An efficient algorithm for determination of the optimum base-station assignment in cellular DS-CDMA systems

An algorithm is proposed that finds the optimum assignment of mobile users to base stations, and its associated transmission powers, in a cellular direct-sequence code-division multiple-access network, with a computational complexity that grows polynomially with the number of users and base stations. The algorithm detects infeasible situations and allows the inclusion of power constraints. Its performance is analyzed in terms of complexity and system capacity.     

Tracking mobile users in wireless communications networks

Tracking strategies for mobile wireless networks are studied. A cellular architecture in which base stations that are interconnected by a wired network communicate with mobile units via wireless links is assumed. The cost of utilizing the wireless links for the actual tracking of mobile users is considered. A tracking strategy in which a subset of all base stations is selected and designed as reporting centers is proposed. Mobile users transmit update messages only upon entering cells of reporting centers, while every search for a mobile user is restricted to the vicinity of the reporting center to which the user last reported. It is shown that, for an arbitrary topology of the cellular network (represented by the mobility graph), finding an optimal set of reporting centers is an NP-complete problem. Optimal and near-optimal solutions for important special cases of the mobility graph are presented     

User mobility profile prediction: An adaptive fuzzy inference approach

Predicting the probabilities that a mobile user will be active in other cells at future moments poses a significant technical challenge to network resource management in multimedia wireless communications. The probability information can be used to assist base stations to maintain a balance between guaranteeing quality of service (QoS) to mobile users and achieving maximum resource utilization. This paper proposes a novel adaptive fuzzy logic inference system to estimate and predict the probability information for direct sequence code division multiple access (DS/CDMA) wireless communications networks. The estimation is based on measured pilot signal strengths at the mobile user from a number of nearby base stations, and the prediction is obtained using the recursive least square (RLS) algorithm. Numerical results are presented to demonstrate the performance of the proposed technique under various path loss and channel shadowing conditions. This revised version was published online in July 2006 with corrections to the Cover Date.     

A distributed implementation of mobility load balancing with power control and cell reselection in 4G network

We consider a self‐organizing network (SON) capability of mobility load balancing in a 4G network, which determines the transmission power level for individual base stations and cell reselection for individual mobile stations such that the network‐wide load is minimized while satisfying the minimum signal‐to‐noise and interference ratio (SINR) requirement of individual users. Both centralized and distributed schemes are proposed. The centralized scheme is based on the greedy algorithm, serving as a performance bound to the distributed scheme. The distributed scheme is to solve the system‐wide optimization problem in the flat network model, i.e. no central control node. Furthermore, it requires relatively low inter‐cell exchange information among neighboring cells over an inter‐cell channel, e.g. X2 interface in the LTE network. The proposed design objective is to minimize the number of mobile users that do not satisfy the specified average throughput, while distributing the user traffic load as uniformly as possible among the neighboring cells. Our simulation results for a uniform user distribution demonstrate that the proposed scheme can achieve up to almost 80% of a load balancing gain that has been achieved by a greedy algorithm in the centralized optimization. Copyright © 2014 John Wiley & Sons, Ltd.     

Efficient location area planning for personal communication systems

A central problem in personal communication systems is to optimize bandwidth usage, while providing Quality of Service (QoS) guarantees to mobile users. Network mobility management, and in particular, location management, consumes a significant portion of bandwidth, which is a necessary overhead for supporting mobile users. We focus our efforts on minimizing this overhead. Unlike previous works, we concentrate on optimizing existing schemes, and so the algorithms we present are easily incorporated into current networks. We present the first polynomial time approximation algorithms for minimum bandwidth location management. In planar graphs, our algorithm provably generates a solution that uses no more than a constant factor more bandwidth than the optimal solution. In general graphs, our algorithm provably generates a solution that uses just a factor O (log n) more bandwidth than optimal where n is the number of base stations in the network. We show that, in practice, our algorithm produces near-optimal results and outperforms other schemes that are described in the literature. For the important case of the line graph, we present a polynomial-time optimal algorithm. Finally, we illustrate that our algorithm can also be used for optimizing the handoff mechanism.     

基于甲虫搜索的改进粒子群无人机辅助网络部署优化算法

在体育赛场等用户大规模聚集或者突发灾难的情况下,地面基站经常面临过载甚至瘫痪的问题。此时,多无人机(UAV)辅助网络系统可以很好地为地面基站提供信号补偿,有效地增强局部地区的通信质量。然而,无人机的机动性和网络流动引起的拓扑结构变化,会导致频繁的间歇性连接甚至出现传输故障。因此,UAV基站的有效部署以及网络性能的优化成为亟待解决的问题。该文提出一种基于甲虫搜索的改进粒子群UAV辅助网络部署优化算法—智能高效算法(IEA),利用甲虫搜索算法(BAS)的个体寻优优势,对粒子群算法(PSO)进行改进,并首次采用双门限约束保证用户通信质量,使得多UAV系统下的网络性能得到了改善。仿真结果表明,相对于传统算法,该文提出的IEA算法在系统吞吐量、用户平均吞吐量以及频谱效率等方面都获得了较大提升。     

Bandwidth-reservation scheme based on road information for next-generation cellular networks

Channel-reservation techniques have been widely studied in cellular networks in order to meet the desired quality-of-service requirements. In this paper, a distributed predictive channel-reservation scheme, called the road-map-based channel-reservation scheme (RMCR), and a call-admission-control algorithm are proposed. The goal is to reduce the handoff-dropping probability and to improve the bandwidth utilization. In the RMCR scheme, we assume that base stations (BSs) are equipped with road-map information and that mobile stations (MSs) are equipped with global positioning systems (GPS) devices. MSs periodically report their GPS location information to their BSs. Based on the location information of the MSs at two consecutive epochs, the BSs estimate the speed and moving direction of the MSs. Furthermore, the BSs estimate the probability that the MSs will enter the neighboring cells based on their velocity and the road-map information stored in the BSs. The BSs then compute the amount of bandwidth to be reserved, based on such estimation. With the road-map information, the BSs can make a more-accurate prediction on the user's mobility and, hence, reduce unnecessary bandwidth reservation. Simulation results show that RMCR is capable of keeping the handoff-dropping probability low and allocating bandwidth to new/handoff calls efficiently. We also show that RMCR is robust with respect to system parameters such as user's speed, the density of roads, the accuracy of mobility measurement, and so on.     

A Virtual Topology Based Routing Protocol for Multihop Dynamic Wireless Networks

In this paper, a new hierarchical multihop routing algorithm and its performance evaluation is presented for fully dynamic wireless networks. The routing algorithm operates on a virtual topology obtained by partitioning the routing information for mobile terminals and mobile base stations into a hierarchical, distributed database. Based on the virtual topology, each mobile base station stores a fraction of the routing information to balance the complexity of the location-update and the path-finding operations. Mobility of the network entities changes the load distribution and causes processing and memory bottlenecks in some parts of the network. However, since the network routing elements are also mobile, their movement can be used to distribute the load. Thus, new load balancing schemes are intoduced to distribute the routing overhead uniformly among the mobile base stations. The performance of the hierarchical multihop routing algorithm is investigated through simulations. It is shown that the routing protocol can cope with high mobility and deliver packets to the destinations successfully.     

Real-time mobility tracking algorithms for cellular networks based on Kalman filtering

We propose two algorithms for real-time tracking of the location and dynamic motion of a mobile station in a cellular network using the pilot signal strengths from neighboring base stations. The underlying mobility model is based on a dynamic linear system driven by a discrete command process that determines the mobile station's acceleration. The command process is modeled as a semi-Markov process over a finite set of acceleration levels. The first algorithm consists of an averaging filter for processing pilot signal, strength measurements and two Kalman filters, one to estimate the discrete command process and the other to estimate the mobility state. The second algorithm employs a single Kalman filter without prefiltering and is able to track a mobile station even when a limited set of pilot signal measurements is available. Both of the proposed tracking algorithms can be used to predict future mobility behavior, which can be, useful in resource allocation applications. Our numerical results show that the proposed tracking algorithms perform accurately over a wide range of mobility parameter values.     

An Algorithm for the Design of a Cost-Optimized Topology for the Fixed Part of a GSM Network

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Dynamic content distribution for mobile enterprise networks

Mobile networks are becoming increasingly popular in enterprise environments as a means for distributing information to a large community of highly dynamic users. In comparison to traditional wired networks, mobile networks are distinguished by a potentially much higher variability in users demand due to user mobility. Most previous content distribution techniques assume a static user demand distribution and, thus, may not perform well in mobile networks. This paper proposes and analyzes a mobile dynamic content distribution network model, which takes demand variations into account to decide whether to replicate a content and whether to remove previously created replicas in order to minimize total network traffic. We develop two solutions to our model: an offline optimal solution, which provides an ideal lower bound on the total traffic, and a practical heuristic online algorithm, which uses demand forecasting to make replication decisions. We provide a thorough evaluation of our solutions, comparing them against ACDN, the only previous dynamic content placement algorithm targeting bandwidth minimization that we are aware of. Our results show that our online algorithm significantly outperforms ACDN, reducing total network traffic by up to 85% in a number of experiments covering a large system design space.     

UMTS integrated with B-ISDN

Since, by the turn of the century, a mobile terminal will be involved in 50 percent of all calls, it is critical that the integration of the fixed and mobile telecommunication systems succeeds. This will require that B-ISDN support some features necessary to provide mobility services to the users. In the scenario discussed in the present article, the UMTS base stations are connected to a B-ISDN local exchange using the same user-network-interface (UNI) as B-ISDN fixed network terminals. Therefore, many of the aspects discussed in the article are related to the UNI     

一种短信业务分布预测算法分析

随着移动通信短信业务的迅速发展,现有的短信业务分布预测算法已经无法满足需求。提出了一种基于聚类分析和模拟退火的短信业务分布预测算法。根据电子地图、基站语音和短信业务统计数据,提取影响短信业务分布的相关属性,采用聚类分析方法中的自组织映射(Self Organizing Map,SOM)方法和k-means算法,将网络中基站进行分类,然后采用模拟退火算法和最小二乘法计算得到不同类型基站中的不同地物的短信日均业务密度值,从而达到对短信进行业务分布预测的目的。通过实际基站短信业务统计数据的验证,该算法大幅提高了短信业务分布预测的准确度。     

Enhanced path prediction for network resource management in wireless LANs

Path prediction is currently being considered for use in the context of mobile and wireless computing toward more efficient network resource management schemes. Path prediction allows the network and services to further enhance the quality of service levels the user enjoys. Such mechanisms are mostly meaningful in infrastructures like wireless LANs. In this article we present a path prediction algorithm that exploits the machine learning algorithm of learning automata. The decision of the learning automaton is driven by the movement patterns of a single user but is also affected by the aggregated patterns demonstrated by all users. Simulations of the algorithm, performed using the realistic mobility pattern generator, show increased prediction accuracy.     

Dynamic Location Management for Mobile Computing

This paper presents a dynamic and individualized location update scheme that considers each user's mobility patterns. The mobility patterns are used to create individualized location areas for each user. The proposed scheme is flexible and can be used in network with arbitrary cell topologies. The scheme, along with other existing schemes is simulated using realistic users' mobility and call arrival patterns, and network topology. The simulated environment consists of 90 cells representing the geographical area of the San Francisco bay, and 66,550 mobile users representing the typical classes of users that are normally present in a real cellular network. Results show the proposed scheme gives lower overall signaling costs, resulting in savings on the limited radio bandwidth that may have otherwise been used for location updates and paging.     

Broadcast Approach for UMTS Mobility Database Recovery

The universal mobile telecommunications system (UMTS) provides high bandwidth packet data services to mobile users. To support mobility management, an MM context is established for every mobile station in its corresponding serving GPRS support node (SGSN). When the SGSN fails, all MM contexts in the SGSN are corrupted. These MM contexts must be recovered or data delivery to the mobile stations will fail. This paper describes a broadcast approach that allows the MS to detect lost MM context in SGSN and therefore speeds up the process for SGSN recovery. We propose an analytic model to evaluate the performance of the broadcast approach. The analytic model is validated against simulation experiments. Based on our study, the network operator can select the appropriate parameter values in the broadcast approach for various traffic conditions.     

A resource estimation and call admission algorithm for wirelessmultimedia networks using the shadow cluster concept

The shadow cluster concept can be used to estimate future resource requirements and to perform call admission decisions in wireless networks. Shadow clusters can be used to decide if a new call can be admitted to a wireless network based on its quality-of-service (QoS) requirements and local traffic conditions. The shadow cluster concept can especially be useful in future wireless networks with microcellular architectures where service will be provided to users with diverse QoS requirements. The framework of a shadow cluster system is completely distributed, and can be viewed as a message system where mobile terminals inform the base stations in their neighborhood about their requirements, position, and movement parameters. With this information, base stations predict future demands, reserve resources accordingly, and admit only those mobile terminals which can be supported adequately. The shadow cluster concept involves some processing and communication overheads. These overheads have no effect on wireless resources, but only on the base stations and the underlying wireline network. It is shown how base stations determine the probabilities that a mobile terminal will be active in other cells at future times, define and maintain shadow clusters by using probabilistic information on the future position of their mobile terminals with active calls, and predict resource demands based on shadow cluster information. In addition, a call admission algorithm is introduced, which uses current traffic and bandwidth utilization conditions, as well as the amount of resources and maximum allowable “dropping probability” being requested. Performance results showing the advantages of the shadow cluster concept are also included     

Optimization of wireless resources for personal communicationsmobility tracking

In personal communications applications, users communicate via wireless with a wireline network. The wireline network tracks the current location of the user, and can therefore route messages to a user regardless of the user's location. In addition to its impact on signaling within the wireline network, mobility tracking requires the expenditure of wireless resources as well, including the power consumption of the portable units carried by the users and the radio bandwidth used for registration and paging. Ideally, the mobility tracking scheme used for each user should depend on the user's call and mobility pattern, so the standard approach, in which all cells in a registration area are paged when a call arrives, may be wasteful of wireless resources. In order to conserve these resources, the network must have the capability to page selectively within a registration area, and the user must announce his or her location more frequently. We propose and analyze a simple model that captures this additional flexibility. Dynamic programming is used to determine an optimal announcing strategy for each user. Numerical results for a simple one-dimensional mobility model show that the optimal scheme may provide significant savings when compared to the standard approach even when the latter is optimized by suitably choosing the registration area size on a per-user basis. Ongoing research includes computing numerical results for more complicated mobility models and determining how existing system designs might be modified to incorporate our approach     

Group vertical handoff management in heterogeneous networks

Traditional vertical handover schemes postulate that vertical handovers (VHOs) of users come on an individual basis. This enables users to know previously the decision already made by other users, and then the choice will be accordingly made. However, in case of group mobility, almost all VHO decisions of all users, in a given group (e.g., passengers on board a bus or a train equipped with smart phones or laptops), will be made at the same time. This concept is called group vertical handover (GVHO). When all VHO decisions of a large number of users are made at the same time, the system performance may degrade and network congestion may occur. In this paper, we propose two fully decentralized algorithms for network access selection, and that is based on the concept of congestion game to resolve the problem of network congestion in group mobility scenarios. Two learning algorithms, dubbed Sastry Algorithm and Q‐Learning Algorithm, are envisioned. Each one of these algorithms helps mobile users in a group to reach the nash equilibrium in a stochastic environment. The nash equilibrium represents a fair and efficient solution according to which each mobile user is connected to a single network and has no intention to change his decision to improve his throughput. This shall help resolve the problem of network congestion caused by GVHO. Simulation results validate the proposed algorithms and show their efficiency in achieving convergence, even at a slower pace. To achieve fast convergence, we also propose a heuristic method inspired from simulated annealing and incorporated in a hybrid learning algorithm to speed up convergence time and maintain efficient solutions. The simulation results also show the adaptability of our hybrid algorithm with decreasing step size‐simulated annealing (DSS‐SA) for high mobility group scenario. Copyright © 2015 John Wiley & Sons, Ltd.