Investigation Of Multiple Access Interference Cancellation Algorithm For FFH/MFSK Communication System

Frequency hopping (FH) communication is one of the popular spread spectrum techniques. In frequency hopping system, the carrier frequency of transmission signal is controlled by the pseudo-random sequence in order to improve the anti-jamming ability of the system. Frequency hopping communication system have many advantages, such as frequency diversity, low probability of intercept and multiple access ability, which makes it has been widely used in military and civilian communications. However, due to all users in the system share the same frequency band, the multiple access interference (MAI) between users becomes an important factor to limit system performance. Reducing or eliminating MAI is one of the effective schemes to increase network capacity and system performance. In this thesis, the multiple access interference cancellation algorithms for FH system are investigated.Firstly, the related knowledge of FH communication system and the fast frequency hopping/Multiple frequency shift keying (FFH/MFSK) system model are introduced. Secondly, the multiple access interference problem in FFH/MFSK system is analyzed. Finally, two classical MAI cancellation algorithm, i.e., co-channel interference elimination (MKI) algorithm and iterative interference cancellation (IIC) algorithm, together with some other related algorithms are discussed. After a survey of these algorithms, some improved schemes are proposed.MKI algorithm is a maximum-likelihood scheme. The candidates matrix which are generated from the combination of all users’symbols are compared with the received matrix in order to estimate a pattern of all users’data symbols which has the most number of coincident entries. The combination number increase dramatically with the number of user growing. The calculation complexity is very high. A sub-group MKI algorithm has been proposed by some scholars. The calculation complexity is reduced by group joint detection of all users. However, the random grouping method is not effective when more ambiguity users are assigned into a group. Then, a grouping method based on sorting is presented in this thesis to avoid this problem. The simulation results show that the improved algorithm can reduce the system complexity.IIC algorithm is an iterative detection algorithm. The detected users’ information is used to eliminate the interference to other users in each iterative processing. The computation complexity is linearly proportional to the number of users. An idea of soft decision method instead of hard decision proposd by some scholars is used to receive energy matrix in the algorithm. Although the performance of system is promoted, the problem of error propagation is not solved yet. Based the problem, the method of constant-weighted is presented in this thesis. The simulation results show that the improved algorithm can enhance system performance.