Spectrum Sensing for Improved QoS of Cognitive Radio Networks

Abstract

In this research wireless cognitive radio networks were thoroughly investigated; its structure, operation cognitive cycle components and envisaged future applications. The objective of the research was to determine how to improve the quality of service of these networks. To suggest the required solutions it was imperative to study the performance of the network under different operational situations and different types of channels, numerous types of channels are used; sensing channel, reporting channel, control channel and transmission channels. All of these channels can be perfect or corrupted with different types and degrees of fading. In this respect the research concentrated on only, two main topics in the cognitive cycle which are spectrum sensing operation and the optimization of the work of the fusion center. The results are obtained for the performance of a newly introduced type spectrum sensing called “wideband cooperative sub Nyquist spectrum sensing MS3”, branch of compressed spectrum sensing. It’s operation and performance under different types of fading; namely; Rician and Nakagami-m was investigated and results obtained were found to be consistent with these obtained by other researchers (i.e. Rayleigh and Log-normal) for different types of fading. An optimization was formulated to determine the optimum value of T0 length of time portion allocated for the sensing operation with the objective to maximize the total throughput of network users, at the same time providing a high degree of protection for the primary users. The results showed that the performance of MS3 combined with generalized energy detector supersedes other types of spectrum sensing techniques. Future perspective: Other operation of the cognitive cycle can be investigated and new suggestions for improving the service of cognitive radio can be devised like: • The learning process and how to build up the data base and how to access it to decreases the burden of the inference element and enhance the performance. • The SDR (software defined radio) operation such that minimum delay in the hopping between different spectrum holes which will lead to improved performance. • Effect of other types of channels on the performance of the whole system.