Research And Implementation Of Signal Detection Technology In Real Wireless Communication Scenario

With the explosive growth of wireless communication services,the limited spectrum resources are becoming more and more strained due to many factors such as spectrum allocation policies and unreasonable allocation of spectrum resources.How to improve the effective utilization rate of radio spectrum resources has become a current urgent matter in the field of wireless communication and is also a hotspot of current 5G technology research.It is recognized that cognitive radio technology can effectively relieve the above-mentioned problems,which mainly relies on signal detection technology to achieve the purpose of opportunistic access to idle frequency bands to achieve efficient use of spectrum resources.It is play a key role for the field of wireless communication to realize faster and more accurate signal detection technology.At present,plenty of signal detection technologies have been proposed at home and abroad,but there are few studies involving signal detection technology in actual wireless communication systems.Actually,because of noise uncertainty,multipath fading shadow effects,non-Gaussian noise interference,various fading channels and son on,these various reasons make wireless communication systems vulnerable,which lead to those common signal detection techniques are often unable to deal with effectively.The main work is as follows:(1)Taking the influence of factors such as multipath fading,hidden terminals and so on at the detection performance in the actual wireless communication scenario into consideration,a detection technology based on duty cycle and joint detection of multiple detection time slots is proposed by this paper.This paper discuss in detail the influence of signal detection performance caused by noise uncertainty and fading channels in actual communication scenarios.The proposed algorithm by this paper can effectively deal with the impact of the possible hidden terminal and the uncertainty of the position of the main user transmitter on the detection performance,which also greatly improve the accuracy of signal detection and reduce the false alarm probability.(2)Combining the different external environments where the cooperative users are located in the actual wireless communication environment,two emulational environments are designed:the external channel environment where each cooperative user is located is the same or different.The three detection methods of soft collaboration,OR collaboration and AND collaboration detection are studied in detail.According to the simulation results,when the false alarm probability is high in actual detection requirement,it is suitable for AND cooperative detection;additionally if communication overhead and algorithm complexity are neglected,it is no doubted that soft cooperative detection will become the best choice;secondly,when background noise of each cooperative user at the same time,the detection performance of the system will be affected by the average SNR of the collaborative users;lastly,if the collaborative users are under non-Gaussian noise,the performance of collaborative detection system will suffer from it greatly.(3)In view of the previous research,the signal detection techniques are all based on Gaussian noise by a fixed detection sample detection method.Taking the non-Gaussian noise scene in the actual communication environment into consideration,the advantages of energy detection and sequential detection are fully combined to design a segmented energy sequential detection method under Laplace noise.According to the simulation results,compared with energy detection under Laplace noise,the proposed method has less detection time,smaller number of detection samples,lower influence of noise uncertainty,and better performance under low SNR conditions;compared with Sequential detection,the computational complexity and communication overhead are significantly reduced.Additionally,it proves that the proposed method can effectively combat complex communication environments by the simulation of the Rayleigh fading channel environment.