handbook of wireless networks and mobile computing

Szuba Parallel and Distributed Computing: A Survey of Models, Paradigms, and proaches / Claudia Leopold Ap-Fundamentals of Distributed Object Systems: A CORBA Perspective / Zahir Tari a

HANDBOOK OF

WIRELESS NETWORKS

AND MOBILE COMPUTING

Copyright © 2002 John Wiley & Sons, Inc ISBNs: 0-471-41902-8 (Paper); 0-471-22456-1 (Electronic)

Series Editor: Albert Y Zomaya

Parallel and Distributed Simulation Systems / Richard Fujimoto

Surviving the Design of Microprocessor and Multimicroprocessor Systems: Lessons Learned / Veljko Milutinovic´

Mobile Processing in Distributed and Open Environments / Peter Sapaty

Introduction to Parallel Algorithms / C Xavier and S S Iyengar

Solutions to Parallel and Distributed Computing Problems: Lessons from

Bio-logical Sciences / Albert Y Zomaya, Fikret Ercal, and Stephan Olariu (Editors)

New Parallel Algorithms for Direct Solution of Linear Equations / C Siva Ram

Murthy, K N Balasubramanya Murthy, and Srinivas Aluru

Practical PRAM Programming / Joerg Keller, Christoph Kessler, and

Jesper Larsson Traeff

Computational Collective Intelligence / Tadeusz M Szuba

Parallel and Distributed Computing: A Survey of Models, Paradigms, and proaches / Claudia Leopold

Ap-Fundamentals of Distributed Object Systems: A CORBA Perspective /

Zahir Tari and Omran Bukhres

Pipelined Processor Farms: Structured Design for Embedded Parallel tems / Martin Fleury and Andrew Downton

Sys-Handbook of Wireless Networks and Mobile Computing /

Ivan Stojmenovic´ (Editor)

Universidad Nacional Autonoma de México

A WILEY-INTERSCIENCEPUBLICATION

JOHN WILEY & SONS, INC.

LETTERS Readers, however, should contact the appropriate companies for more complete information regarding

trademarks and registration.

Copyright © 2002 by John Wiley & Sons, Inc All rights reserved

No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic

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services of a competent professional person should be sought.

ISBN 0-471-22456-1

This title is also available in print as ISBN 0-471-41902-8.

For more information about Wiley products, visit our web site at www.Wiley.com.

Qing-An Zeng and Dharma P Agrawal

Harilaos G Sandalidis and Peter Stavroulakis

v

3.6 Fixed-Channel Assignment Problem 57

Andrew D Myers and Stefano Basagni

7 Traffic Integration in Personal, Local, and Geographical Wireless Networks 145

Raffaele Bruno, Marco Conti, and Enrico Gregori

7.4 Third-Generation Cellular Systems: UMTS 160

Thyagarajan Nandagopal and Xia Gao

Koji Nakano and Stephan Olariu

Koji Nakano and Stephan Olariu

11.4 Other Issues 260

Albert Gräf and Thomas McKenney

Hung-Yun Hsieh and Raghupathy Sivakumar

14.8 Subscription and Fraud Detection in Mobile Phone Systems 317

15.3 MAC Layer 331

Yu-Chee Tseng, Wen-Hua Liao, and Shih-Lin Wu

19 Power Optimization in Routing Protocols for Wireless and 407 Mobile Networks

Stephanie Lindsey, Krishna M Sivalingam, and Cauligi S Raghavendra

22 Topological Design, Routing, and Handover in Satellite Networks 473

Afonso Ferreira, Jérôme Galtier, and Paolo Penna

22.3 Network Mobility and Traffic Modeling 478

23.5 Multicasting in Mobile Ad Hoc Networks: Adopting Wireless 500Protocols

25.2 Mobility Requirements and Constraints in an IP Environment 530

26 Data Management in Wireless Mobile Environments 553

Sandeep K S Gupta and Pradip K Srimani

Dharma P Agrawal, University of Cincinnati, Department of Electrical Engineering and

Computer Science, Cincinnati, Ohio 45221

Michel Barbeau, Carleton University, School of Computer Science, Ottawa, Ontario KIS

Raffaele Bruno, Consiglio Nazionale delle Ricerche (CNR), Istituto CNUCE, 56010

Ghezzano, Pisa, Italy

Marco Conti, Consiglio Nazionale delle Ricerche (CNR), Istituto CNUCE, 56010

Ghez-zano, Pisa, Italy

Christos Douligeris, Institute of Computer Science, FORTH, Heraklion, Crete, Greece Afonso Ferreira, CNRS Mascotte, 13S INRIA Sophia Antipolis, BP 93, F-06902 Sophia

Antipolis Cedex, France

Jérôme Galtier, France Telecom R&D and CNRS Mascotte, 13S INRIA Sophia

Antipo-lis, BP 93, F-06902 Sophia Antipolis Cedex, France

Xia Gao, University of Illinois at Urbana-Champaign, Coordinated Science Laboratory,

Urbana, Illinois 61801

Silvia Giordano, Swiss Federal Institute of Technology, Institute of Computer

Communi-cations and AppliCommuni-cations, CH-1015 Lausanne, Switzerland

Albert Gräf, Johannes Gutenberg University, Department of Music Informatics, 55099

Mainz, Germany

xiii

Enrico Gregori, Consiglio Nazionale delle Ricerche (CNR), Istituto CNUCE, 56010

Ghezzano, Pisa, Italy

Sandeep K S Gupta, Arizona State University, Department of Computer Science and

Engineering, Tempe, Arizona 85287

Hung-Yun Hsieh, Georgia Institute of Technology, School of Electrical and Computer

Engineering, Atlanta, Georgia 30332

Qinglong Hu, IBM Almaden Research Center, San Jose, California

Jeannette C M Janssen, Dalhousie University, Department of Mathematics and

Statis-tics, Halifax, Nova Scotia B3H 3J5, Canada

Thomas Kunz, Carleton University, Systems and Computer Engineering, Ottawa, Ontario

K1S 5B6, Canada

Dik-Lun Lee, Hong Kong University of Science and Technology, Department of

Comput-er Science, Clear WatComput-er Bay, Hong Kong

Wang-Chien Lee, Verizon Laboratories, Waltham, Massachusetts

Wen-Hua Liao, National Central University, Department of Computer Science and

Infor-mation Engineering, Tao-Yuan, Taiwan

Stephanie Lindsey, Washington State University, School of Electrical Engineering and

Computer Science, Pullman, Washington 99l64

Errol L Lloyd, University of Delaware, Department of Computer Science and

Informa-tion Sciences, Newark, Delaware 19716

Andrew D Myers, University of Texas at Dallas, Department of Computer Science,

Richardson, Texas 75083

Thomas McKenney, Johannes Gutenberg University, Department of Music Informatics,

55099 Mainz, Germany

Koji Nakano, Japan Advanced Institute for Science and Technology

Thyagarajan Nandagopal, University of Illinois at Urbana-Champaign, Coordinated

Sci-ence Laboratory, Urbana, Illinois 61801

Lata Narayanan, Concordia University, Department of Computer Science, Montreal,

Quebec H3G 1M8, Canada

Stephan Olariu, Old Dominion University, Department of Computer Science, Norfolk,

Virginia 23529

Andrzej Pelc, Unversité du Québec à Hull, Departement d’Informatique, Hull, Québec

J8X 3X7, Canada

Paolo Penna, CNRS Mascotte, 13S INRIA Sophia Antipolis, BP 93, F-06902 Sophia

An-tipolis Cedex, France

Cauligi S Raghavendra, University of Southern California, Department of Electrical

Engineering, Los Angeles, California 90089

Lakshmi Ramachandran, Trillium Digital Systems, International Tech Park, Bangalore

560 066, India

Harilaos G Sandalidis, Telecommunications Systems Institute, 37 Iroon Polytechniou

Str., Crete, Greece

Raghupathy Sivakumar, Georgia Institute of Technology, School of Electrical and

Com-puter Engineering, Atlanta, Georgia 30332

Krishna M Sivalingam, Washington State University, School of Electrical Engineering

and Computer Science, Pullman, Washington 99164

Pradip K Srimani, Clemson University, Department of Computer Science, Clemson,

Yu-Chee Tseng, National Chiao-Tung University, Department of Computer Science and

Information Engineering, Hsin-Chu 300, Taiwan

Jorge Urrutia, Universidad Nacional Autonoma de Mexico, Instituto de Matematicas,

Mexico D.F., Mexico

Thanos Vasilakos, FORTH, Institute of Computer Science, Heraklion, Crete, Greece Jie Wu, Florida Atlantic University, Department of Computer Science and Engineering,

Boca Raton, Florida 33431

Shih-Lin Wu, Chang Gung University, Department of Electrical Engineering, Tao-Yuan,

Taiwan

Jianliang Xu, Hong Kong University of Science and Technology, Department of

Comput-er Science, Clear WatComput-er Bay, Hong Kong

Qing-An Zeng, University of Cincinnati, Department of Electrical Engineering and

Com-puter Science, Cincinnati, Ohio 45221

Jingyuan Zhang, University of Alabama, Department of Computer Science, Tuscaloosa,

Alabama 35487

The past five decades have witnessed startling advances in computing and tion technologies that were stimulated by the availability of faster, more reliable, andcheaper electronic components The design of smaller and more powerful devices en-abled their mobility, which is rapidly changing the way we compute and communicate.For instance, the worldwide number of cellular phone subscribers has quadrupled in thelast five years and has grown to over half a billion (see www.gsmdata.com) Wirelessand mobile networks are emerging as networks of choice, due to the flexibility andfreedom they offer The use of satellite, cellular, radio, sensor, and ad hoc wireless net-works, wireless local area networks (LAN), small portable computers, and personalcommunication systems (PCS) is increasing These networks and devices support a trendtoward computing on the move, known as mobile computing, nomadic computing, orcomputing anywhere anytime The applications of mobile computing and wireless net-works include e-commerce, personal communications, telecommunications, monitoringremote or dangerous environments, national defense (monitoring troop movements),emergency and disaster operations, remote operations of appliances, and wirelessInternet access

communica-This handbook is based on a number of self-contained chapters and provides an tunity for practitioners and researchers to explore the connection between various comput-

oppor-er science techniques and develop solutions to problems that arise in the rapidly emoppor-ergingfield of wireless networks The mobile computing area deals with computing and commu-nication problems that arise in packet radio networks, mobile cellular systems, personalcommunication systems, and wireless local area networks The main direction of the book

is to review various algorithms and protocols that have been developed in this area, withemphasis on the most recent ones

This book is intended for researchers and graduate students in computer science andelectrical engineering, and researchers and developers in the telecommunications industry.Although much has been written, especially recently, in this rapidly growing field, no oth-

er book treats problems in wireless networks from a computer science perspective, though a number of books that follow the engineering approach exist The editor taught acomputer science graduate course with the same title and contents as this handbook, butwas not able to find any book that covered even half of the topics covered here (the courseoutline and transparencies for lectures given by me in the course can be found atwww.site.uottawa.ca/~ivan) This handbook can be used as a textbook and a reference foruse by students, researchers, and developers

al-xvii

MOBILE AND WIRELESS NETWORKING ISSUES

Mobile users do not necessarily use wireless interfaces Instead, they can simply connect

to fixed networks with a wired interface while away from their home or office On the

oth-er hand, a fixed-location usoth-er may use a wireless intoth-erface (via a LAN) in an office ronment Other examples include wireless local loops, which provide fixed wireless ac-cess for voice and data transfer and high-speed Internet access Wireless networks mayuse a fixed infrastructure as a backbone For instance, cellular networks connect a mobilephone to the nearest base station (BS) A BS serves hundreds of mobile users in a givenarea (cell) by allocating frequencies and providing hand-off support BSs are linked (bywireline, fiberline, or wireless microwave links) to base station controllers that provideswitching support to several neighboring BSs and serve thousands of users Controllersare in turn connected to a mobile switching center that is capable of serving more than100,000 users Mobile switching centers are finally connected directly to the public ser-vice telephone network (PSTN) Therefore only the first and perhaps the last connection(if the other user is also using a mobile phone) are normally wireless However, the wire-less link poses design challenges The main difference between wired and wireless links is

envi-in the type of communication Wired lenvi-inks normally provide one-to-one communicationwithout interference, whereas wireless links use one-to-many communication that has aconsiderable noise and interference level and bandwidth limitations Simultaneous wire-less communications require channel separation, where channel may refer to time, fre-quency, or code The channel capacity typically available in wireless systems is much low-

er than what is available in wired networks The regulated frequency spectrum furtherlimits the number of users that can be served concurrently Mobile devices use batterypower, and limited power resources pose further design challenges High noise levelscause larger bit-error rates Forward error correction algorithms or error detectionschemes (such as cyclic redundancy control) followed by buffering and selective retrans-mission must be used One-to-many free space communication is also insecure, since athird party may easily receive the same messages Encryption and decryption proceduresthat provide security require, at the same time, significant power and bandwidth resources.Some wireless networks do not have a fixed infrastructure as a backbone Examples are

ad hoc networks, sensor networks, and wireless LANs Wireless networks of sensors arelikely to be widely deployed in the near future because they greatly extend our ability tomonitor and control the physical environment from remote locations and improve the ac-curacy of information obtained via collaboration among sensor nodes and online informa-tion processing at those nodes Networking these sensors (empowering them with the abil-ity to coordinate among themselves on a larger sensing task) will revolutionizeinformation gathering and processing in many situations Sensors are normally small,cheap devices with limited computing power The typical size of a sensor is about one cu-bic centimeter However, the SmartDust project is attempting to determine whether an au-tonomous sensing, computing, and communication system can be packed into a cubic mil-limeter mote to form the basis of integrated, massively distributed sensor networks.Sensors can be placed in an indoor environment at convenient locations Alternatively,hundreds or thousands of them can be placed in a field For example, sensor nodes can beair-dropped from a helicopter to cover an open field and report on vehicular activity or

troop movement Each node contains one or more of the following sensor types: acoustic,seismic, magnetic, infrared, and visual imaging Once the sensors are in place, each ofthem can detect neighboring sensors and decide about their transmission radius so that thenumber of sensors receiving signals is within some limit This is a nontrivial problem in it-self For instance, a recently published algorithm, in which each node transmits hello mes-

sages using radius kr, where r is a fixed small radius and k is modified until the number of

responses is within limits, is not deterministic, has collision problems, and does not anty the process convergence or connectivity of the obtained network

guar-Sensors should alternate between sleeping and active periods so that the life of eachsensor, and overall network life, is maximized They could be divided into clusters for fur-ther power savings

The detection and reporting of target movements is also a nontrivial problem If everysensor that detects movement reports it to a center, too many messages are generated,causing collision problems and reducing sensor energy too quickly A recently proposedalgorithm (which assumes that each sensor knows its own geographic location and is able

to detect the direction of an object that is “visible”) suggests that all nodes whose boring nodes lie on the same side of a straight line from the node to the detected objectshould report the object’s presence It was expected that there would be exactly two suchnodes (located at tangents from the object to the convex hull of the sensors) This solution,however, may activate more sensors (the criteria can be satisfied for more nodes) or maynot activate any sensor at all (for example, when the object is located inside the convexhull of the sensors) Even when exactly two such sensors are selected, the sensors could betoo close to the line segment between them, causing computational errors in object loca-tion based on two object directions An alternative solution is to select only locally ex-treme sensors in four directions (N, S, E, and W) or possibly eight directions (including

neigh-NW, NE, SW, and SE), and to combine the data obtained along the paths from them to acenter that collects the data Sensors that combine data will only forward “significant” im-provements in the object’s location We can envision similar applications for monitoringenvironmental pollutants and their source and direction of movement Several computerscience projects along these lines (e.g., sensor information technology, diffusion-basednetworking, mobile scripts for target tracking, queries for collaborative signal processing),are currently ongoing (www.darpa.mil/ito/research/sensit, http://netweb.usc.edu/scadds,http://strange.arl.psu.edu/RSN, www.cs.columbia.edu/dcc/asn, etc.)

A similar wireless network technology that has received significant attention in recentyears is the ad hoc network Mobile ad hoc networks consist of wireless hosts that com-municate with each other in the absence of a fixed infrastructure They are used in disasterrelief, conferences, and battlefield environments Wireless LANs are designed to operate

in a small area such as a building or office complex The communication between twohosts in wireless LANs, sensor, and ad hoc networks is not always direct Hosts in wirelessLANs, sensor, and ad hoc networks use the same frequency for communication Direct (orsingle-hop) transmission between any two hosts may require significant power (powernormally decreases with the square or higher degree of distance between hosts) and isprone to collisions with other such transmissions Thus, two hosts normally communicatevia other hosts in the network (multihop communication) The solution to this involvessolving routing problems Collisions are difficult to detect because of the hidden station

problem Two hosts that do not communicate directly may simultaneously transmit sages to a common neighbor, causing collision Mobile networks should provide supportfor routing by maintaining communication during mobility In order to maintain an ongo-ing routing task (e.g., ongoing phone call) or to facilitate route establishment or paging,mobile networks must also provide support for location management, that is, keepingtrack of the host location.

mes-The performance of wireless networks greatly depends on the choice of the mediumaccess control (MAC) scheme For instance, MAC protocols used in cellular networks inthe United States and Europe differ The IS-95 standard used in the United States usescode division multiple access (CDMA), whereas the GSM standard used in Europe usesTDMA (time division multiple access) on the top of FDMA (frequency DMA) CDMAprovides more channels but at the expense of more noise and interference These differ-ences prevent interoperability and global mobility, and also create obstacles to standard-ization of the third generation (3G) of cellular systems

Ad hoc, sensor, and wireless local area networks may use the IEEE 802.11 standard formedium access, in which hosts wait for a randomly selected number of transmission-free slots (back-off counter) before transmitting a message Other standards (e.g.,HIPERLAN) are also available One emerging MAC layer technology is Bluetooth(www.bluetooth.net) It provides short-range (about 10 meters), low-cost wireless connec-tivity among hosts such as computers, printers, scanners, PCs, or sensors In Bluetooth en-vironments, hosts are organized into piconets, with one host in each piconet serving asmaster and a limited number (up to seven) of slave hosts directly linked to the master.Satellites are in wide use for broadcast services and long distance and internationalphone services to stationary users Low-earth orbit (LEO) satellite systems, such asTeledesic (expected to be operational in 2003 and consisting of 288 satellites), will pro-vide mobile communications to every point on earth Satellites are organized in concentricorbits and maintain links with several satellites in neighboring orbits and nearest satellites

in the same orbit

Wireless ATM (asynchronous transfer mode) is an emerging technology for support ofvoice and data transmission ATM connections rely partly on wireless networks Newchallenges in the design of wireless ATM include varying channel characteristics, quality

of service support, and support of end-to-end ATM connection as the user moves from onelocation to the other ATM is a connection-oriented technology, so after a mobile user’smove to a new location, connection rerouting has to be performed In a cellular network orATM connections, location management schemes are needed in order to provide updatedlocation information when a connection to a mobile user needs to be set up (routed) orrerouted

The Wireless Application Protocol (WAP, www.wapforum.org) allows the development

of applications that are independent of the underlying wireless access technology, andadapts existing website contents for transmission over wireless links and display on mo-bile devices WAP architecture consists of a mobile client that sends an encoded request to

a gateway and receives an encoded response from the gateway via a wireless network Thegateway, in turn, sends a request to a server and receives a response (content) from it over

a wired network WAP consist of application, session, transaction, security, transport, andwireless layers Mobile devices require mobile operating systems (OSs) that are small in

size and memory (e.g., 300 KB) and are able to operate with little processing power andsatisfy real-time requirements, such as voice traffic.

BRIEF OUTLINE OF THIS HANDBOOK

The wide range of topics in this handbook makes it an excellent reference on wireless works and mobile computing Because each chapter is fully self-contained, readers can fo-cus on the topics that most interest them Most of the chapters (if not all) in this handbookhave great practical utility The handbook emphasizes computer science aspects, includingimplementation Mathematical and engineering aspects are also represented in some chap-ters, since it is difficult to separate clearly all the issues among the three areas Even whenother aspects are clearly dominant, they are a good supplement to the rest of the hand-book

net-A short outline of the material presented in each of the chapters of this volume follows.The purpose is to identify the contents and also to aid diverse readers in assessing justwhat chapters are pertinent to their pursuits and desires Each chapter should provide thereader with the equivalent of consulting an expert in a given discipline by summarizingthe state of the art, interpreting trends, and providing pointers to further reading

It is a challenging task to clearly divide chapters into discrete areas because of laps One such classification that will be attempted here is to divide the chapters into fivemain research areas: multiple access schemes, cellular networks, data communication,multihop networks, and mobile computing Many chapters deal with more than one ofthese areas, so clear separation is difficult As a quick guide through the chapter topics,the first half of the chapters deal with multiple access schemes, data communication, andcellular networks; and other half deal with multihop networks and mobile computing Weshall now elaborate in more detail on each chapter, and try to group chapters into the fivelisted areas

over-Cellular networks were certainly the first and so far most successful commercial cation of wireless networks The research in this area is hence more advanced than in theothers Nevertheless, it remains a hot research topic because of emerging technologiessuch as the third generation (3G) of mobile phone systems Chapters 1–5 deal primarilywith cellular networks

appli-Chapter 1 discusses handoff, which is the mechanism for transferring an ongoing callfrom one base station to another as a user moves through the coverage area of a cellularsystem It must be fast and efficient to prevent the quality of service from degenerating to

an unacceptable level Admission control is a related problem, in which the radio resourcemanagement system has to decide if a new call arrival or a request for service or handoffmay be allowed into the system Handoffs are normally prioritized with respect to newcalls Four conventional handoff schemes in a voice-based, single traffic system (nonpri-ority schemes, priority schemes, handoff call queuing schemes, and originating and hand-off calls queuing schemes) are summarized in this chapter In addition, two handoffschemes with and without preemptive priority procedures for integrated voice and datawireless mobile networks are also covered in detail

Mobile phone users move among base stations but do not always register with the

cur-rent base station, to avoid communication overhead and excessive battery use There exists

a traoff between the frequency of location update by the mobile phone user and the lay in locating a user when a phone call is made Chapter 2 reviews existing solutions tothe location management problem

de-Chapters 3, 4, and 5 discuss the media access control problem in cellular networks.They are therefore at the intersection of the first two research areas of this handbook—multiple access schemes and cellular networks Media access control in cellular networks

is achieved primarily by assigning different frequencies to users that are connected to thesame or neighboring base stations, and repeating the same frequencies when the corre-sponding base stations are sufficiently far apart to avoid or minimize the interference.Chapter 3 describes fixed-channel assignment schemes in cellular networks, with theemphasis on recent heuristic algorithms that apply genetic algorithms, tabu search, neuralnetworks, fuzzy logic, and other heuristics in solving problems Channel assignment isgenerally classified into fixed and dynamic In fixed channel assignment (FCA), channelsare nominally assigned in advance according to the predetermined estimated traffic inten-sity at various base stations In dynamic channel assignment (DCA), channels are as-signed dynamically as calls arrive It is more efficient in terms of channel usage, but re-quires more complex and time-consuming control Hybrid channel assignment (HCA)combines the two approaches by dividing the frequencies into two separate ranges, one forFCA and other for DCA In borrowing channel assignment (BCA), the channel assign-ment is initially fixed If there are incoming calls for a cell whose channels are all occu-pied, the cell borrows channels from its neighboring cells and thus call blocking is pre-vented

Cochannel interference is the most critical of all interference that occurs in cellular dio The same channel cannot be assigned to two users that are connected to the same ortwo “close” base stations since such cochannel interference is likely to cause an unaccept-able signal-to-noise ratio The minimal distance between two base stations that can use thesame channel is called the reuse distance If this is the only type of interference consid-ered, the channel assignment problem reduces to a multicoloring problem In a multicolor-ing problem defined on a graph, each base station is demanding a certain number of col-ors (that is, frequencies), so that any two neighboring nodes get a disjoint set of colors(and, of course, colors assigned to each node are all distinct) When translated to cellularsystems, nodes are base stations, and two base stations are “neighbors” in graph terms ifthe distance between then is less than the reuse distance Chapter 4 studies this simplifiedversion of the famous graph coloring problem that is known to be computationally diffi-cult Algorithms and lower bounds for this problem (including FCA, DCA, BCA, andHCA problem statements) are surveyed

ra-The secondary source of interference in cellular systems is adjacent channel ence The filters for each channel at base stations are not ideal, and allow the signals fromneighboring channels, with reduced strength, to generate noise In a general problem

interfer-statement, two base stations (i.e., cells) that are at a distance i (where i is the minimal

number of cell crossings between two cells) cannot be assigned two frequencies that differ

by less than c i The cosite constraint c0indicates the channel separation at the same base

station, which is normally high compared to other constraints The intersite constraints c i (i > 0) most often take smaller values, especially one or two An intersite constraint of one

indicates that the two base stations must use distinct frequencies, whereas zero constraintindicates that the two cells may reuse frequencies More precisely, in a good channel as-signment, they actually should reuse the frequencies Chapter 5 gives an overview of algo-rithms and lower bounds for this problem It also discusses relevant results on graph label-ing, which form the basis of many of the algorithms

Several chapters deal with multiple access schemes Since the wireless medium is herently a shared resource, controlling channel access becomes a central theme that deter-mines the system capacity, complexity, and cost Chapter 6 focuses on the design and im-plementation of media access control (MAC) protocols for cellular telephony, wirelessATM, and ad hoc networks Fundamental MAC protocols include frequency division mul-tiple access (FDMA), time division multiple access (TDMA), code division multiple ac-cess (CDMA), and random access schemes such as ALOHA and carrier sense multiple ac-cess (CSMA)

in-Chapter 7 discusses the integration of voice and data traffic in wireless networks Itconcentrates on Bluetooth technology (the de facto standard for wireless personal areanetworks), IEEE 802.11 technology (the main standard for wireless local area networks),and the UMTS technology for third generation cellular systems

Fairness among mobile or wireless users implies that the allocated channel bandwidth

is in proportion to the “weights” of the users Fair queuing in the wireless domain posessignificant challenges due to unique issues in the wireless channel such as location-depen-dent and bursty channel error Hence, it is imperative to provide fair channel accessamong multiple contending hosts Chapter 8 identifies key issues in wireless fair queuing,defines a wireless fair service model, and surveys algorithms from contemporary litera-ture

Chapters 9 and 10 deal with organization issues for medium access in radio networks,which are distributed systems with no central arbiter, consisting of n radio transceivers,also called stations The wireless environment is single-hop one, meaning that each station

is able to hear a transmission from any other station The time is slotted, and all sions occur at slot boundaries Chapter 9 describes how each station can assign to itself a

transmis-unique identifier in the range [1, n] so that the i-th user is able to transmit the message in the i-th slot This provides collision-free TDMA transmission in a round robin fashion.

The algorithms are distributed, and their analysis is based on combinatorial facts of mial distribution, tree partitions, and graphs Initialization protocols with and without col-lision detection capabilities, and using one of several channels for communication, arepresented The leader election problem designates one of the stations as leader Chapter 10surveys recent protocols on the leader election problem in single-hop, single-channel ra-dio networks

bino-Chapters 10–14 deal primarily with data communication issues in wireless networks,with considerable overlap with all other listed areas

Mobile wireless environments are characterized by asymmetric communication Thedownlink communication from base station, satellite, or other server is much greater thanthe uplink communication capacity In broadcast, data are sent simultaneously to all usersresiding in the broadcast area Each user in a data broadcast problem has a list of desiredfiles or data it wants to receive from the server The order and frequency for each file ordatum that is broadcast should take access efficiency and power conservation into ac-

count Access efficiency concerns how fast a request is satisfied, whereas power tion concerns how to reduce a mobile client’s power consumption when it is accessing thedata it wants Chapter 11 surveys various techniques and problem formulations for wire-less data broadcast, sometimes also refereed to as broadcast scheduling.

conserva-Digital broadcasting systems are expected to replace current FM radio and televisiontechnology Chapter 12 considers the design of DAB (digital audio broadcasting) net-works The DAB system transmits whole ensembles consisting of multiple radio programsand other data services, and allows an ensemble to be transmitted on a single channel even

if the corresponding transmitters may interfere The task is to arrange services into a lection of ensembles for each request area, and to assign channels to the resulting ensem-bles The problem can be formulated as the combined bin packing and graph coloringproblem Several basic heuristics, lower bounding algorithms, and the tabu search solutionare described

col-With the increasing number of wireless and mobile devices using the Internet, searchers have been studying the impact of wireless networking technologies on the dif-ferent layers of the network protocol stack Chapter 13 focuses on the transport layer inmicrocell and macrocell wireless networks The task in the transport layer is to organizethe speed of transmissions, acknowledgment, and possible retransmissions of every pack-

re-et of a data transfer It deals primarily with the nre-etwork congestion problem The uniquecharacteristics of wireless networks that result in poor performance for existing protocolstandards are identified (such as reduced bandwidth, which needs to be distinguishedfrom congestion), and approaches that have been proposed to address these characteristicsare surveyed

Chapter 14 focuses on security and fraud detection problems in mobile and wirelessnetworks, and presents some solutions to several aspects of the security problem, such asauthentication of mobile users and fraud detection in mobile phone operations Further in-creases in network security are necessary before the promise of mobile telecommunica-tion can be fulfilled

Chapters 14–24 deal with multihop wireless networks Their primary characteristic isthat mobile or wireless stations, phones, users, sensors, or other devices (let us call themnodes) cannot communicate directly with any other node in the network Thus, they com-municate with each other via other nodes, through several hops The network is then mod-eled by a graph where two nodes are linked if and only if they can directly communicate

If that graph is a complete graph (where each node can directly communicate to any othernode), the network is called a single-hop one Cellular networks and transport protocolsalso deal with multihop networks, but the problems studied and solution presented are notsignificantly based on the underlying graph model

Ad hoc networks are a key to the evolution of wireless networks They are typicallycomposed of equal nodes that communicate over wireless links without any central con-trol Ad hoc wireless networks inherit the traditional problems of wireless and mobilecommunications, such as bandwidth optimization, power control, and transmission qualityenhancement In addition, the multihop nature and the lack of fixed infrastructure bringnew research problems such as configuration advertising, discovery and maintenance, aswell as ad hoc addressing and self-routing Many different approaches and protocols havebeen proposed and there are even multiple standardization efforts within the Internet En-

gineering Task Force, as well as academic and industrial projects Chapter 15 focuses onthe state of the art in mobile ad hoc networks It highlights some of the emerging tech-nologies, protocols, and approaches (at different layers) for realizing network services forusers on the move in areas with possibly no preexisting communications infrastructure.People-based networks, where information is transmitted using “people” (i.e., personaldevices such as personal digital assistants), are also discussed.

To avoid interference of signals arriving from several neighbors to a single host, or multaneous transmissions from two neighboring hosts, each host should create its owntransmission schedule That is, each host should decide which time slots are available forcollision-free transmissions Chapter 16 explores the computational and algorithmic com-plexity of broadcast scheduling, which, in general form, is an NP-complete problem Thechapter reviews existing broadcast scheduling approximation, off-line and on-line, andcentralized and distributed algorithms, and discusses their effect on the quality of theschedules produced

si-In a wireless network, routing the message (finding a path between a source and a tination node) is a basic data communication protocol A mobile ad hoc network consists

des-of a set des-of mobile hosts capable des-of communicating with each other without the assistance

of base stations Chapter 17 reviews the existing routing algorithms for networks ing of nodes that do not have information about their geographic position

consist-Recently, the location of a sensor or station was made feasible by adding a GPS power, small-size receiver that is able of determining its location (latitude, longitude, andheight) within a few millimeters by cooperating with existing satellite and auxiliary earthnetworks GPS also provides global timing to stations Position information enables devel-opment of localized routing methods (greedy routing decisions are made at each node,based solely on the knowledge of positions of neighbors and the destination, with consid-erable savings in communication overhead and with guaranteed delivery provided locationupdate schemes are efficient for a given movement pattern) When GPS is not available,the relative position of neighboring nodes may be determined based on strength of signalsfrom neigboring nodes, or some other alternative means Chapter 18 surveys routing algo-rithms in communication networks, where nodes are aware of their geographic positionand those of their neigboring nodes The algorithms take advantage of geometric proper-ties of planar networks, constructing a planar subgraph of a given wireless network Guar-anteed delivery is a salient property of the algorithms, assuming destination location is ac-curate and the network is modeled by unit graphs In a unit graph, all nodes have the sametransmission radius, and two nodes can directly communicate if and only if their distance

low-is less than that radius

Chapter 19 surveys energy-efficient routing protocols for wireless ad hoc networks Itincludes evaluation of energy consumption in ad hoc routing protocols, localized routingalgorithms that optimize based on power and other metrics, network topology generationdesigned to optimize power consumption, routing algorithms that balance power con-sumption among all network nodes, and algorithms that maximize nodes’ lifetimes

A set of nodes in a network is dominating if all the nodes in the system are either in theset or neighbors of nodes in the set Chapter 20 reviews simple and efficient distributed al-gorithms for calculating a connected dominating set in ad hoc wireless networks, whereconnections of nodes are determined by their geographic distances Applications of domi-

nating sets in reducing the cost of routing, multicasting, and broadcasting are also cussed.

dis-Chapter 21 reviews research on routing in ad hoc and sensor wireless networks in thelight of node mobility, changes in node activity, and availability of methods to determinethe absolute or relative coordinates of each node Various approaches in the literature areclassified according to some criteria Mobility is apparently a very difficult problem tohandle in ad hoc networks, and all proposed solutions have significant drawbacks Addi-tional problems arise with “sleep” period operation, that is, changes in a node’s activitystatus with or without mobility Although significant progress has been made on routingwith a known destination location, issuing location updates to enable efficient routing re-quires further investigation

Chapter 22 surveys communication-related issues arising in the context of low earthorbit (LEO) satellite constellations In particular, it studies the impact of the predictablemovement of the satellites on the techniques used in topological design, routing, andhandover strategies

In a multicasting problem, a message is to be sent from a node to several other nodes inthe network Chapter 23 briefly reviews multicasting methods that were proposed in the lit-erature for wired networks, and then gradually relaxes the requirement that all nodes be sta-tionary, discussing multicast protocols for cellular networks (characterized by a fixed infra-structure with mobile end nodes) and ad hoc networks (infrastructureless mobile networks) Broadcasting is the task of forwarding a message from a source (or central facility) toall the nodes in the network Chapter 24 reviews broadcasting algorithms in radio net-works, under different communication scenarios and different amounts of knowledge ofthe network The chapter primarily deals with the worst-case analysis of algorithms.Chapters 25–28 deal primarily with mobile computing or computing and communica-tion protocol issues in the presence of node mobility

Chapter 25 presents the basic characteristics of mobile IP, which is a protocol that lows transparent routing of IP datagrams to mobile nodes on the Internet Each mobilenode is always identified by its home address, regardless of its current point of attachment

al-to the Internet When away from its home, information about its current point of ment to the Internet is provided through a care-of address associated with the node Thehome agent sends datagrams destined for the mobile node through a tunnel to the care-ofaddress After arriving at the end of the tunnel, each datagram is then delivered to the mo-bile node Routing, security, and management issues are discussed based on the most re-cent activities of the relevant standardization bodies

attach-Chapter 26 surveys data management schemes in wireless mobile environments bile computing can possibly be viewed as a variation of traditional distributed computingfrom the data management point of view In general, there are two possible scenarios Inthe first, the entire database is distributed only among the wired components, e.g., the mo-bile switching stations (MSS), each base station managing its own share of the databasewith the additional capability of locating the components of the databases that are not lo-cally available In the second approach, the entire database is distributed over both thewired and wireless components of the system The functionality of a database manage-ment system depends on the design of database and replication of data schemes These is-sues are handled, in some form or other, via caching data in the mobile units and periodi-

Mo-cally validating this data using different techniques The protocols and frequency of dation of the data have a profound influence on the performance of data management inmobile environments.

vali-The advent of distributed computing has had a major influence in the computing try in recent years, witnessed by the growth of mobile computers and networked comput-ing systems The desire to share resources, to parcel out computing tasks among severaldifferent hosts, and place applications on machines most suitable to their needs, has led todistributed programming systems such as CORBA and DCOM, which predominate in themarketplace Pervasive computing can be defined as access to information and softwareapplications anytime and anywhere Users are mobile and services are provided by collec-tions of distributed components collaborating together Recent advances in mobile com-puting, service discovery, and distributed computing are key technologies to support per-vasive computing Chapter 27 is about software technologies used to address problems inmobile, distributed, and pervasive computing It reviews characteristics, software architec-ture, and key open communication technologies (service discovery and distributed com-puting) to support pervasive computing

indus-Recent advances in wireless and mobile computing, and inexpensive, portable deviceshave resulted in the emergence of indoor wireless networks Chapter 28 focuses on chal-lenges specific to this environment It discusses design issues and options for the physicallayer, and dwells at length on a few media access control (MAC) layer protocols that havebeen proposed for the indoor environment It is shown how these problems have beendealt with in some popular and well-accepted technologies, namely, Wireless LAN (IEEE802.11), HomeRF and Bluetooth Network topology and self-organization of such net-works, with special reference to Bluetooth, which has very interesting topology construc-tion problems, is also discussed

RECOMMENDED READING

Each chapter in the handbook is accompanied by its own reference section However, it isnecessary for the reader to refer to journals and conference proceedings to keep up withthe recent developments in the field

Some of the important journals that publish articles in the area of wireless networksand mobile computing in the field are:

앫 ACM Computer Communication Review (www.acm.org)

앫 ACM Mobile Computing and Communications Review

(http://www.acm.org/sigmo-bile/MC2R)

앫 Communications of the ACM (www.acm.org)

앫 IEEE/ACM Transactions on Networking (www.ton.cc.gatech.edu)

앫 IEEE Communications Magazine (www.computer.org)

앫 IEEE Pervasive Computing (www.computer.org/pervasive)

앫 IEEE Transactions on Mobile Communications (www.computer.org/tmc)

앫 IEEE Transactions on Parallel and Distributed Systems (www.computer.org)

앫 IEEE Transactions on Selected Areas in Communication (www.computer.org)

앫 IEEE Transactions on Vehicular Technology (www.computer.org)

앫 IEEE Transactions on Wireless Communications (www.ee.ust.hk/~eekhaled)

앫 International Journal of Wireless Information Networks (www.baltzer.nl)

앫 IEEE Communication Letters (www.computer.org)

앫 International Journal of Communication Systems

앫 International Journal of Satellite Communications

앫 Journal of Parallel and Distributed Computing

앫 Mobile Networks and Applications (www.baltzer.nl/monet)

앫 Wireless Communications and Mobile Computing (www.wiley.com)

앫 Wireless Networks (www.acm.org/journals/125.html)

앫 Wireless Personal Communication (www.baltzer.nl)

The reader is also encouraged to refer to the proceedings of some of the main eventsand conferences that cover the topics, for example:

앫 ACM International Conference on Mobile Computing and Networking MOBICOM(www.acm.org/sigmobile)

앫 International Workshop on Discrete Algorithms and Methods for Mobile Computingand Communications (DIAL M for Mobility)

앫 International Workshop on Wireless Mobile Multimedia, WoW MoM

앫 International Workshop on Modeling, Analysis and Simulation of Wireless and bile Systems, MSWiM

Mo-앫 ACM Symposium on Mobile Ad Hoc Networking and Computing, MobiHoc

앫 ACM Wireless Mobile Internet Workshop

앫 IEEE INFOCOM (www.ieee-infocom.org)

앫 IEEE International Parallel and Distributed Processing Symposium, IPDPS(www.ipdps.org)

앫 IEEE Vehicular Technology Conference, VTC

앫 IEEE Hawaii International Conference on System Sciences, Software TechnologyTrack (www.hicss.org)

앫 International Conference on Parallel Processing

앫 IEEE International Conference on Distributed Computing and Systems

앫 IASTED International Conference on Parallel and Distributed Computing and tems (www.iasted.com/confrences)

Sys-앫 IEEE International Conference on Computer Communications and Networks,

ICC-CN (www.icccn.cstp.umkc.edu)

앫 International Conference on Communications in Computing, CIC (www.cs.utep.edu/~cic)

앫 IEEE GLOBECOM

앫 IEEE Symposium on Computers and Communications (www.comsoc.org/iscc)

앫 IEEE International Conference on Universal Personal Communications

The Internet is becoming the major source of information in this area, since the ity of researchers put their own papers on their web pages From my own experience, theprimary source of information is the research index that can be found athttp://citeseer.nj.nec.com/cs This is a citation database that links papers according to theirsubject and mutual citations, and provides the web and e-mail addresses for many of theauthors (and, of course, Internet search engines can locate most of the remaining ones)

major-ACKNOWLEDGMENTS

The editor is grateful to all the authors for their contributions to the quality of this book The assistance of reviewers for all chapters is also greatly appreciated The Univer-sity of Ottawa and Universidad National Autonoma de Mexico provided an ideal workingenvironment for the preparation of this handbook, including computer facilities for effi-cient Internet search, communication by electronic mail, and writing my own contribu-tions

hand-The editor is thankful to Dr Albert Zomaya, editor of the Parallel and DistributedComputing book series at Wiley, for his support and encouragement in publishing thishandbook The editor also appreciates the support of Dr Stephan Olariu for encouragingpublication of this handbook by Wiley instead of other publishers that also offered con-tracts Dr Philip Meyler, editor at Wiley, also deserves special mention for his timely andprofessional cooperation, and for his decisive support of this project

Finally, I thank my children Milos and Milica and my wife Natasa for making this fort worthwhile and for their patience during the numerous hours at home that I spent infront of the computer

ef-I hope that the readers will find this handbook informative and worth reading ments from readers will be greatly appreciated

Com-SITE, University of Ottawa, Ottawa, Ontario, Canada IVANSTOJMENOVIC´Ivan@site.uottawa.ca

ivan@leibniz.iimas.unam.mx; www.site.uottawa.ca/~ivan

DISCA, IIMAS, UNAM, Mexico D.F., Mexico

April 2001

WIRELESS NETWORKS AND MOBILE COMPUTING

CHAPTER 1

Handoff in Wireless Mobile Networks

QING-AN ZENG and DHARMA P AGRAWAL

Department of Electrical Engineering and Computer Science,

University of Cincinnati

Mobility is the most important feature of a wireless cellular communication system ally, continuous service is achieved by supporting handoff (or handover) from one cell toanother Handoff is the process of changing the channel (frequency, time slot, spreadingcode, or combination of them) associated with the current connection while a call is inprogress It is often initiated either by crossing a cell boundary or by a deterioration inquality of the signal in the current channel Handoff is divided into two broad categories—hard and soft handoffs They are also characterized by “break before make” and “make be-fore break.” In hard handoffs, current resources are released before new resources areused; in soft handoffs, both existing and new resources are used during the handoffprocess Poorly designed handoff schemes tend to generate very heavy signaling trafficand, thereby, a dramatic decrease in quality of service (QoS) (In this chapter, a handoff isassumed to occur only at the cell boundary.) The reason why handoffs are critical in cellu-lar communication systems is that neighboring cells are always using a disjoint subset offrequency bands, so negotiations must take place between the mobile station (MS), thecurrent serving base station (BS), and the next potential BS Other related issues, such asdecision making and priority strategies during overloading, might influence the overallperformance

Usu-In the next section, we introduce different types of possible handoffs Usu-In Section 1.3,

we describe different handoff initiation processes The types of handoff decisions arebriefly described in Section 1.4 and some selected representative handoff schemes are pre-sented in Section 1.5 Finally, Section 1.6 summarizes the chapter

Handoffs are broadly classified into two categories—hard and soft handoffs Usually, thehard handoff can be further divided into two different types—intra- and intercell handoffs.The soft handoff can also be divided into two different types—multiway soft handoffs andsofter handoffs In this chapter, we focus primarily on the hard handoff

1

Copyright © 2002 John Wiley & Sons, Inc ISBNs: 0-471-41902-8 (Paper); 0-471-22456-1 (Electronic)

A hard handoff is essentially a “break before make” connection Under the control of theMSC, the BS hands off the MS’s call to another cell and then drops the call In a hard hand-off, the link to the prior BS is terminated before or as the user is transferred to the new cell’sBS; the MS is linked to no more than one BS at any given time Hard handoff is primarilyused in FDMA (frequency division multiple access) and TDMA (time division multiple ac-cess), where different frequency ranges are used in adjacent channels in order to minimizechannel interference So when the MS moves from one BS to another BS, it becomes im-possible for it to communicate with both BSs (since different frequencies are used) Figure1.1 illustrates hard handoff between the MS and the BSs.

A hard handoff occurs when the old connection is broken before a new connection is vated The performance evaluation of a hard handoff is based on various initiation criteria[1, 3, 13] It is assumed that the signal is averaged over time, so that rapid fluctuations due

acti-to the multipath nature of the radio environment can be eliminated Numerous studieshave been done to determine the shape as well as the length of the averaging window andthe older measurements may be unreliable Figure 1.2 shows a MS moving from one BS(BS1) to another (BS2) The mean signal strength of BS1decreases as the MS moves awayfrom it Similarly, the mean signal strength of BS2increases as the MS approaches it Thisfigure is used to explain various approaches described in the following subsection

1.3.1 Relative Signal Strength

This method selects the strongest received BS at all times The decision is based on amean measurement of the received signal In Figure 1.2, the handoff would occur at posi-tion A This method is observed to provoke too many unnecessary handoffs, even whenthe signal of the current BS is still at an acceptable level

1.3.2 Relative Signal Strength with Threshold

This method allows a MS to hand off only if the current signal is sufficiently weak (lessthan threshold) and the other is the stronger of the two The effect of the threshold depends

Figure 1.1 Hard handoff between the MS and BSs

on its relative value as compared to the signal strengths of the two BSs at the point at

which they are equal If the threshold is higher than this value, say T1in Figure 1.2, thisscheme performs exactly like the relative signal strength scheme, so the handoff occurs at

position A If the threshold is lower than this value, say T2in Figure 1.2, the MS would lay handoff until the current signal level crosses the threshold at position B In the case of

de-T3, the delay may be so long that the MS drifts too far into the new cell This reduces the

quality of the communication link from BS1and may result in a dropped call In addition,this results in additional interference to cochannel users Thus, this scheme may createoverlapping cell coverage areas A threshold is not used alone in actual practice becauseits effectiveness depends on prior knowledge of the crossover signal strength between thecurrent and candidate BSs

1.3.3 Relative Signal Strength with Hysteresis

This scheme allows a user to hand off only if the new BS is sufficiently stronger (by a

hys-teresis margin, h in Figure 1.2) than the current one In this case, the handoff would occur

at point C This technique prevents the so-called ping-pong effect, the repeated handoffbetween two BSs caused by rapid fluctuations in the received signal strengths from bothBSs The first handoff, however, may be unnecessary if the serving BS is sufficientlystrong

1.3.4 Relative Signal Strength with Hysteresis and Threshold

This scheme hands a MS over to a new BS only if the current signal level drops below athreshold and the target BS is stronger than the current one by a given hysteresis margin

In Figure 1.2, the handoff would occur at point D if the threshold is T

T2

T3

Figure 1.2 Signal strength and hysteresis between two adjacent BSs for potential handoff

1.3.5 Prediction Techniques

Prediction techniques base the handoff decision on the expected future value of the ceived signal strength A technique has been proposed and simulated to indicate better re-sults, in terms of reduction in the number of unnecessary handoffs, than the relative signalstrength, both without and with hysteresis, and threshold methods

There are numerous methods for performing handoff, at least as many as the kinds of stateinformation that have been defined for MSs, as well as the kinds of network entities thatmaintain the state information [4] The decision-making process of handoff may be cen-tralized or decentralized (i.e., the handoff decision may be made at the MS or network).From the decision process point of view, one can find at least three different kinds ofhandoff decisions

1.4.1 Network-Controlled Handoff

In a network-controlled handoff protocol, the network makes a handoff decision based onthe measurements of the MSs at a number of BSs In general, the handoff process (includ-ing data transmission, channel switching, and network switching) takes 100–200 ms In-formation about the signal quality for all users is available at a single point in the networkthat facilitates appropriate resource allocation Network-controlled handoff is used infirst-generation analog systems such as AMPS (advanced mobile phone system), TACS(total access communication system), and NMT (advanced mobile phone system)

1.4.3 Mobile-Controlled Handoff

In mobile-controlled handoff, each MS is completely in control of the handoff process.This type of handoff has a short reaction time (on the order of 0.1 second) MS measuresthe signal strengths from surrounding BSs and interference levels on all channels A hand-off can be initiated if the signal strength of the serving BS is lower than that of another BS

by a certain threshold

In urban mobile cellular radio systems, especially when the cell size becomes relativelysmall, the handoff procedure has a significant impact on system performance Blocking

probability of originating calls and the forced termination probability of ongoing calls arethe primary criteria for indicating performance In this section, we describe several exist-ing traffic models and handoff schemes.

intro-1.5.1.1 Hong and Rappaport’s Traffic Model (Two-Dimensional)

Hong and Rappaport propose a traffic model for a hexagonal cell (approximated by a cle) [5] They assume that the vehicles are spread evenly over the service area; thus, the lo-cation of a vehicle when a call is initiated by the user is uniformly distributed in the cell.They also assume that a vehicle initiating a call moves from the current location in any di-rection with equal probability and that this direction does not change while the vehicle re-mains in the cell

cir-From these assumptions they showed that the arrival rate of handoff calls is

re-B O= the blocking probability of originating calls

P f = the probability of handoff failure

O= the arrival rate of originating calls in a cell

The probability density function (pdf) of channel holding time T in a cell is derived as

F Tn (t) = the cumulative distribution function (cdf) of the time T n

F Th (t) = the cdf of the time T h

1/C= the average call duration

C= P h (1 – B O )/[1 – P hh (1 – P f)]

1.5.1.2 El-Dolil et al.’s Traffic Model (One-Dimensional)

An extension of Hong and Rappaport’s traffic model to the case of highway microcellularradio network has been done by El-Dolil et al [6] The highway is segmented into micro-cells with small BSs radiating cigar-shaped mobile radio signals along the highway Withthese assumptions, they showed that the arrival rate of handoff calls is

where

P hi = the probability that a MS needs a handoff in cell i

R cj = the average rate of total calls carried in cell j

R sh= the rate of successful handoffs

The pdf of channel holding time T in a cell is derived as

f T (t) = 冢 冣e–(C+ni)t+ 冢 冣e–(C+h)t (1.4)

where

1/ni= the average channel holding time in cell i for a originating call

1/h= the average channel holding time for a handoff call

G = the ratio of the offered rate of handoff requests to that of originating calls

1.5.1.3 Steele and Nofal’s Traffic Model (Two-Dimensional)

Steele and Nofal [7] studied a traffic model based on city street microcells, catering topedestrians making calls while walking along a street From their assumptions, theyshowed that the arrival rate of handoff calls is

H= m=1冱6 [
O(1 – B O ) P h +
h (1 – P f ) P hh] (1.5)where

= the fraction of handoff calls to the current cell from the adjacent cells

h= 3
O(1 – B O ) P I

P I= the probability that a new call that is not blocked will require at least one handoff

The average channel holding time T in a cell is

P delay = P cross P d, the proportion of pedestrians leaving the cell by crossing the road

P d= the probability that a pedestrian would be delayed when he crosses the road

=
H(1 – P f)/[
H(1 – P f) +
O(1 – B O)]

1.5.1.4 Xie and Kuek’s Traffic Model (One- and Two-Dimensional)

This model assumes a uniform density of mobile users throughout an area and that a user

is equally likely to move in any direction with respect to the cell border From this sumption, Xie and Kuek [8] showed that the arrival rate of handoff calls is

where

E[C] = the average number of calls in a cell

c—dwell= the outgoing rate of mobile users

The average channel holding time T in a cell is

T

苶 = (1.8)

1.5.1.5 Zeng et al.’s Approximated Traffic Model (Any Dimensional)

Zeng et al.’s model is based on Xie and Kuek’s traffic model [9] Using Little’s formula,when the blocking probability of originating calls and the forced termination probability

of handoff calls are small, the average numbers of occupied channels E[C] is

approximat-ed by

where 1/is the average channel holding time in a cell

Therefore, the arrival rate of handoff calls is

Xie and Kuek focused on the pdf of the speed of cell-crossing mobiles and refined vious results by making use of biased sampling The distribution of mobile speeds ofhandoff calls used in Hong and Rappaport’s traffic model has been adjusted by using

f *(v) = (1.11)

where f ( v) is the pdf of the random variable V (speed of mobile users), and E[V] is the

av-erage of the random variable V.

f *(v) leads to the conclusion that the probability of handoff in Hong and Rappaport’s

traffic model is a pessimistic one, because the speed distribution of handoff calls are notthe same as the overall speed distribution of all mobile users

Steele’s traffic model is not adaptive for an irregular cell and vehicular users In Zeng

et al.’s approximated traffic model, actual deviation from Xie and Kuek’s traffic model isrelatively small when the blocking probability of originating calls and the forced termina-tion probability of handoff calls are small

1.5.2 Handoff Schemes in Single Traffic Systems

In this section, we introduce nonpriority, priority, and queuing handoff schemes for a gle traffic system such as either a voice or a data system [6–14] Before introducing these

sin-schemes, we assume that a system has many cells, with each having S channels The

chan-nel holding time has an exponential distribution with mean rate  Both originating andhandoff calls are generated in a cell according to Poisson processes, with mean rates
O

and
H, respectively We assume the system with a homogeneous cell We focus our tion on a single cell (called the marked cell) Newly generated calls in the marked cell arelabeled originating calls (or new calls) A handoff request is generated in the marked cellwhen a channel holding MS approaches the marked cell from a neighboring cell with asignal strength below the handoff threshold

atten-1.5.2.1 Nonpriority Scheme

In this scheme, all S channels are shared by both originating and handoff request calls The

BS handles a handoff request exactly in the same way as an originating call Both kinds ofrequests are blocked if no free channel is available The system model is shown in Figure1.3

With the blocking call cleared (BCC) policy, we can describe the behavior of a cell as a

(S + 1) states Markov process Each state is labeled by an integer i (i = 0, 1, · · · , S),

repre-vf(v)



E[V]

S 21Channels

senting the number of channels in use The state transition diagram is shown in Figure 1.4.

The system model is modeled by a typical M/M/S/S queueing model.

Let P(i) be the probability that the system is in state i The probabilities P(i) can be

de-termined in the usual way for birth–death processes From Figure 1.4, the state

equilibri-um equation is

P(i) = P(i – 1), 0  i  S (1.12)Using the above equation recursively, along with the normalization condition

冱i=0 S P(i) = 1 (1.13)

the steady-state probability P(i) is easily found as follows:

P(i) = P(0), 0  i  S (1.14)where

Equation (1.16) is known as the Erlang-B formula

A blocked handoff request call can still maintain the communication via current BS til the received signal strength goes below the receiver threshold or until the conversation

un-is completed before the received signal strength goes below the receiver threshold

O+
H

O+
HS

1.5.2.2 Priority Scheme

In this scheme, priority is given to handoff requests by assigning S Rchannels exclusively

for handoff calls among the S channels in a cell The remaining S C (= S – S R) channels areshared by both originating calls and handoff requests An originating call is blocked if the

number of available channels in the cell is less than or equal to S R (= S – S C) A handoff quest is blocked if no channel is available in the target cell The system model is shown inFigure 1.5

re-We define the state i (i = 0, 1, · · · , S) of a cell as the number of calls in progress for the

BS of that cell Let P(i) represent the steady-state probability that the BS is in state i The probabilities P(i) can be determined in the usual way for birth–death processes The perti-

nent state transition diagram is shown in Figure 1.6 From the figure, the state balanceequations are

SC 21Channels