A Network Selection Policy under Delay Constraint and Resource Prediction in Integrated Wireless Systems

doi:10.7652/xjtuxb201402013

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A Network Selection Policy under Delay Constraint and Resource Prediction in Integrated Wireless Systems

更新时间：2025-07-09

- A Network Selection Policy under Delay Constraint and Resource Prediction in Integrated Wireless Systems
- Vol. 48, Issue 2, Pages: 74-79(2014)
- 作者机构：
  
  西安电子科技大学综合业务网理论及关键技术国家重点实验室,西安,710071
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb201402013
  CLC： TN929
- Online First：10 February 2014，
  
  Published：2014
- 稿件说明：
移动端阅览
A Network Selection Policy under Delay Constraint and Resource Prediction in Integrated Wireless Systems[J]. 2014, 48(2): 74-79.
DOI：

A Network Selection Policy under Delay Constraint and Resource Prediction in Integrated Wireless Systems[J]. 2014, 48(2): 74-79. DOI： 10.7652/xjtuxb201402013.

摘要

针对异构无线网络中不同业务的时延限制和网络资源不确定性的问题

提出了一种联合时延限制和资源预测的网络选择(JDPNS)策略。该策略首先预测下一时隙信道资源的空闲概率和占用概率

如果空闲概率大于占用概率

则认为信道资源可以使用

如果空闲概率小于占用概率

则认为信道资源被占用

可以避免盲目接入造成的资源浪费和网络负载不均衡

然后以基于有效容量的信息传输速率作为目标函数

以用户的功率控制作为约束条件

在保障用户服务质量的前提下

采用凸优化理论得到最大化的网络传输速率

最后用户根据预测结果和传输速率两方面因素

选择具有充足带宽资源和最大传输速率的网络进行接入。仿真实验表明:在不同信道衰落条件下

JDPNS策略与注水策略相比

传输速率提高了1倍; JDPNS策略的传输速率更接近已知网络资源空闲情况的速率上界。

Abstract

A joint delay constraint and resource prediction policy for network selection(JDPNS)is proposed to manage the problems caused by delay constraint of different services and resource uncertainty in integrated wireless systems. The probabilities of free and occupation are evaluated which can avoid resource wasting and load unbalancing. When the probability of free is larger than the probability of occupation

the channel resource can be used to transmit. While the probability of free is smaller than the probability of occupation

the channel resource is occupied. Then the transmission rate based on the concept of effective capacity is formulated as an objective function with the constraint of power control. The optimal transmission rate which can provide quality-of-service guarantees is obtained by applying the convex theory. Finally

the user accesses the proper network according to both the prediction result and the transmission rate. Simulation results and comparisons with the water-filling policy show that the JDPNS policy gets about twice the transmission rate in different fading channels

and that the transmission rate achieved by the JDPNS policy is closer to the available upper-bound rate.

关键词

Keywords

references

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