Interference management self optimization method based on non-orthogonal multiple access

Abstract

The invention discloses an interference management self optimization method based on non-orthogonal multiple access, and belongs to the field of wireless network. The method comprises the following steps: firstly, in a super dense scene, for a fixed sub-bandwidth, each small base station separately calculates a signal to noise ratio to a respective request user, deletes the adjacent interference base stations of the present base station according to the sensed interference signal intensity of the adjacent base stations, and independently constructs a dynamic local interference map; then, each small base station independently accomplish resource allocation by comprehensively considering the communication demand and the information of the local interference map, in order to reduce the interface among the networks, the interference optimization problem is modeled as a game problem based on satisfaction, a resource allocation result is obtained by using a distributed algorithm, each small base station reasonably allocates different power and sub-bandwidths to respective request users, so that the system interference is maximized. By adoption of the interference management self optimization method, the network interference is reduced, ensures the communication needs of the user is ensured, and the convergence is good.

Description

technical field [0001] The invention belongs to the field of wireless networks, in particular to an interference management self-optimization method based on non-orthogonal multiple access. Background technique [0002] Ultra-dense networking technology can effectively increase network capacity and expand network coverage by deploying low-power small base stations on a large scale in hotspot areas, and has become one of the key technologies of 5G. Ultra-dense networking improves the network throughput by reducing the path loss between the base station and the end user. It not only increases the effective received signal, but also amplifies the interference signal. At the same time, low-power small base stations with different transmission frequencies are deployed overlappingly with the macro base station. The sharp increase in cell density makes interference extremely complicated. How to effectively eliminate interference and coordinate interference has become a key issue t...

AI Technical Summary

Problems solved by technology

However, as the useful signal strength increases, the interference problem caused by adjacent small base stations becomes more complicated. At the same time, considering the deployment of a large number of small base stations, the traditional centralized optimization scheme will generate large signaling overhead, which is no longer applicable; in addition , in order to further improve the...

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