A QoS Provisioning Recurrent Neural Network based Call Admission Control for beyond 3G Networks

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Abstract The Call admission control (CAC) is one of the Radio Resource Management (RRM) techniques that plays influential role in ensuring the desired Quality of Service (QoS) to the users and applications in next generation networks. This paper proposes a fuzzy neural approach for making the call admission control decision in multi class traffic based Next Generation Wireless Networks (NGWN). The proposed Fuzzy Neural call admission control (FNCAC) scheme is an integrated CAC module that combines the linguistic control capabilities of the fuzzy logic controller and the learning capabilities of the neural networks. The model is based on recurrent radial basis function networks which have better learning and adaptability that can be used to develop intelligent system to handle the incoming traffic in an heterogeneous network environment. The simulation results are optimistic and indicates that the proposed FNCAC algorithm performs better than the other two methods and the call blocking probability is minimal when compared to other two methods. Keywords: Radio resource management, Heterogeneous wireless Networks, Call admission control, Call blocking probability, Recurrent radial basis function networks.

1. Introduction The majority researchers believe that the next stage beyond third-generation(3G) networks will include multiple wireless access technologies, all of which will coexist in a heterogeneous wireless access network environment[1,2] and use a common IP core to realize user-focused service delivery. The coexistence of Heterogeneous radio access technologies (RATs) will noticeably amplify the intensity different in development of different high-speed multimedia services, such as video on demand, mobile gaming, Web browsing, video streaming, voice over IP and e-commerce etc. Seamless inter system roaming across heterogeneous wireless access networks will be a major feature in the architecture of next generation wireless networks [3]. The future users of mobile communication look for always best connected (ABC) anywhere and anytime in the Complementary access technologies like Wireless Local Area Networks (WLAN), Worldwide Inter operability for Microwave Access (Wi-Max) and Universal Mobile Telecommunication Systems (UMTS) and which may coexist with the satellite networks [4- 6].It is very well evident that no single RAT can provide ubiquitous coverage and continuously high quality service. The mobile users may have to roam among various radio access technologies to keep the network connectivity active and to meet the applications/users requirements. With increase in offered services and access networks, efficient user roaming and management of available radio resources becomes decisive in providing the network stability and QoS provisioning.
   The mobile communication networks are evolving into adaptable Internet protocol based networks that can handle multimedia applications. When multimedia data is supported by wireless networks, the networks should meet the quality of service requirements. One of the key challenges to be addressed in this prevailing scenario is the

A QoS Provisioning Recurrent Neural Network based Call Admission Control for beyond 3G Networks

Ramesh Babu H.S.1, Gowrishankar2, Satyanarayana P.S3.

1Department of Information Science and Engineering,
Acharya Institute of Technology Bangalore, INDIA

2Department of Computer Science and Engineering,
B.M.S. College of Engineering,
Bangalore, INDIA

3Department of Electronics and Communication Engineering,
B.M.S. College of Engineering,
Bangalore, INDIA

IJCSI International Journal of Computer Science Issues, Vol. 7, Issue 2, No 5, March 2010 ISSN (Online): 1694-0784 ISSN (Print): 1694-0814

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distribution of the available channel capacity among the multiple traffic ensuring the QoS requirements of the traffic that are operating with different bandwidth requirements. There are many call admission control(CAC) algorithms proposed in the literature to handle single-class network traffic such as real-time traffic like voice calls [7-10].To serve the multiple classes of traffic we have the Partitioning CAC [11][12] and threshold based CAC [13] .The paper proposes the CAC framework for multi traffic based heterogeneous wireless networks . The resource allocation is a challenging task when the resources are always in scarce in a wireless environment.
Efficient and intelligent call admission control policies should be in place which can take care of this contradicting environment to optimize the resource utilization. There are works reported on computation intelligence based call admission control algorithms. These algorithms admit or reject the call by applying comp

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