Location Update versus Paging Trade-Off in Cellular Networks: An Approach Based on Vector Quantization

A practical information theoretic framework is developed for studying the optimal tradeoff between location update and paging costs in cellular networks. The framework envisions the quantization of location information into a registration area (RA) level granularity, followed by the use of an entropy-coding technique to decrease the location update rate. The rate distortion theory of the lossy quantization is identified as an appropriate measure for capturing the optimal tradeoff between a mobile's update rate and its location uncertainty. Based on LZ-78 compression, two different RA-level location update algorithms (RA-LeZi and LeZi-RA) have been developed, both of which asymptotically approach this rate-distortion bound. By allowing for quantization loss in the mobile node's movement pattern, this framework can reduce the overall update cost below the entropy bound associated with the original loss-less LeZi-update mobility management algorithm. Simulation results demonstrate a sharp decrease (/spl sim/ 50%) in the update cost, at the expense of a minor (/spl sim/ 25%) increase in the overall location management costs. The key essence of this framework lies in its practical applicability, because today's wireless networks already track the mobile user at an RA-level granularity.

In this paper, we develop an analytical model of the signaling costs due to location update and paging for the radio interface in mobile communications networks. This model accounts for the effects that the savings brought by different algorithms have on the total Location Management (LM) costs. It also takes into account the trade-off between the location update and paging costs, showing that those strategies that achieve savings in the location update costs deliver a larger overall improvement in the total LM costs than those algorithms focusing on the minimization of the paging costs. Moreover, leveraging the factors studied to obtain this model, we also analyze the overall LM costs including the fixed network part.

Application of AI techniques for locating mobile terminals in mobile wireless cellular networks: A novel paging scheme

LOCATION MANAGEMENT AND COST PLANNING FOR PERSONAL COMMUNICATION SYSTEMS

Location management deals with how to track mobile users within the cellular network. It consists of two basic operations: location update and paging. The total location management cost is the sum of the location update cost and the paging cost. Location areas and reporting centers are two popular location management schemes. The motivation for the study is the observation that the location update cost difference between the reporting centers scheme and the location areas scheme is small whereas the paging cost in the reporting centers scheme is larger than that in the location areas scheme. The paper compares the performance of the location areas scheme and the reporting centers scheme under aggregate movement behavior mobility models by simulations. Simulation results show that the location areas scheme performs about the same as the reporting centers scheme in two extreme cases, that is, when a few cells or almost all cells are selected as the reporting cells. However, the location areas scheme outperforms the reporting centers scheme at the 100% confidence level with all call-to-mobility ratios when the reporting cells divide the whole service area into several regions.

Several solutions have been proposed for improving the Quality of Service (QoS) in wireless cellular networks, such as Call Admission Control (CAC) and handover strategies. However, none of them considers the usage of different interfaces for different conditions. In this work, we propose a Fuzzy-Based Multi-Interface System (FBMIS), where each node is equipped with two interfaces: the traditional cellular network interface and Mobile Ad hoc Networks (MANET)interface. The proposed FBMIS system is able to switch from cellular to ad-hoc mode and vice versa. We consider four input parameters: Distance Between Nodes (DBN), Node Mobility (NM), Angle between Node and Base station (ANB), and User Request Security (URS). We evaluated the performance of the proposed system by computer simulations using MATLAB. The simulation results show that our system has a good performance.

In a high-capacity cellular network with limited spectral resources, it is desirable to minimize the radio bandwidth costs associated with paging when locating mobile users. Sequential paging, in which cells in the coverage area are partitioned into groups and paged in a non-increasing order of user location probabilities, permits a reduction in the average radio costs of paging at the expense of greater delay in locating the users. We present a polynomial time algorithm for minimizing paging cost under the average delay constraint, a problem that has previously been considered intractable. We show the conditions under which cluster paging, a simple heuristic technique proposed for use with dynamic location update schemes, is optimal. We also present analytical results on the average delay and paging cost obtained with sequential paging, including tight bounds.

The scarce radio resources available to any cellular radio network have to be shared between its revenue-generating voice- and data-carrying services, and non-revenue-generating management services. One of these management services is location management, crucial for the network to keep track of the location of its subscribers and to connect their incoming calls. Location management consists of the two activities, paging and location updating, both of which are structured around a subdivision of the network service area called the location area (LA). The ways in which the service area is partitioned therefore has a direct impact on the amount of radio bandwidth that has to be spent on location management. However, paging and location updating share an antagonistic relationship, and finding the optimal LA partitioning that strikes a balance between the two is a challenging design problem. In this paper, the problem of finding the optimal LA partitioning of a cellular radio network service area in order to minimise the total location management signalling cost is addressed. The choice of the decision variables used in the mathematical programming model results in an objective function that is conceptually easy to understand and a solution method that is simple and straightforward.

This paper presents an efficient heuristic algorithm for the channel assignment problem in cellular radio networks. The task is to find channel assignment with minimum frequency bandwidth necessary to satisfy given demands from different nodes in a cellular network. At the same time the interference among calls within the same cell and from different neighboring cells are to be avoided, where interference is specified as the minimum frequency distance to be maintained between channels assigned to a pair of nodes. The simplest version of this problem, where only cochannel interferences are considered, is NP-complete. The proposed algorithm could generate a population of random valid solutions of the problem very fast. The best among them is the optimum or very near to optimum solution. For all problems with known optimal solutions, the algorithm could find them. A statistical estimation of the performance of the proposed algorithm is done. Comparison with other methods show that our algorithm works better than the algorithms that we have investigated.

Given the increasing global emphasis on sustainable energy usage and the rising energy demands of cellular wireless networks, this work seeks an optimal short-term, continuous-time power-procurement schedule to minimize operating expenditure and the carbon footprint of cellular wireless networks equipped with energy-storage capacity, and hybrid energy systems comprising uncertain renewable energy sources. Despite the stochastic nature of wireless fading channels, the network operator must ensure a certain quality-of-service (QoS) constraint with high probability. This probabilistic constraint prevents using the dynamic programming principle to solve the stochastic optimal control problem. This work introduces a novel time-continuous Lagrangian relaxation approach tailored for real-time, near-optimal energy procurement in cellular networks, overcoming tractability problems associated with the probabilistic QoS constraint. The numerical solution procedure includes an efficient upwind finite-difference solver for the Hamilton-Jacobi-Bellman equation corresponding to the relaxed problem, and an effective combination of the limited memory bundle method (LMBM) for handling nonsmooth optimization and the stochastic subgradient method (SSM) to navigate the stochasticity of the dual problem. Numerical results, based on the German power system and daily cellular traffic data, demonstrate the computational efficiency of the proposed numerical approach, providing a near-optimal policy in a practical timeframe.

The channel assignment problem is increasingly important in cellular radio networks. Since the utilizable range of the frequency spectrum is not unlimited, the optimal assignment problem for assigning appropriate channels among individual members of a cellular network is crucial for network designers. This study seeks a conflict-free inter-cell channel assignment that satisfies both traffic demand requirements and electromagnetic compatibility (EMC) constraints. Specifically, this investigation proposes a novel and efficient channel assignment approach in cellular radio networks using a modified genetic algorithm. Applying this approach to a well-known problem demonstrates that this new strategy clearly outperforms some existing algorithms.

Cellular mobile systems provides access to a wide range of services and allow mobile terminals (MTs) to move randomly from one place to another within a well-defined geographical area. Due to the growing number of mobile users, global connectivity, and the small size of cells, one of the most critical issues regarding these networks is location management. The challenging task in a cellular system is to track the location of the mobile users effectively so that the connection establishment cost and delay is low. In recent years, several strategies have been proposed to improve the performance of the location management procedure in cellular networks. In this paper, we propose an intelligent approach by taking the User Profile History (UPH); to reduce the location update cost by combining Back-Propagation Algorithm and Cascaded Correlation Neural Network. The implementation of this strategy has been subject to extensive tests. The results obtained confirm the efficiency of UPH in significantly reducing the costs of both location updates and call delivery procedures when compared to the various other strategies well-known in the literature.

Location management is the basis for ensuring service continuity in low earth orbit (LEO) satellite mobile communication systems. The dual mobility of LEO satellites and mobile users triggers frequent location update procedures, which will increase the network location management overhead and bring great challenges to network location management, especially in the mega satellite networks. In this paper, we propose a location management technology solution for mega satellite networks, including location management architecture, location area design, location update, and paging procedures. A medium earth orbit (MEO) satellite-assisted location management architecture is proposed to improve the efficiency of location management. It extends the location management control plane from the ground to space and adopts a distributed location management mechanism. A dual location area, including the satellite location area and user location area, is designed to balance the network location update and paging overhead. Based on the dual location area, we systematically design low-overhead location update and paging procedures. Simulation results have verified that the proposed location management technology solution can reduce the total location management overhead and delay by at least 45.8% and 20.8%, respectively.

Network protocols in cellular wireless data networks must update routes as a mobile host moves between cells. These routing updates combined with some associated state changes are called handoffs. Most current handoff schemes in wireless networks result in data loss or large variations in packet delivery times. Unfortunately, many applications, such as real-time multimedia applications and reliable transport protocols, adapt to long term estimates of end-to-end delay and loss. Violations and rapid fluctuations of these estimates caused by handoff processing often result in degraded performance. For example, loss during handoff adversely affects TCP performance [4], and high packet loss and variable delays result in poor real-time multimedia performance. In this paper, we describe a multicast-based protocol that eliminates data loss and incurs negligible delays during a handoff. The basic technique of the algorithm is to anticipate a handoff using wireless network information in the form of received signal strengths and to multicast data destined for the mobile host to nearby base stations in advance. This routing, combined with intelligent buffering techniques at the base stations, enables very rapid routing updates and eliminates data loss without the use of explicit data forwarding. We have implemented this protocol using IP Multicast and Mobile IP-like routing. In our implementation, handoffs typically take between 8 and 15 ms to complete and result in no data loss.

Conventional cellular wireless networks were designed with the purpose of providing high throughput for the user and high capacity for the service provider, without any provisions of energy efficiency. As a result, these networks have an enormous Carbon footprint. In this paper, we describe the sources of the inefficiencies in such networks. First, we present results of the studies on how much Carbon footprint such networks generate. We also discuss how much more mobile traffic is expected to increase so that this Carbon footprint will even increase tremendously more. We then discuss specific sources of inefficiency and potential sources of improvement at the physical layer, as well as at higher layers of the communication protocol hierarchy. In particular, considering that most of the energy inefficiency in cellular wireless networks is at the base stations, we discuss multi-tier networks and point to the potential of exploiting mobility patterns in order to use base station energy judiciously. We then investigate potential methods to reduce this inefficiency and quantify their individual contributions. By a consideration of the combination of all potential gains, we conclude that an improvement in energy consumption in cellular wireless networks by two orders of magnitude, or even more, is possible.