Dynamic Spectrum Management Techniques In Cognitive Radio Based On WSN

As we all know, in today’s society wireless spectrum resource is one of the most valuableresources, but with the continuous and rapid development of science and technology, radiospectrum resources are increasingly strained while using a wireless communication device,especially in wireless sensor Network (WSN). The conventional fixed spectrum allocation hasgreatly limited the spectrum utilization. The main way to alleviate this situation is to improve theflexibility in the allocation of spectrum resources, and the combination of cognitive radio has found“spectral hole" and the rational use of new technology will greatly ease the constraints of wirelesssensor network(WSN) spectrum problems.The first part of this thesis proposes CRWSN communication model based on RSSI classcellular topology by introducing the idea of coalition game, and maximizes system throughput as agoal to solve the mathematical model, then designs a discrete stochastic approximation based onspectrum communication and scheduling algorithms with common joint water-filling algorithm, thealgorithm defines the access method and communication protocol within the communicationalliance. Finally, it introduces the use of game theory in the coalition formation and the stabilitycriteria of the algorithms.The second part of this thesis describes the design and simulation of discrete particle swarmspectrum scheduling optimization algorithm (DPSO) on distributed processing platform based onSpark. First it introduces the traditional particle swarm optimization and discrete particle swarmoptimization algorithm, and then introduces the PSO algorithm to optimize the particles in thespectrum, because CRWSN has more nodes, which makes the problem more complex and therequest processing time is too long, then introduces the optimization algorithm based on paralleldistributed processing platform Spark. It describes in detail how to initialize the particle spectrum tochoose from a spectrum to update to the final particle spectrum stage. Finally, it uses the EU project(SEEDS) to simulate all system design. Experiments show that, under Spark platform, discrete PSOcan indeed be optimized in a relatively short period of time to select the appropriate spectrum tocommunicate. This will greatly enhance the cognitive spectrum scheduling system for wirelesssensor networks and has more optimal use of the entire spectrum space.