Research On Key Technologies Of Intelligent Communication Countermeasures In Cognitive Self-Organizing Networks

With the continuous development of science and technology,wireless communication systems continue to evolve.At present,5G has begun to be applied on a large scale,and users have higher and higher requirements for communication,which has led to increasingly limited radio resources.Especially in military communication applications,the wireless electromagnetic environment has become particularly complicated due to the information transmission between multiple communication devices,the complexity of the geographical environment,and the malicious interference of enemy signals.In order to detect the enemy's radio communication signals,it is usually necessary to dynamically detect,real-time and accurately interfere with the enemy's communication and determine its technical parameters.On the basis of in-depth study of software radio and employment perception detection methods,this article combines software Lab VIEW and hardware NI-USRP 2920 to build an intelligent communication countermeasure platform.In order to improve the ability to detect cognitive users to achieve efficient communication confrontation,this article mainly does the following work:First of all,for the single user situation,this thesis improves the energy detection method and reduces the threshold training requirements.After obtaining the frequency point data that meets the requirements,the maximum value of the array is indexed to directly obtain the communication frequency point of the primary user,and then the relevant calculation energy Indirectly obtain the effective bandwidth of the user.Experimental results show that the relevant parameters of user signals can be obtained more accurately,and the signal perception speed is improved to a certain extent.Secondly,in order to meet the needs of multiple countermeasures,in addition to parameters such as frequency and bandwidth,it is also necessary to obtain the modulation scheme of the wireless signal.This article introduces the principle of modulation signal,including MPSK,MASK,MFSK and MSK.Digital characteristics and frequency spectrum characteristics of digital modulation signals.This article classifies different modulation schemes based on the method of cyclostationary feature detection,and the classifier uses the MAXNET neural structure.Experimental results show that the proposed method can effectively automatically classify four modulation methods,including FSK,BPSK,MSK and QPSK.Finally,for realizing the dynamic communication countermeasure demonstration,this paper builds the corresponding intelligent communication countermeasure platform through the software radio equipment USRP and the software development environment Lab VIEW.The platform mainly realizes the effective acquisition of frequency point bandwidth characteristic parameters;target user perception based on frequency point detection;self-interference signal elimination and suppression,and real-time detection of electromagnetic spectrum environment and other system functions.Experimental results show that the intelligent communication countermeasure system built can effectively continuously interfere with the target user's communication,and after the target user performs frequency hopping,it can still achieve continuous tracking of interference through spectrum sensing.