A Resource Sharing Oriented Service Offloading Method in Dense Heterogeneous Cellular Networks

Abstract

The invention discloses a service unloading method for resource sharing in a dense heterogeneous cellular network. The method comprises the following steps: initializing a network resource state, forming a stable alliance partition for multiple channels, performing frequency spectrum leasing and service unloading in an alliance, and periodically repeating the previous steps by taking network environment change in to consideration at the same time. According to the invention, the service unloading method for resource sharing, provided by the invention, solves the problems of lack of frequency resources and unbalanced server loads existing in the dense heterogeneous cellular network; by taking such performance indexes as network performance, network time delays and the like into consideration, an effectiveness function is designed, a macro-micro base station cooperation framework based on an alliance gaming theory is brought forward, and high-efficiency server unloading can be realized for resource sharing; and the high-efficiency utilization of frequency spectrum resources in the alliance is realized based on the stable alliance partition, and the network overall performance is improved accordingly.

Description

technical field [0001] The invention belongs to the technical field of wireless communication, and in particular relates to a resource sharing-oriented service unloading method in a dense heterogeneous cellular network. Background technique [0002] With the rapid development of mobile communications, the surge in business data demand and the scarcity of spectrum resources have become opportunities and challenges for the future development of mobile communications. However, in the current environment where heterogeneous networks are highly converged and developed, various low-power nodes including Microcells, Femtocells and Relay Nodes are deployed in macrocells (i.e. micro base station) has become one of the key technologies to improve network capacity. Due to constraints such as the coverage of micro base stations and the number of antennas, there are serious problems such as uneven load and low spectrum utilization in the network, which hinders the further deployment of ...

AI Technical Summary

Problems solved by technology

However, the disadvantage of this method is that in dense heterogeneous cellular scenarios, the number of interactions between service providers and the interaction information data need to be large, and it cannot guarantee time-varying wireless data services and dynamic wireless channel fading scenarios. real-time requirements

The shortcomings of this method are: it does not consider the problem of base station performance degradation after the target base station unloads services, and does not take appropriate incentives to promote cooperation between base stations

The disadvantage of this method is that it needs to solve the first-order partial derivative many times in the process of game resource optimization, the calculation is complicated and the convergence speed is slow

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