Method for joint optimization of MLB and MRO in LTE network

Abstract

The invention discloses a method for the joint optimization of MLB (Mobility Load Balancing) and MRO (Mobility Robustness Optimization) in an LTE (Long Term Evolution) network. The method comprises the followings steps: a load level is periodically detected by a cell s in the LTE network so as to judge whether the cell is overloaded; when the cell is overloaded, the load information of all neighboring cells is obtained by the cell s, the loads of the neighboring cells are respectively compared with an acceptance threshold, and whether the number n of the neighboring cells of which the loads are respectively lower than the acceptance threshold is 0 is judged, wherein n is an integer; the n neighboring cells are sequentially arranged from light load to heavy load when n is not equal to 0, the cell individual offsets (CIO) of the n neighboring cells relative to the cell s and the hysteresis parameters of the n neighboring cells are respectively obtained, and an array with a length n is established for storing the modified hysteresis parameter value of the cell s; and the CIOm of the arranged mth neighboring cell relative to the cell s is adjusted by the s, and the CIOs of the cell s relative to the mth neighboring cell is adjusted by the m. The method provided by the invention can increase a conversion success rate, balance the load of the network, increase the throughput of the network and improve the performance of the network.

Description

technical field [0001] The invention belongs to the field of wireless communication, and more specifically relates to a joint optimization method of MLB and MRO in an LTE network. Background technique [0002] With the rapid development of communication technologies and services, the scale of wireless networks is getting larger and larger. In order to better meet people's needs, the Long-Term Evolution (LTE) network introduces a home base station (Home eNB), and various technical systems coexist, which makes the network very complicated. If the traditional network planning and optimization method is still used, operators will spend a lot of operating costs, and the efficiency of manual operation of massive network parameters will be reduced, and the network maintenance effect cannot be guaranteed. Therefore, while paying attention to equipment performance, operators will pay more attention to the efficiency of network maintenance and operation. How to reduce OPEX is a probl...

AI Technical Summary

Problems solved by technology

These two solutions can solve the conflict between MLB and MRO to a certain extent, but neither takes user perception into consideration. For example, after the solution is run, the load of the overloaded cell will not be reduced immediately, and the call quality of the voice users will still be reduced. Relatively low, poor user perception

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