| Summary: | 博士 === 國立中央大學 === 資訊工程學系 === 104 === The Long Term Evolution-Advanced (LTE-Advanced) is the further version of Long Term Evolution. In LTE-Advanced, relay technique is developed to extend the communication coverage of evolved Node B (eNB) and to increase network capacity by deploying the lightweight eNB as well as relay nodes (RNs). Network providers have investigated network planning for improving system performance and satisfying user requirements with minimal construction cost and most served users for many years, but users always expect to acquire better communication quality. Most existing literatures on network planning in LTE-Advanced merely considered deploying one kind of RNs within an eNB’s coverage. In this thesis, the planning problem of multiple eNBs and two types of RNs is formulated based on mixed integer linear programming and proved as an NP-complete problem. Type 1 RNs are aimed to place in the center of eNB, and Type 1a RNs are deployed at the cell edge of eNB. Three algorithms are proposed to tackle the planning problem of a large-scale LTE-Advanced relay network and analyzed in a planning case and simulation-based results. The goal of the thesis is to maximize the communication quality of all served users with a lower construction cost. The objective function of the thesis is evaluated with the designed cost performance index (CPI) ratio of average Signal-to-Interference-plus-Noise Ratio (SINR) to construction cost. Results show that the proposed Tree with Type 1a RN algorithm minimizes the construction cost of planning result with a significant number of served users, and yields the highest CPI ratio of number of served users over construction costs. However, the Tree with Type 1a RN algorithm does not tackle the placement problem of Type 1 RN. The Tree with Type 1 RN and Type 1a RN algorithm is further proposed to accomplish the deployment work of multiple eNB, Type 1a RNs and Type 1 RNs at the same time. However, it may construct two eNBs that their distance is too close to cause communication interference from the overlapping area with the same carrier. Therefore, the Interference Coordination algorithm is proposed to prevent deploying eNBs with signal interference. The proposed Interference Coordination algorithm not only eliminates the communication interference as well as the highest average SINR value of all served users but also spends the lower construction cost on network planning. In addition, it serves more users than the proposed Tree with Type 1a algorithm and the Tree with Type 1 RN and Type 1a RN algorithm. Furthermore, it yields the highest CPI ratio of average SINR value to construction cost. The proposed Interference Coordination algorithm is convinced that it provides all served users with the best signal quality. Most importantly, it is expected to provide the best communication quality for next generation mobile networks.
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