Analysis of resource splitting scheme with cognitive based admission control for femto-WiFi wireless networks

被引:3
|
作者
AlQahtani, Salman A. [1 ]
机构
[1] King Saud Univ, Dept Comp Engn, Coll Comp & Informat Sci, Riyadh, Saudi Arabia
关键词
Analytical modeling; Connection admission control; Femtocell Integration; Loss probability; Throughput;
D O I
10.1007/s11276-014-0744-8
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The coexistence of femtocell and WiFi networks in a heterogeneous spectrum environment with licensed and unlicensed bands will support multi-mode femtocell users (FUs) to simultaneously transmit on both licensed and unlicensed bands. The efficient integration of both femtocell and WiFi technologies is seen as crucial for supporting the offloading of femtocell traffic to WiFi networks. To successfully deploy these integrated technologies, the overall licensed and unlicensed spectrum usage must be efficiently managed. Thus, we propose a new cognitive-based connection-level admission control with access retrial for a femtocell network that operates under a mixed spectrum of unlicensed and licensed bands. By deploying cognitive radio concepts, the FUs will utilize the unused spectrum of the existing unlicensed spectrum of the WiFi network in an opportunistic manner in addition to using the licensed spectrum. By using the retrial phenomenon policy, the blocked FUs can retry the access, which can reduce their loss probability. An analytical model using a three-dimensional continuous time Markov chain with a level-dependent quasi birth-and-death structure was developed to evaluate and study the performance of the proposed scheme. The matrix analytic method was used to obtain the steady state probability and performance measures. The result shows that the performance of FUs for integrated femtocell-WiFi networks using the proposed scheme significantly improved in terms of FUs throughput and loss probability. The results also show that the retrial phenomenon of FUs enhances their performance.
引用
收藏
页码:2307 / 2317
页数:11
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