A dynamic channel allocation method based on generic algorithm

Abstract

The invention uses genetic algorithms to realize dynamic channel allocation (DMA). By contrast, a nonlinear method is more suitable for nonlinear characteristics of the reality and for parallel arithmetic, can be flexibly transferred to fit various wireless channel allocation technologies; the invention is additionally characterized that channel performance is collectively estimated and channel resources are equally distributed so as to comparatively improve the comprehensive utilization ratio of the channel resource. The invention adopts carrier frequency, time slot, spread spectrum codes and the angle of wave beam as genomes to realize chromosome coding; the operating procedure is that a sliding window is used for filtering a species group to form a vector X which equals (CF3, C, F2, CF1, CF0, TS2, TS1, TS0, SF3 ,SF2, SF1, SF0, BS2, BS1, BS0), and then the genetic algorithms, such as hybridization, variation, etc., are selected to realize the dynamic allocation and optimization of the channel.

Description

technical field [0001] The invention relates to the field of wireless communication, in particular to a method for dynamically allocating channels based on genetic algorithms in wireless communication. Background technique [0002] Channel allocation method in wireless communication network is the main measure to improve the capacity of wireless network. Channel allocation is determined by the joint allocation of carrier frequencies in the frequency domain, time slots in the time domain, code domain spreading codes, and beam angles in the space domain, while maximizing network capacity while meeting communication quality requirements. [0003] In order to expand the capacity of the wireless network, a dynamic channel allocation method is usually adopted. The characteristic of dynamic channel allocation is that the cell has no fixed channel allocation. When there is a call request, the system adopts a certain strategy to allocate a channel from the channel combination. As l...

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Problems solved by technology

[0004] However, these dynamic channel allocation methods are characterized by business-based linear methods, which fail to fully consider that the actual communication environment may be nonlinear environments such as construction areas, water areas, and hills; the communication process is also affected by multipath transmission, Rayleigh attenuation, and multispectral It is difficult to predict the position parameters due to influences such as Le effect; the principle of optimal performance and time priority may also make some link requests unable to be allocated to channels due to missed time; moreover, the channel resources obtained by most links are not optimal. Reasonable, such as excess channel capacity, stop using strong interference channels, etc., resulting in waste of some channel resources, which may affect other links lost or even rejected

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