Dissertation > Industrial Technology > Radio electronics, telecommunications technology > Wireless communications > Mobile Communications

Research on Self-Organizing Networks in LTE-A Heterogeneous Networks

Author MaChuan
Tutor YuGuanDing
School Zhejiang University
Course Information and Communication Engineering
Keywords Heterogeneous network Self-organizing network Cooperative communication Load balancing Handover decision
CLC TN929.5
Type Master's thesis
Year 2012
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In order to enhance the network coverage, and increased network capacity, LTE-A proposes a series of low power nodes to form a multi-layer cellular network, i.e. the heterogeneous network deployed at the macrocell. Later be deployed in accordance with the heterogeneous network mode, the LTE-A network structure will become more large and complex. If the network operator is still artificial network planning and network optimization, will cause a dramatic increase in costs. Therefore, the introduction of LTE-A concept of a self-organizing network aims to improve the self-organizing capacity of the network to reduce network infrastructure costs and operating expenses. In this paper, the different types of heterogeneous networks, select 3 SON use cases to study. The first use case is the eNB-HeNB coverage Femtocell UE network cooperation between the communication mechanism. ENB-HeNB covering a total network as a cognitive radio network, and to improve the system throughput and fairness target HeNB network RCP strategy that joint relay selection, channel selection and power allocation strategy proposed a low complexity heuristic algorithm - node grouping algorithm. The algorithm is able to increase the average throughput of HeNB network, while improving the fairness among users. The second use case eNB-RN the total overlay network downlink load balancing problem. In this paper, the characteristics of a self-organizing load balancing scheme RSPC-RL. In the proposed scheme, each relay node by adjusting the reference signal power to change the coverage, thereby adjusting the distribution of load on the network. The same time, the program introduces a reinforcement learning algorithm, the relay node can independently obtain the optimal reference signal power control strategy. The algorithm has the characteristics of distributed, low complexity, high performance, it is applied to the actual multi-hop cellular networks. The third use case is the eNB-RN-HeNB covering interlayer network switching problem. In this paper, based resides probability and switching priority switching scheme, can effectively reduce the frequent and unnecessary handover. The core idea of ??the proposed program is: lower threshold UE cut Femtocell UE resides in Femtocell probability, to reduce redundant switching; improve UE UE resides in Femtocell probability cut the Femtocell threshold, in order to reduce unnecessary switching. The proposed algorithm is able to maintain essentially the same rate of dropped calls, a significant reduction in the number of UE switch.

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