Distributed intelligence call acceptance control method and device

Abstract

Disclosed a intelligent calling receiving control method based on the distributed design and its relative device, comprises four modules: a fuzzy equivalent interference evaluator, a neural network interference predictor, a actual system performance feedback module and a fuzzy calling receiving processor. The invention selects the fuzzy logic to evaluate the equivalent interference according to the service character of new users; using the neural network technique predictor to predict the total interference level of connected user at next time; measuring the lost probability of voice and data service of local section and adjacent sections at present time as the system feedback; the fuzzy calling receiving controller operates the receiving judgment according to aforementioned factors. The invention imports the distributed design into the intelligent calling receiving control method, submits the conception of equivalent lost probability of adjacent sections, synthesized measures the effect of calling receiving control from the adjacent user QoS on local section, to assure the receiving of new calling will not reduce the service quality of local and adjacent sections.

Description

technical field [0001] The present invention relates to a call admission control method (CAC), in particular to a distributed intelligent call admission control method (DICAC: Distributed Intelligent Call Admission Control) and a device based on distributed thinking, belonging to the field of communication system resource management. Background technique [0002] Call admission control methods are under development. At present, there are three main categories of research on call admission control schemes in CDMA cellular communication systems: one is the CAC algorithm based on SIR or total interference signal power; the other is the CAC algorithm based on the system capacity analysis model; the third is based on CAC algorithm for power control model. However, these algorithm studies are either limited to single service systems, or do not consider the multi-cell Quality of Service (QoS) requirements at the same time. [0003] Chang Chung-Ju in his article "Intelligent Call ...

AI Technical Summary

Problems solved by technology

However, this algorithm has the following disadvantages: only the QoS requirements of the users in the current cell are considered in the decision, and the influence of the congestion status of the adjacent cells on the admission decision of the cell is ignored

In fact, due to the microcell or picocell structure of the cell, handover occurs frequently. If handover occurs after the user accesses the network, whether the cell can provide the user with available resources, and whether the user's handover will cause the cell service Decreased quality is also an important issue that should be considered

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