On The Key Technologies Of Network Optimiza-Tion For Inter-cell Interference Suppression

Network optimization is to reconfigure resources and parameters of a cellular network according to the external environment, such as radio propagation conditions, traffic distri-bution, user distribution, user behavior characteristics (e.g. tidal migration) and equipment running status. It ensures that the cellular network can continuously and stably provide a variety of mobile communication services to the users. TD-SCDMA is the third gen-eration mobile communication technology standard proposed by China, and a large-scale TD-SCDMA network has being operating in Chinese mainland. However, its network op-timization technology is not yet mature. The inter-cell interference in TD-SCDMA net-works is a serious problem and has become one of the main factors affecting network performance. In this dissertation, three key cellular network optimization techniques for inter-cell interference suppression are investigated, including scrambling code assignment, frequency assignment and coverage optimization.The scrambling code assignment (SCA) in TD-SCDMA is systematically studied. A proper inter-cell interference model is first established, where interference generation mechanism in the physical layer, radio propagation conditions and traffic distributions all are taken into consideration so that the interference is accurately modeled. Then the defi-nition and mathematical formation of complex-valued spreading code, as well as its cross correlation functions are discussed in detail. Furthermore, a concept of scrambling code family is proposed and the Interference Equivalence Theorem is proved. Based on the the-orem, SCA problem can be simplified into two subproblems, including scrambling code family assignment (SCFA) and scrambling code selection (SCS), whose computational complexities are much less than that of the original problem. The SCFA problem is mod-eled as a0-1quadratic programming and then solved. As to SCS, the existence of the solution is proved and a greedy algorithm is proposed to solve this subproblem. Besides, a method of calculating the interference-to-signal ratio (ISR) matrix from the measurement report data is developed to ensure that the algorithm is applicable to a practical network. Numerical results show that our algorithm can achieve a much lower inter-cell interference than those of the existing algorithms.For frequency assignment (FA), our research focus is on the generation of interference matrix (IM) because IM is the basis of FA. IM is employed to describe the potential inter-ference intensity between any two cells in a cellular network, so that its accuracy has direct influence on the performance of FA. Unfortunately, neither measurement report (MR) data nor drive test (DT) data, which are the data used to generate a IM, contains complete net-work information. In order to generate a more accurate IM, our idea is to make a data fusion from MR data and DT data to obtain a new data containing complete network information. A concept of Carrier-to-interference Spectrum (CIRS) is proposed, and then the coverage of a cell is split into several characteristic regions through clustering analysis of the CIRS derived from DT data. Multiple linear regression analysis is carried out, and the resulted regression model establishes an association between the MR data and DT data in every characteristic region. Based on this model, two data fusion algorithm are proposed. One is to reinforce MR data using the frequency-domain information of DT data. The other is to reshape DT data using the traffic distribution information extracted from MR data. Compared with the MR data and DT data measured from a practical network, the fused data indeed contains more complete information which validates the effectiveness of our algorithm. The algorithm has been integrated into a commercial network optimization soft-ware, and has been utilized for the FA in three cities of Zhejiang province. The results are quite satisfactory.Good coverage of the common broadcasting signals (e.g. pilot) is the basis to provide seamless access. A novel coverage optimization model based on multi-sector joint beam-forming is proposed. In the model, poor coverage is eliminated through joint beamforming of several neighboring sectors in the "region to be optimized" under the constraint that no new poor coverage raises in the "region of first ring neighboring sectors", and the inter-ference to the surrounding sectors is minimized through minimization of the total transmit power. Furthermore, a heuristic algorithm is developed based on the iteration of sector coverage updating and antenna array excitation weights optimization. Compared with the existing joint power adjusting algorithm, our algorithm can achieve a much higher carrier-to-interference ratio with a much lower transmit pilot power.