Research On Self-optimization Technologies Of LTE Femtocell Network

Femtocell is defined as a mini-basestation subsystem following the trend of broadband mobilization. The main task of femtocell is to provide better signal coverage and QoS indoors or other specific scenarios.In respect to the self-optimizing and anti-interference problems, the following two aspects are discussed in this thesis:First, a neighbor cell list optimizing method in femtocell scenarios is proposed to make up for a deficiency of existing algorithms. This method take special considerations about registered users in closed access mode femtocell to guarantee their data services. This method can increase the system capacity and at the same time decrease the outage rate of whole system.Second, a coverage optimization algorithm based on the Multiple Attribute Decision Making (MADM) is proposed to optimize the radio coverage area of LTE femtocell two-layer network in enterprise deployment. Considering some basic requirements of coverage, including coverage holes, coverage overlaps, area spectral efficiency (ASE) and load balancing, the coverage optimization problem is modeled as a MADM problem. Then the MADM-based coverage optimization problem is solved by the Gray relation analysis (GRA) method. Simulation results show that the proposed scheme can achieve a better ASE performance and effectively balance the traffic load amongst all femtocells, as well as obtaining a good tradeoff between coverage holes and coverage overlap.