Research Of Cooperative Spectrum Sensing In Cognitive Radio

Spectrum is the most importance resource for wireless communication systems. The inconsistency between the lack of spectrum resources and new service demands which need lots of bands becomes more and more obviously. In order to solve the problem, cognitive radio is presented. Spectrum sensing is the basis and prerequisite of cognitive radio. It is also the most challenging issues in cognitive radio. Aiming at the problem, the local spectrum sensing algorithms and cooperative spectrum sensing algorithms are discussed in detail with lots of simulation analysis in this paper.First of all, the backgrounds, applications and developments and research significance are introduced, then all kinds of local spectrum sensing algorithms are describes, and the formula derivation of non-cooperative energy detection are deduced in detail with simulations and performance analysis results. However, the performances of local spectrum sensing algorithms degrade fast due to Multipath Rayleigh Fading. In order to eliminate the multipath influence, cooperative spectrum sensing is represented. The soft combination algorithms (for example maximum ratio combination, equal gain combination and optimal combination etc) and an innovation 2bits quantization scheme are introduced. The simulations and performance analysis have been done, and the simulation results indicate that the 2bits scheme is very well compromised between performance and complexity. Secondly, the conventional hard combination algorithms (for instance "and", "or", "k out of n") based on energy detection in cooperative spectrum sensing are represented. Based on the above, a self-adaptation single threshold spectrum sensing algorithm for cooperative users is proposed. The simulation results indicate that the proposed algorithm can boost the system performance. Eventually, the key parameters (such as detection probability, false alarm probability, throughput and sensing time) in cognitive radio are discussed and optimized in this paper. At the same time, an innovation optimal strategy for throughputs is introduced followed with the simulation results which indicate that the strategy is very well.