Q-learning Based Network Selection for WCDMA/WLAN Heterogeneous Wireless Networks

被引：0

作者：

Xu, Yubin ^{[1
]}

Chen, Jiamei ^{[1
]}

Ma, Lin ^{[1
]}

Lang, Gaiping ^{[1
]}

机构：

[1] Harbin Inst Technol, Commun Res Ctr, Harbin 150080, Peoples R China

来源：

2014 IEEE 79TH VEHICULAR TECHNOLOGY CONFERENCE (VTC-SPRING) | 2014年

关键词：

access control; network selection; heterogeneous networks; Q-learning; ADMISSION CONTROL;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper investigates the problem of network selection in access control for heterogeneous networks of WCDMA/WLAN. To optimize the network selection decision policy, an optimization equation is defined with the objective of maximizing the total rewards, and then a new Q-learning Based Network Selection (QBNS) mechanism is proposed to solve the equation. In the QBNS Algorithm, Q-learning algorithm is employed by taking both of the network capacity and the quality of service (QoS) requirements of users into account. In addition, the network states are analyzed by considering interference power of WCDMA subnet and channel busyness ratio of WLAN subnet. Simulation results show that the proposed QBNS scheme can obtain lower call blocking probability and much higher total reward performance than the traditional Semi-Markov Decision Process (SMDP) Algorithm.

引用

页数：5

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