Study On Detection Algorithm And Performance Of Multi-Carrier NOMA System In Jamming Environment

With the rapid development of the Internet of Things(Io T)and 5G,Non-Orthogonal Multiple Access(NOMA)technology has become an important multi-user communication technology.Unlike traditional Orthogonal Multiple Access(OMA)technology,NOMA can effectively improve system capacity and spectrum efficiency,thus meeting the growing wireless communication demands.At the same time,in information warfare,once a communication system is subjected to deliberate jamming,the normal reception of signals will be affected,and the system will face the risk of reduced reliability.Therefore,it is of great significance to adopt effective anti-jamming technology for communication systems.This thesis mainly studies the interference detection and suppression technology of multi-carrier NOMA system,signal detection technology and its performance under jamming environment.The main work of this thesis includes:Firstly,the thesis introduces the basic principles of NOMA systems,the channel model used in the system,frame structure,and relevant synchronization algorithms.A two-user NOMA link based on OFDM is established,and the basic performance of the OFDM-NOMA link is simulated to verify the feasibility of the system architecture.Secondly,the thesis introduces and models several common types of jamming,including frequency-domain single-tone jamming,narrowband jamming,and timedomain Gaussian pulse jamming.The thesis uses the Consecutive Mean Excision(CME)algorithm and the Forward Consecutive Mean Excision(FCME)algorithm to detect frequency-domain jamming and conduct performance analysis and comparison.Ultimately,the thesis combines the CME interference detection algorithm with methods such as overlapping window and sliding average preprocessing and adopts a zerosuppression interference suppression algorithm to process frequency-domain single-tone jamming and narrowband jamming.The thesis conducts bit error rate(BER)simulation on a single-user OFDM system under frequency-domain jamming.For time-domain Gaussian pulse jamming,the thesis also uses CME detection algorithm and zerosuppression algorithm for processing and uses segment processing and whole segment processing during the detection process.The thesis compares the performance of the two methods using missed detection probability and conducts BER simulation on a singleuser OFDM system under time-domain jamming.Finally,this thesis investigates the key signal detection techniques involved in OFDM-NOMA links under jamming environments,including channel estimation,decoding,and Successive Interference Cancellation(SIC).To mitigate the impact of interference suppression on channel estimation,the thesis employs a method of smooth denoising to improve the performance of channel estimation.To alleviate the impact of interference suppression on decoding,the thesis uses a soft decision-making algorithm to mitigate the degradation of link performance caused by larger jamming bandwidth.To address the impact of interference suppression on SIC,the thesis uses a re-suppression method to avoid introducing additional jamming.Ultimately,by simulating the performance of the entire link under jamming environments,the thesis verifies that the designed OFDM-NOMA link has good anti-jamming performance.