Intensive-network self-optimizing switching method

Abstract

The invention provides an intensive-network self-optimizing switching method and belongs to the technical field of radio communication. According to the architecture characteristics of intensiveness, hierarchy and amorphism of an intensive heterogeneous honeycomb network and switching characteristics of high frequency and low performance, the intensive-network self-optimizing switching method includes firstly sensing passing-by rate, moving speed, acceptance and idle degrees of a target honeycomb of an MS (mobile station), acquiring of tendency of the MS to the target honeycomb by the passing-by rate and the speed based on FL (fuzzy logic), and acquiring affinity of the honeycomb towards new users by the acceptance and the idle degrees, and self-adaptively adjusting switching parameters based on Q-Learning algorithm by taking tendency and affinity as input and resource utilization rate, call drop rate, switching failure rate and ping-pong switching rate as instant awards, so as to optimize the switching failure rate, the ping-pong switching rate and the call drop rate. Compared with the prior art, the intensive-network self-optimizing switching method can remarkably improve high-switching failure rate, ping-pong switching rate and call drop rate of the MS under the intensive heterogeneous network.

Description

technical field [0001] The invention relates to the technical field of wireless communication networks, in particular to a self-optimizing switching method in an LTE-A dense heterogeneous cellular network. Background technique [0002] In recent years, the demand for mobile data traffic has continued to increase, and network operators have gradually deployed more small cells in LTE-A heterogeneous cellular networks to form dense heterogeneous cellular networks. Small cell is a small-scale coverage network deployed by low-power nodes, which has the characteristics of small shape, flexible deployment, and plug-and-play. There are many types of small cells, mainly including Microcell, Picocell, Femtocell, and small cells covered by relay stations. [0003] Handover management has always been one of the key research directions of radio resource management in LTE-A heterogeneous cellular networks. Low handover performance is an urgent problem to be solved in heterogeneous cellul...

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Problems solved by technology

[0004] The 3GPP TR36.839 agreement pointed out that the handover performance of MS in LTE-A heterogeneous cellular network is lower than that of traditional homogeneous cellular network, and the handover parameters of traditional homogeneous cellular network are no longer applicable to LTE-A heterogeneous cellular network. Cellular network

However, as the LTE-A heterogeneous cellular network gradually develops into a dense small cell deployment architecture, this method will greatly reduce the communication quality QoS received by the MS, and even cause a large number of dropped calls

Because, in a dense heterogeneous cellular network, there are often multiple continuous small cells densely covered in the mobile path of the MS, forcibly preventing the MS from cutting into the small cell will only make its wireless link quality strongly interfered by the small cell for a long time, thus Causes poor communication quality or frequently triggers dropped calls

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