Sanjoy K. Sen

A selective location update strategy for PCS users

A new location update strategy for personal communication services (PCS) networks and its implementation using a genetic algorithm are proposed. Most of the practical cellular mobile systems partition a geographical region into location areas (LAs) and users are made to update on entering a new LA. The main drawback of this scheme is that it does not consider the individual user mobility and call arrival patterns. Combining these factors with the LA‐based approach, we propose an optimal update strategy which determines whether or not a user should update in each LA, and minimizes the average location management cost derived from a user‐specific mobility model and call generation pattern. The location management cost optimization problem is also elegantly solved using a genetic algorithm. Detailed simulation experiments are conducted to capture the effects of mobility and call‐arrival patterns on the location update strategy. The conclusion from this work is that skipping location updates in certain LAs leads to the minimization of the overall location management cost for a user with a specific mobility pattern and even with moderately high call arrival rate.

A call admission and control scheme for quality-of-service (QoS) provisioning in next generation wireless networks

We propose a framework for quality‐of‐service (QoS) provisioning for multimedia services in next generation wireless access networks. This framework aims at providing a differentiated treatment to multimedia traffic flows at the link layer, which can be broadly classified as real‐time (or delay‐sensitive) and non‐real‐time (or delay‐tolerant). Various novel schemes are proposed to support the differential treatment and guarantee QoS. These schemes include bandwidth compaction, channel reservation and degradation, with the help of which a call admission and control algorithm is developed. The performance of the proposed framework is captured through analytical modeling and simulation experiments. Analytically, the average carried traffic and the worst case buffer requirements for real‐time and non‐real‐time calls are estimated. Simulation results show up to 21% improvement in the admission probability of real‐time calls and up to 17% improvement in the admission probability of non‐real‐time calls, when various call control techniques like bandwidth compaction are employed. Using our channel reservation technique, we observe a 12% improvement in the call admission probability compared to another scheme proposed in the literature.

Adaptive Location Prediction Strategies Based on a Hierarchical Network Model in a Cellular Mobile Environment

We present four eecient heuristics (one basic scheme and three of its variants) to predict the location of a mobile user in the cellular mobile environment. The proposed location management schemes assume a hierarchy of location areas, which might change dynamically with changing traac patterns. A method to compute this hierarchical tree is also proposed. Depending on the proole of the user movements for the last time units, the most probable (and the future probable) location areas are computed for the user in the basic scheme and its rst variant. The second variant predicts the location probabilities of the user in the future cells combining them with those already traversed in the last time units to form the most probable location area. The third variant is a hybrid of the rst and second variants. Finally, the proposed heuristics are validated by extensive simulation of a real time cellular mobile system, where all the four schemes are compared under various traac patterns.

A framework for bandwidth degradation and call admission control schemes for multiclass traffic in next-generation wireless networks

The next-generation wireless networks need to support a wide range of multimedia applications with limited radio resources like bandwidth. In this paper, we propose a novel integrated framework for bandwidth degradation and call admission control (CAC) for multiclass real-time multimedia traffic in such networks. To increase the total carried traffic in an overloaded (saturated) wireless system, some of the ongoing calls in our framework are allowed to operate under a degraded mode, thereby releasing wireless channels that can be used to accommodate new calls, however, at the cost of user satisfaction. Indeed, an increase in carried traffic (i.e., providers revenue generation) and users quality-of-service satisfaction are two conflicting goals in a bandwidth allocation scheme. The proposed framework adequately models this tradeoff by introducing the negative revenue (i.e., loss) from bandwidth degradation, and finding the optimal degradation and admission policies that maximize the net revenue. When there is a mixture of real-time and nonreal-time calls in the system, the former are given preemptive priority over the latter, which are buffered for future admission in case of preemption. A channel sharing scheme is proposed for nonreal-time traffic and analyzed using a Markov modulated Poisson process-based queueing model. Detailed simulation experiments are conducted to validate our proposed framework.

Quality-of-Service degradation strategies in multimedia wireless networks

We propose new strategies for call degradation and call admission in a third generation multimedia wireless network. Our approach is based on modeling the quality-of-service (QoS) degradation of real-time and non-real-time traffic. To increase the carried traffic in an overloaded system, some of the ongoing calls are forced to operate under a degraded mode, thereby releasing channels that they are using. Two orthogonal QoS parameters, called carried traffic and bandwidth degradation, are characterized and a cost function describing the total revenue earned by the system from a bandwidth degradation policy is formulated. This cost function model is then extended to incorporate a call admission policy. Detailed simulation experiments are conducted to validate the proposed model. When there is a mixture of real-time and non-real-time calls in the system, the real-time traffic generally has preemptive priority over the other, which are buffered for future admission in case of preemption. A channel sharing scheme is proposed for non-real-time traffic and analyzed using a Markov modulated Poisson process (MMPP) based queueing model and by simulation experiments.

A new location update strategy for cellular networks and its implementation using a genetic algorithm

A new location update strategy and its implementation using a genetic algorithm are proposed. Most of the practical cellular mobile systems partition a geographical region into location areas (LA) and users are made to update on entering a new LA. The main drawback of this scheme is that it does not consider the individual user mobility and call arrival patterns. Combining per-user mobility and call arrival patterns with the LAbased approach, an optimal update strategy is proposed for each user which determines whether or not to update in each LA. The update strategy minimizes the average location management cost derived from a user-specific mobility model and call generation pattern. The location management cost optimization problem is solved using a genetic algorithm. The results clearly demonstrate that for low user residing probability in LA’s, low call arrival rate and high update cost, skipping updation in several LA’s leads to minimization of the overall location management cost.

A novel load balancing scheme for the tele-traffic hot spot problem in cellular networks

We propose a dynamic load balancing scheme for the tele-traffic hot spot problem in cellular networks. A tele-traffic hot spot is a region of adjacent hot cells where the channel demand has exceeded a certain threshold. A hot spot is depicted as a stack of hexagonal ‘Rings’ of cells and is classified as complete if all cells within it are hot. Otherwise it is termed incomplete. The rings containing all cold cells outside the hot spot are called ‘Peripheral Rings’. Our load balancing scheme migrates channels through a structured borrowing mechanism from the cold cells within the ‘Rings’ or ‘Peripheral Rings’ to the hot cells constituting the hot spot. A hot cell in ‘Ring i’ can only borrow a certain fixed number of channels from adjacent cells in ‘Ring i+1’. We first propose a load balancing algorithm for a complete hot spot, which is then extended to the more general case of an incomplete hot spot. In the latter case, by further classifying a cell as cold safe, cold semi-safe or cold unsafe, a demand graph is constructed which describes the channel demand of each cell within the hot spot or its ‘Peripheral Rings’ from its adjacent cells in the next outer ring. The channel borrowing algorithm works on the demand graph in a bottom up fashion, satisfying the demands of the cells in each subsequent inner ring until ‘Ring 0’ is reached. A Markov chain model is first developed for a cell within a hot spot, the results of which are used to develop a similar model which captures the evolution of the entire hot spot region. Detailed simulation experiments are conducted to evaluate the performance of our load balancing scheme. Comparison with another well known load balancing strategy, known as CBWL, shows that under moderate and heavy tele-traffic conditions, a performance improvement as high as 12% in terms of call blockade is acheived by our load balancing scheme.

A distributed load balancing algorithm for the hot cell problem in cellular mobile networks

We propose a novel channel management algorithm, called distributed load balancing with selective borrowing (D-LBSB), for cellular mobile networks. As an underlying approach, we start with a fixed channel assignment scheme where each cell is initially allocated a set of local channels, each to be assigned on demand to a user in that cell. The novelty of our D-LBSB scheme lies in handling the hot cell problem because it proposes to migrate unused channels from suitable cold cells to the hot ones through a distributed channel borrowing algorithm. With the help of a Markov model, the probability of a cell being hot and the call blocking probability in a cell are derived. Detailed simulation experiments are carried out in order to evaluate our proposed methodology. Performance comparison reveals that the D-LBSB scheme performs better than a centralized version in an overloaded system, and significantly better than several other existing schemes in terms of call blocking probability, under moderate and heavy loads.

Call admission and control for quality-of-service provisioning in cellular networks

We propose a call admission and a call control algorithm for optimistic quality-of-service (QoS) provisioning for multimedia traffic in the third generation wireless networks. Unlike most of the existing schemes which over-reserves wireless bandwidth our scheme uses a user classification algorithm and reserves bandwidth only in the destination cells for a certain class of users, called departing users. For wireless systems requiring continuous spectrum allocation, a novel approach called bandwidth compaction (similar to memory compaction in operating systems) is proposed for efficient utilization of the available spectrum. The multimedia traffic is also classified as real-time and non-real-time. A Markov modulated Poisson process (MMPP) based queueing model is proposed to capture the call admission priority of real-time calls over non-real-time ones, which are buffered for future admission in case of preemption. Detailed simulation experiments are performed to compare our scheme with a similar existing scheme. We observe performance improvements as high as 24% for call blocking probability and 12% for call admission and successful hand-off probability.

An efficient distributed channel management algorithm for cellular mobile networks

We propose a novel channel management algorithm, called distributed load balancing with selective borrowing (D-LBSB), for cellular mobile networks. As an underlying approach, we start with a fixed channel assignment scheme where each cell is initially allocated a set of local channels, each to be assigned on demand to a user in that cell. The novelty of our D-LBSB scheme lies in handling the hot cell problem because it proposes to migrate unused channels from suitable cold cells to the hot ones through a distributed channel borrowing algorithm. With the help of a Markov model, the probability of a cell being hot and the call blocking probability in a cell are derived. Detailed simulation experiments are carried out in order to evaluate our proposed methodology. Performance comparison reveals that the D-LBSB scheme performs better than a centralized version in an overloaded system, and significantly better than several other existing schemes in terms of call blocking probability, under moderate and heavy loads.