), particle swarm optimization (PSO) and genetic algorithm (GA), the algorithm improves the PU SINR, SU sum throughput and SU signal to interference noise (SINR) ratio in a TVWS network. Only one algorithm considered (SAP) has better PU SINR, SU sum throughput and SU signal to interference noise (SINR) ratio in a TVWS network but it has poor running time