Abstract
Forced termination of connections during handover and blocked connection initiation are annoying from the perspective of multiservice cellular system users. Previous studies have shown that an admission control policy reduces the dropping probability to a much lower level but at the cost of raising the blocking probability to a higher level. As an alternative for reducing both blocking and dropping probabilities, we make use of the Adaptive Multirate (AMR) scheme, which is a well-known real-time streaming coding technique. For an example of AMR technique, a video source is encoded into multiple independent descriptions. A cellular device, depending on its available computing and network resources, joins different descriptions to meet performance requirements. The base layer is received and the enhancement layer(s) are abandoned if the cellular capacity is insufficient for high-quality video. Mobile cellular devices currently obtain basic video quality at a lower frame rate. AMR services can substantially improve the degree of user satisfaction and guarantee the connection-level quality of service (QoS) for different multimedia. In cellular systems, the QoS requirements of different services require a connection admission control (CAC) that limits the number of connections in each access network. Therefore, we focus on the CAC and connection-level QoS of multiservice traffic using adaptive coding in mobile cellular systems. We initially analyzed our CAC policy in a multiservices cellular system by formulating the CAC policy functions, arrival rate, departure rate, blocking probability, and dropping probability of the multiservices, before we derived the connection-level QoS and verified it by simulation. The adaptive coding of multiservices traffic has a significant impact on the connection-level QoS in multiservice cellular systems. Our method decreased the blocking and dropping probabilities by adapting multirate services while users were roaming. Mobile cellular operators providing AMR services could apply our CAC to fulfill the quality requirements of the user experience and also improve the connection-level QoS.
Highlights
We introduced the Connection admission control (CAC) policy functions that were based on the service category and the type of connection request
(1) We evaluated the effect of using a CAC policy, which was supported by adaptive bandwidth for call service in wireless access networks
Mobility and handovers are important factors in cellular systems, so multiservices based on models with user mobility and a CAC policy were considered
Summary
The probability of blocking connection requests for service type s in cell i of new users For each cell i 2 f1; 2; 3; 4g, the CAC policies for connection requests from new and handover users for service type s 2 S can be modeled using the policy functions βnis ðmiÞ and βhhist ðmiÞ , respectively.
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