Accumulation and Elimination: A Hard Decision-Based Multi-User Interference Cancellation Method in Satellite Communication System  
[PERSON]  
1 School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China; 1 [EMAIL_ADDRESS] (H.L. ); [EMAIL_ADDRESS] (Y.J. ); [EMAIL_ADDRESS] (K.Y)  
[PERSON]  
1 School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China; 1 [EMAIL_ADDRESS] (H.L. ); [EMAIL_ADDRESS] (Y.J. ); [EMAIL_ADDRESS] (K.Y)  
[PERSON]  
3 School of Cyberspace Science and Technology, Beijing Institute of Technology, Beijing 10008  
system capacity for the increasing number of users and the limited spectrum resources. Due to these advantages, the MEO communication system has proven to be successful when ground communications services fail or cannot reach. For example, in pelagic fishery, earthquake rescue, forest fire monitoring, location monitoring of international flights, or unmanned aerial vehicles (UAVs) [2; 3; 4]. However, with the increase in the number of users, the concern for multi access interference (MAI) becomes more compelling within DS-CDMA systems [5]. MAI exists when a weak received signal is interfered with by one or more strong signals as expounded in [6; 7]. As a result, the effective cross-correlation among signals weaken the communication capability of the up-link satellite receiver, which is shown in Figure 1. Despite the insignificant effect that an individual user may have on others, the proliferation of synchronous signals amplifies the impact of MAI, thereby considerably impacting communication stability significantly. We must highlight that current acquisition algorithms cannot solve the MAI problem [6], thus illuminating the requirement for innovative solutions. In DS-CDMA systems, the signals of all users overlap in both time and frequency dimensions. Conventional DS-CDMA systems follow a single-user detection strategy, where users are detected by correlating the received signals with the local pseudo-noise (PRN) codes through a specific filter, known as the matched filter method [8; 9]. In reference [10], [PERSON] presented a method to capture weak signals in the presence of strong interference, irrespective of signal power, noise power, and jamming power. In reference [11; 12], they considered methods to eliminate narrow-band interference as well as broad-band interference to improve acquisition performance. In reference [13], the proposed algorithm decreases the false alarm probability through the decision of the ratio of the maximum value and the second maximum value of the correlation results. However, none of the aforementioned methods took MAI into consideration. MAI greatly affects the individual detection results. In reference [14], multi-user detection algorithms (MUD) were introduced as a promising solution to address this problem. In reference [15], [PERSON] proposed a class of suboptimal detectors based on the minimization of the mean square error (MMSE) or the weighted-squared-error performance criterion. Although these detectors perform nearly as well as the optimal detector, their utilization is hindered by the impracticality of real-time matrix inverse operations [16]. To mitigate the computational complexity, interference-canceling multi-user detection algorithms have been developed and put forward. As discussed in [17; 18; 19], serial interference cancellation (SIC) possesses the capability to eliminate not only the signals transmitting from other users within the same communication system but also the pernicious narrow-band interference. Nevertheless, the SIC algorithm demands a significant level of power control, and its serial nature cannot meet the real-time acquisition requirements. In reference [20],  
Figure 1: The up-link of the multi-user system. the multi-stage parallel interference cancellation (PIC) algorithm concurrently analyzes all MAI for simultaneous cancellation, which can additionally be cascaded for utmost optimization.