Adaptive Predictive Handoff Scheme with Channel Borrowing in Cellular Network

Previously, we presented an extension of predictive channel reservation (PCR) scheme, called HPCR_CB, for handoff motivated by the rapid evolving technology of mobile positioning. In this thesis, the author proposes a new scheme, called adaptive PCR_CB (APCR_CB), which is an extension of HPCR_CB by incorporating the concept of adaptive guard channels. In APCR_CB, the number of guard channel(s) is adjusted automatically based on the average handoff blocking rate measured in the past certain time period. The handoff blocking rate is controlled under the designated threshold and the new call blocking rate is minimized. The performance evaluation of the APCR_CB scheme is done by simulation. The result shows the APCR_CB scheme outperforms the original PCR, GC, and HPCR_CB schemes by controlling a hard constraint on the handoff blocking probability. It is able to achieve the optimal performance by maximizing the resource utilization and by adapting to changing traffic conditions automatically

Adaptive Predictive Handoff Scheme with Channel Borrowing in Cellular Network

Previously, we presented an extension of predictive channel reservation (PCR) scheme, called HPCR_CB, for handoff motivated by the rapid evolving technology of mobile positioning. In this thesis, the author proposes a new scheme, called adaptive PCR_CB (APCR_CB), which is an extension of HPCR_CB by incorporating the concept of adaptive guard channels. In APCR_CB, the number of guard channel(s) is adjusted automatically based on the average handoff blocking rate measured in the past certain time period. The handoff blocking rate is controlled under the designated threshold and the new call blocking rate is minimized. The performance evaluation of the APCR_CB scheme is done by simulation. The result shows the APCR_CB scheme outperforms the original PCR, GC, and HPCR_CB schemes by controlling a hard constraint on the handoff blocking probability. It is able to achieve the optimal performance by maximizing the resource utilization and by adapting to changing traffic conditions automatically

Reduce the probability of blocking for handoff and calls in cellular systems based on fixed and dynamic channel assignment

In cellular systems the high probability of blocking represents a big problem for users, The proposed solution by reducing the blocking probability and investigation cellular systems by method channels assignment. The aim from apaper is studying the effect the channel assignment on the value of blocking probability. The results showed that the fixe channeld assignment gives a large probability of blocking for high loads, While  (FCA) reduce probability of blocking for handoff and calls according to cluster size. The cellular system representation in the case of (DCA), in (3-cell reuse) and (7-cell reuse), the results showed the first best way to reduce blocking probability and lead to reduce to approximately zero when loads that are less than 200%. Increasing  the cluster size causes to reduce blocking  probability. the results showed that the probability blocking for handoff  less than from probability of  blocking for new calls

3D Transition Matrix Solution for a Path Dependency Problem of Markov Chains-Based Prediction in Cellular Networks

Handover (HO) management is one of the critical challenges in current and future mobile communication systems due to new technologies being deployed at a network level, such as small and femtocells. Because of the smaller sizes of cells, users are expected to perform more frequent HOs, which can increase signaling costs and also decrease user's performance, if a HO is performed poorly. In order to address this issue, predictive HO techniques, such as Markov chains (MC), have been introduced in the literature due to their simplicity and generality. This technique, however, experiences a path dependency problem, specially when a user performs a HO to the same cell, also known as a re-visit. In this paper, the path dependency problem of this kind of predictors is tackled by introducing a new 3D transition matrix, which has an additional dimension representing the orders of HOs, instead of a conventional 2D one. Results show that the proposed algorithm outperforms the classical MC based predictors both in terms of accuracy and HO cost when re-visits are considered

Dynamic Channel Allocation in Mobile Multimedia Networks Using Error Back Propagation and Hopfield Neural Network (EBP-HOP)

AbstractIn mobile multimedia communication systems, the limited bandwidth is an issue of serious concern. However for the better utilization of available resources in a network, channel allocation scheme plays a very important role to manage the available resources in each cell. Hence this issue should be managed to reduce the call blocking or dropping probabilities. This paper gives the new dynamic channel allocation scheme which is based on handoff calls and traffic mobility using hopfield neural network. It will improve the capacity of existing system. Hopfield method develops the new energy function that allocates channel not only for new call but also for handoff calls on the basis of traffic mobility information. Moreover, we have also examined the performance of traffic mobility with the help of error back propagation neural network model to enhance the overall Quality of Services (QoS) in terms of continuous service availability and intercell handoff calls. Our scheme decreases the call handoff dropping and blocking probability up to a better extent as compared to the other existing systems of static and dynamic channel allocation schemes

Client-based SBM layer for predictive management of traffic flows in heterogeneous networks

In a heterogeneous networking environment, the knowledge of the time before a vertical handover (TBVH) for any network is vital in correctly assigning connections to available channels. In this paper, we introduce a predictive mathematical model for calculating the estimated TBVH component from available network parameters and discuss the different scenarios that arise based on a mobile host’s trajectory. We then introduce the concept of an intelligent Stream Bundle Management Layer (SBM) which consists of a set of policies for scheduling and mapping prioritised traffic streams on to available channels based on their priority, device mobility pattern and prevailing channel conditions. The layer is also responsible for the maintenance of connections during vertical handovers to avoid their forced termination

A hierarchical channel selection scheme for macro/micro cellular networks

Hierarchical channel allocation schemes for cellular networks offer a promising approach to solve the pressing problem of increasing the cellular servicing capacity in spite of the limited radio spectrum available. We propose a hierarchical channel selection scheme for handling handoffs and new calls in micro/macro cellular systems. The scheme is intended to improve the performance and quality of service of these systems by increasing the cell channel utilization, reducing the handoff blocking probability and improving the responsive to new calls. The proposed scheme is based on several design enhancements including an overflow buffer, which is used for handoff calls that cannot be immediately switched to a micro cell channel. The application of this overflow buffer is made feasible by the availability of the umbrella coverage of the macro cell. A modified Guard Channel policy is proposed in conjunction with the overflow buffer for the purpose of giving handoff requests higher priority without the aggressive blocking of new calls. Load balancing rules aimed at the careful selection of micro and macro cell channels are developed. Handoff and new call requests are classified into few categories and control techniques for handling each category are defined. Each allocation for a new channel requires a check on the load factor of the cell. A detailed simulation model was developed to evaluate the hierarchical scheme, refine its design, and compare its performance with four of the schemes previously proposed in the literature. The simulation tests were performed under different tele traffic conditions and parameter values. The performance comparison results obtained by our extensive tests have shown that the proposed scheme consistently reduces the average handoff dropping rate, increases the new call acceptance rate and enhances the throughput of the cellular system

Robustness of optimal channel reservation using handover prediction in multiservice wireless networks

The aim of our study is to obtain theoretical limits for the gain that can be expected when using handover prediction and to determine the sensitivity of the system performance against different parameters. We apply an average-reward reinforcement learning approach based on afterstates to the design of optimal admission control policies in mobile multimedia cellular networks where predictive information related to the occurrence of future handovers is available. We consider a type of predictor that labels active mobile terminals in the cell neighborhood a fixed amount of time before handovers are predicted to occur, which we call the anticipation time. The admission controller exploits this information to reserve resources efficiently. We show that there exists an optimum value for the anticipation time at which the highest performance gain is obtained. 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Proactive policy management using TBVH mechanism in heterogeneous networks.

In order to achieve seamless interoperability in heterogeneous networking, it is vital to improve the context-awareness of the mobile node (MN) so that it is able to predict future network conditions with sufficient accuracy. In this paper, we introduce a predictive mathematical model for calculating the estimated Time Before Vertical Handover (TBVH) component from available network parameters. The model is practically implemented in OPNET and our simulation results confirm the validity of the concept. We then demonstrate how the knowledge of TBVH along with other network parameters can be applied by downward Quality of Service management policies which bundle multi-class traffic streams on to available network channels based on application QoS, device mobility patterns and prevailing channel conditions

Efficient resource allocation and call admission control in high capacity wireless networks

Resource Allocation (RA) and Call Admission Control (CAC) in wireless networks are processes that control the allocation of the limited radio resources to mobile stations (MS) in order to maximize the utilization efficiency of radio resources and guarantee the Quality of Service (QoS) requirements of mobile users. In this dissertation, several distributed, adaptive and efficient RA/CAC schemes are proposed and analyzed, in order to improve the system utilization while maintaining the required QoS. Since the most salient feature of the mobile wireless network is that users are moving, a Mobility Based Channel Reservation (MBCR) scheme is proposed which takes the user mobility into consideration. The MBCR scheme is further developed into PMBBR scheme by using the user location information in the reservation making process. Through traffic composition analysis, the commonly used assumption is challenged in this dissertation, and a New Call Bounding (NCB) scheme, which uses the number of channels that are currently occupied by new calls as a decision variable for the CAC, is proposed. This dissertation also investigates the pricing as another dimension for RA/CAC. It is proven that for a given wireless network there exists a new call arrival rate which can maximize the total utility of users, while maintaining the required QoS. Based on this conclusion, an integrated pricing and CAC scheme is proposed to alleviate the system congestion