According to the suggestions put forward by the International Telecommunication Union (ITU), the terrestrial and GSO satellite communication systems possess priority over the NGSO satellite systems in the utilization of spectrum resources. Thus, from the perspective of interference, the already-built terrestrial and GSO satellite communication systems and the NGSO satellite systems can be regarded as primary and secondary systems, respectively. The primary system can use spectrum resources without any constraint, while the secondary system ought to use them without significant effect on the primary system in cases in which the same spectrum resources are utilized. GSO satellites have a relatively long history of being utilized for communication. The almost complete analysis of interference scenarios between them has been constructed to achieve interference mitigation. By contrast, the position and velocity of NGSO satellites constantly change, so the interference variables change with time and space, bringing about new challenges for the design of NGSO satellite constellations. In order to mitigate the co-frequency interference that results from NGSO satellite constellations, the ITU has carried out studies in advance about related techniques and proposed a series of mitigation strategies in its recommendations. The traditionally used methods include spatial isolation, time isolation, and so on. There are many published academic papers focusing on the mitigation of interference and elevation of performance in various communication systemsby now. [PERSON] et al. [20] provided basic orbital and interference theories between the satellite systems in NGSO. [PERSON] et al. [21] offered a spectrum sharing optimization method in the constellation design for NGSO broadband satellite systems. [PERSON] et al. [22] proposed a fast calculation method based on the occurrence probability of satellite in the visible zoom. [PERSON] et al. [23] offered a comparison of the architecture of three large constellations of satellites in NGSO and provided methods to determine the number of ground stations and gateways and to estimate the total system throughput. [PERSON] et al. [24] compared the beam coverage design of the OneWeb system with the SpaceX system and evaluated the performance of both systems. [PERSON] et al. [25] provided an adaptive beam power control method to mitigate the interference between multi-beam GSO and NGSO communication systems. [PERSON] et al. [26] focused on the fractional programming theory and applied it to design the communication systems so as to obtain the maximum transmission data rate. [PERSON] et al. [27] presented a dynamic channel allocation (CA) method based on deep reinforcement learning in multi-beam satellite systems which can effectively lower the blocking probability. [PERSON] et al. [28] proposed a novel cognitive beamhopping satellite system in spectrum coexistence of multi-beam satellites. [PERSON] et al. [29] offered a modified Q-learning method based on a greedy algorithm for NGSO networks to lift the performance in spectrum-sharing scenarios with GSO and terrestrial networks. [PERSON] et al. [30,31] provided a spectrum sharing method for cognitive GSO and NGSO satellite networks based on dynamic frequency allocation. The NGSO beams were divided into several clusters based on a seven-beam frequency reuse pattern, and the allocation scheme was implemented in each cluster. The current work aims to develop a channel allocation method to mitigate the co-frequency interference involved with the NGSO satellites equipped with multi-beam antennas. There are two main contributions in this paper. Firstly, the mathematical relationship between the off-axis angle and beam distance is derived. For different beams in the satellites with multi-beam antennas, the same distance may stand for different off-axis angles with significantly different values. Therefore, the revised distance is introduced to reflect the off-axis angle better using beam distance.