Spectrum Resource Allocation And Spectrum Sharing For Cloud Radio Access Network

Mobile Internet traffic rises more quickly, the expenses for construction, operation, upgrading the radio access network increase continuously, while revenue is increased slowly. The cloud wireless access network is composed with collaborative wireless network and real-time cloud infrastructure. The collaborative wireless network is based on centralized baseband processing pool, composed of the remote radio frequency unit and antenna, and the real-time cloud infrastructure is based on open type platform. C-RAN satisfies the request of low energy consumptions, low cost operating costs and spectrum efficiency improving. The real-time C-RAN can realize dynamic wireless resource allocation and collaborative wireless processing.Spectrum resource for mobile communication system is limited, so it is important to improve spectrum efficiency. In the spectrum allocation algorithms in3GPP, the spectrum resources allocated to each base station is fixed. When the number of users or the position of lots of users in the scene where the base stations distribute is changed, the base stations are always in the condition of overload or under load. The utilization of communications equipment and spectrum resources can’t achieve maximum.Under the background of C-RAN, this paper proposed an algorithm to improve spectrum allocation algorithm. The algorithm provides a method to allocate the spectrum resource to each base station according to the proportion of user number to the total number. Simulation results shows the algorithm achieve more reasonable use of spectrum resources. In addition, this paper proposes an algorithm to select base stations cluster in the cloud wireless access network. The algorithm is mainly based on the distribution of RRU and the cell measurement information of the cell access procedure. The simulation results show that the dynamic spectrum allocation algorithm in this paper improves the performance of the system function significantly. The cluster algorithm proposed in this paper is reasonable and effective. The algorithm reduces energy consumption and improves energy efficiency, and the throughput of the system is improved at the same time.