Research On Cooperative Spectrum Sensing In Cognitive Radio

Radio spectrum is essential resource for wireless communications.The spectrum scarcity becomes a growing problem in recent years along with the increase of data size carried by wireless system.In order to ease spectrum scarcity,inter-system spectrum sharing is proposed to explore the idle spectrum resource and improve the spectrum efficiency.Cognitive radio is one of the most important means to achieve spectrum sharing.Spectrum sensing is the key technology of cognitive radio which is used to find available spectrum resource for flexible spectrum access.Cooperative spectrum sensing is proposed that fuses local information from different detecting nodes to enhance the performance of spectrum sensing.This dissertation focuses on the cooperative spectrum sensing in cognitive radio.Local decision and information fusion scheme of cooperative sensing are studied in this dissertation to improve the reliability of cooperative sensing,and then the performance of cognitive radio systems.The content of this dissertation includes global information fusion,hierarchical decision fusion and multi-threshold local decision.In the first place,the global information fusion is studied in this dissertation.In cooperative spectrum sensing,fusion center fuses the local decisions of detecting nodes and makes global decision about whether signals of primary system exists.So the merits of global information fusion scheme have immediate impact on the reliability of cooperative spectrum sensing.This dissertation proposes a Semisoft Combination Scheme based on Local Double-threshold Decision(SC-LDD scheme).In this scheme,membership function is used to make local decision,and weighted based decision fusion is used to combine local decisions.The simulation results show that SC-LDD scheme has advantages over conventional hard fusion scheme.The performance improvement is more significant when the number of detecting nodes is small.Secondly,this dissertation studies the hierarchical decision fusion.The capacity limitation of report channels a key technical problem for the detecting nodes which send the local decisions over the air.Hierarchical Decision Fusion can ease the capacity limitation problem of report channel by improving the efficiency of report channels.This dissertation proposes a Low-Overhead Twice Cooperative Spectrum Sensing(LOTCSS)scheme,and derives the analytical expression of the reliability of LOTCSS scheme in additive white Gaussian noise(AWGN),Rayleigh and Rice channels respectively.Moreover,the power allocation based interference alignment scheme is proposed to mitigate inter-cluster interference,and improves the bit error rate performance of secondary system.The results of numerical analysis show that the performance of LOTCSS scheme is better than conventional single-threshold based twice cooperative spectrum sensing in AWGN channel,Rayleigh and Rice Fading channels.Thirdly,Multi-threshold Local Decision is studied in this dissertation.In cooperative spectrum sensing,a "softer" information fusion can be achieved by multi-bit quantization of local detecting results,which can improve the reliability of cooperative spectrum sensing.Multi-bit quantization needs multi-threshold when making local decision.So such "softer"information fusion is equal to multi-threshold local decision.This dissertation proposes an adaptive double threshold cooperative Spectrum Sensing based energy detection(ADTCSSED)scheme and a Multi-Threshold based Cooperative Spectrum Sensing(MTCSS)scheme.ADTCSSED reduces the computational complexity and prolong the sensing time.MTCSS makes a tradeoff between conventional hard fusion and soft fusion.In MTCSS scheme,linear quantization function is adopted to make local decision,and decrease the loss of raw information from detecting nodes.The simulation results show that the MTCSS scheme has better performance compared with conventional single-threshold based cooperative spectrum sensing.