Power allocation of femtocells

With the implementation of the LTE/LTE-A system, the proportion of indoor high-speed data services in the communication business is growing, which puts forward even higher standards for the indoor coverage and system capacity of mobile communication systems. The frequency band of LTE/LTE-A system deployment is mainly distributed in the high-frequency band and the attenuation of high-frequency signals through the walls of buildings is worse than that of low-frequency signals, leading to the increase of indoor weak coverage and blind coverage. Deploying several femtocell base stations in a traditional macro-cellular network can effectively improve the indoor coverage quality of the traditional macro-cellular network. Due to the shortage of spectrum resources, the femtocell base stations and the macrocell base stations are deployed in the same frequency band, which will bring serious interference to the macro-cellular network and reduce the performance of the two-tier network. Therefore, it is necessary to study the interference management of the two-tier network. The cognitive radio technology can improve the low spectrum utilization of femtocell base stations effectively. In this dissertation, the femtocell technology and the cognitive radio technology are combined effectively and the problem of interference suppression is studied based on resource allocation in the coexistence of the cognitive femtocell base station and the macro-cellular network. Existing algorithms that recognize spectrum-aware resource allocation in femtocell base stations basically ignore the imperfect spectrum-sensing factors, and it is difficult to achieve in practice. In this dissertation, the novel network resource allocation scheme is proposed for the cognitive femtocell network based on an imperfect spectrum sensing method. The target of this algorithm is to maximize the sum throughput of all femtocell users under the quality-of-service constraints of both femtocell users and macro communication using the channel and power allocation method.Master of Science (Communications Engineering