Interference Suppression Algorithm And Resource Allocation Scheme Based On LTE-A System

To support the growing demand for high-speed multimedia applications, the3rd Generation Partnership Project (3GPP) creates the Long Term Evolution (LTE) cellular system. With the ambition of exceeding the performance, LTE-A is introduced with the intention of outperforming the specifications defined by IMT-Advanced in3GPP Release10. However, LTE-A still has a series of challenges, such as the interference rejection, wireless resource utilization, etc., which are always the research hotspots. In this thesis, the interference rejection techniques and resource allocation strategies are studied. The main contents are as follows.Firstly, this thesis studies the interference rejection algorithms under the multi-cell and multi-user scenario. Within each cell there is lots of base stations that can be coordinated to serve the users. In order to restrain the interference and also reduce coordination overhead, we consider base station clustering so that each user is served by only a small number of base stations. Thus, our objective is to jointly perform the base station clustering and beamformer designing. This thesis proposes the SLNR based objective function, and then jointly performs base station clustering and beamformer designing based on SLNR. The simulation results have shown that the proposed joint optimization algorithm in this thesis restrains the interference, and performs better than the traditional algorithm both in system throughput and signaling overheads. Compared with the existing joint optimization algorithm, the complexity and signaling overheads of the proposed algorithm are lower with a relatively low performance loss. Secondly, this thesis studies the resource allocation strategies under the distributed and centralized small cell scenarios with channel estimation error, and studies the influence of different channel estimation errors on the resource allocation strategies. Then an iterative power allocation algorithm considering the channel estimation error is proposed. The simulation results have shown that the system capacity is lower in both scenarios with channel estimation error, compared with the perfect channel estimation. The greater the channel estimation error, the more system channel capacity to reduce. Compared with the distributed small cell scenario, the channel estimation error has less influence on the algorithm in centralized small cell scenario.The main contributions and innovation of the thesis are as follows. The interference rejection algorithm proposed in this thesis not only improves the system capacity but also reduces the signaling overheads and algorithm complexity, which is more practical. Finally we study the iterative power allocation algorithm considering the channel estimation error under the distributed and centralized small cell scenarios, and the influence of different channel estimation errors on the algorithm.