Research On Spectrum Allocation Strategies Based On Different Spectrum Sharing Methods

The widespread adoption and application of mobile Internet technology has led to the explosive growth of the traffic carried by the wireless communication systems, and it is imperative to improve the capacity of the wireless communication systems. However, the spectrum resource, as a type of limited resource, has been unable to meet the growing spectrum demand as it is constantly being allocated. At present, the spectrum resource is mainly allocated in a fixed distribution mode, and in this mode, the spectrum resource is often not fully utilized, resulting in low utilization rate of licensed spectrum. The emergence of cognitive radio technology makes it possible to share licensed spectrum, thereby improving spectrum utilization and mitigating the contradiction between the spectrum resource shortage and growing spectrum requirements. The spectrum resource of cognitive radio system has multiple attribute characteristics, and the maximum spectrum efficiency can be obtained by the best matching of the attributes of frequency spectrum and the user's service requirements. Therefore, how to realize the effective allocation of spectrum resource is an important issue for cognitive radio systems to share licensed spectrum.On the other hand, unlicensed spectrum sharing has also become an effective way to alleviate the problem of spectrum resource shortage. Unlicensed spectrum is an open spectrum resource, which does not belong to a certain type of systems. Therefore, it is an important part of the research on unlicensed spectrum sharing to ensure fair coexistence among different systems. In addition, the use of unlicensed spectrum resource needs to deal with complex interference situation. Solving interference is the key issue of unlicensed spectrum resource allocation, which will directly affect the system throughput and spectrum utilization.This thesis focuses on the spectrum allocation strategies based on spectrum sharing,including the following two aspects:1. Based on opportunistic spectrum sharing scenarios, a spectrum allocation strategy that can effectively match the attributes of spectrum and user needs is studied. Different from the traditional spectrum allocation considering only a single performance requirement, the spectrum allocation strategy for cognitive users takes into account the multiple service requirements, and designs the unified utility function to integrate it as an index to evaluate the utility of the spectrum to cognitive users. Considering the fairness among users, we introduce the fair weighting factor, and then establish the spectrum allocation optimization model and study the corresponding spectrum allocation algorithm. The simulation results show that the spectrum allocation strategy can effectively balance the spectrum utility and the fairness between users.2. An effective spectrum allocation strategy is studied to reduce the system interference and improve the throughput of the system based on the LTE-U Vehicle Platoon network sharing the spectrum of WiFi. Firstly, we analyze the co-channel and adjacent channel interference of unlicensed spectrum, and establish a unified interference model.Then, we map the interference relation between Vehicles with the interference model to obtain the interference of the whole network. Considering the interference relation, the spectrum allocation strategy effectively isolates the channel in geographical distance and frequency domain to avoid interference. The simulation results show that the proposed spectrum allocation strategy can effectively reduce the interference inside the system and improve the system throughput.