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CDMA - System capacity engineering By Kiseon Koo and Insoo Koo PDF

218 Pages·2007·4.01 MB·english
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CDMA Systems Capacity Engineering For a listing of recent titles in the Artech House Mobile Communications Series, turn to the back of this book. CDMA Systems Capacity Engineering Kiseon Kim Insoo Koo artechhouse.com Library of Congress Cataloguing-in-Publication Data A catalog record for this book is available from the Library of Congress. British Library Cataloguing in Publication Data Kim, Kiseon CDMA systems capacity engineering—(Artech House mobile communications series) 1. Code division multiple access I. Title II. Koo, I. S. 621.3’8456 ISBN 1-58053-812-6 Cover design by Yekaterina Ratner © 2005 ARTECH HOUSE, INC. 685 Canton Street Norwood, MA 02062 Allrightsreserved.PrintedandboundintheUnitedStatesofAmerica.Nopartofthisbook maybereproducedorutilizedinanyformorbyanymeans,electronicormechanical,includ- ing photocopying, recording, or by any information storage and retrieval system, without permission in writing from the publisher. Alltermsmentionedinthisbookthatareknowntobetrademarksorservicemarkshave beenappropriatelycapitalized.ArtechHousecannotattesttotheaccuracyofthisinforma- tion.Useofaterminthisbookshouldnotberegardedasaffectingthevalidityofanytrade- mark or service mark. International Standard Book Number: 1-58053-812-6 10 9 8 7 6 5 4 3 2 1 Contents Preface ix Acknowledgments xi CHAPTER 1 Introduction 1 1.1 Capacity Issues 6 1.2 Overview and Coverage 9 References 14 CHAPTER 2 System Capacity of CDMA Systems 17 2.1 Introduction 17 2.2 System Model and Analysis 18 2.3 Single Cell CDMA Capacity 20 2.4 Multiple Cell CDMA Capacity 22 2.5 Conclusions 25 References 27 CHAPTER 3 Sensitivity Analysis in CDMA Systems 29 3.1 System Model and System Capacity 30 3.2 The Significance and Definitions of Sensitivity Analysis 32 3.2.1 The Significance of Sensitivity Analysis 32 3.2.2 Basic Definitions of Sensitivity 32 3.3 Sensitivity of System Capacity with Respect to System Reliability in CDMA Cellular Systems 34 3.4 Conclusion 37 References 37 CHAPTER 4 Effect of Traffic Activity on System Capacity 39 4.1 Introduction 39 4.2 Traffic Modeling 40 4.3 Outage Probability and System Capacity 42 4.3.1 AILM 43 4.3.2 SILM 44 v vi Contents 4.3.3 Comparison of AILM and SILM 46 4.4 Effect of Traffic Activity on System Capacity 47 4.4.1 Analysis Under the Same Transmission Rate 48 4.4.2 Analysis Under the Same Average Rate 49 4.5 Conclusions 51 References 52 CHAPTER 5 A Dynamic Resource Allocation Scheme to Efficiently Utilize System Capacity 55 5.1 Introduction 56 5.2 System Capacity and Remaining Resources 57 5.3 Service Rates for Throughput Maximization 58 5.4 The Proposed Resource Allocation Scheme 61 5.5 Group Selection According to the Parameters of VBR Service Groups 64 5.6 Conclusions 67 References 68 CHAPTER 6 Voice/Data Mixed CDMA Systems with Prioritized Services 69 6.1 Introduction 69 6.2 System and Traffic Models 70 6.2.1 System Model 70 6.2.2 Traffic Model 71 6.3 Erlang Capacity Analysis Under the Proposed CAC Scheme 73 6.4 Numerical Example 79 6.5 Conclusion 84 References 85 CHAPTER 7 Erlang Capacity of CDMA Systems Supporting Multiclass Services 87 7.1 Introduction 87 7.2 System Model and System Capacity 88 7.3 Erlang Capacity for the Multimedia CDMA Systems 91 7.4 Numerical Example 93 7.5 Conclusion 96 References 98 CHAPTER 8 Erlang Capacity Under the Delay Constraint 101 8.1 Introduction 101 8.2 System Model 102 8.3 Markov Chain Model and Blocking Probability 104 8.4 Delay Distribution 108 8.5 Delay Confidence 114 8.6 Erlang Capacity 116 8.7 Conclusions 119 References 120 Contents vii CHAPTER 9 Multiclass CDMA Systems with a Limited Number of Channel Elements 123 9.1 Introduction 123 9.2 System Model 124 9.3 Erlang Capacity for the Multimedia CDMA Systems 125 9.4 Numerical Example and Discussion 129 9.4.1 Single FA Case 129 9.4.2 Case of Multiple FAs and Graphic Interpretation Method 133 9.5 Conclusion 137 References 139 CHAPTER 10 Approximate Analysis Method for CDMA Systems with Multiple Sectors and Multiple FAs 141 10.1 Introduction 141 10.2 System Model 142 10.3 Approximate Analysis Method 142 10.4 Calculation Complexity of the Proposed Method 145 10.5 Numerical Example 147 10.5.1 An Interesting Observation: Two Traffic Parameters to Efficiently Approximate the Call Blocking Probability in CDMA Systems with Three Sectors 148 10.6 Conclusion 151 References 152 CHAPTER 11 Erlang Capacity of Hybrid FDMA/CDMA Systems Supporting Multiclass Services 153 11.1 Introduction 153 11.2 System Model 155 11.3 Channel Assignment Methods 156 11.3.1 ICCA 157 11.3.2 CCCA 157 11.4 Erlang Capacity Analysis 157 11.4.1 Erlang Capacity Analysis for CCCA 157 11.4.2 Erlang Capacity Analysis for ICCA 162 11.5 Numerical Example 162 11.6 Conclusion 166 References 167 CHAPTER 12 Erlang Capacity of Multiaccess Systems Supporting Voice and Data Services 169 12.1 Introduction 169 12.2 System Model 170 12.3 Operation Methods of Multiaccess Systems 172 12.3.1 Separate Operation Method 173 viii Contents 12.3.2 Common Operation Method 173 12.4 Erlang Capacity Analysis 174 12.4.1 Erlang Capacity Analysis for Separate Operation Method 174 12.4.2 Erlang Capacity Analysis for Common Operation Method 177 12.5 Numerical Results 178 12.6 Conclusion 183 References 184 APPENDIX A TheM/M/ Model 187 APPENDIX B TheM/M/mLoss Model 189 List of Acronyms 191 About the Authors 193 Index 195 Preface Technologymustbesustainableinthesenseofefficiency,notonlytosatisfyquality requirements,buttoobtainthesameobjectiveswiththeminimumresources.Qual- ity satisfaction has been an interesting issue to engineers as an objective of target technology, and technologies are continually evolving to optimize and fulfill the requiredqualities.Thesatisfactionobjectivesofqualitycanbequantitativelymod- eled in many cases. There had been continuous improvement of the satisfaction level on the modeled spaces, because the modeled problem is rather concrete and resolvable analytically within the artificially configured world. However, the sus- tainability relevant to the minimum resources is suggested by a higher layer than typicalengineering,anditisratheranabstracttopicforsocialmovementandeco- politicalcampaigns.Subsequently,whiletheengineersdevotetheirtimeandefforts in the narrow concept of quality optimization, there have been growing concerns aboutwhethertheengineeringdevelopmentandrelevantresultsarereallycontribu- tive sustainably for mundane usages or simply for the progressing toward endless goals. Observing that global resources are becoming more scarce, it would be greatlybeneficialifengineersreallyunderstandtheissuesofsustainabilitytoimple- ment technologies and systems. Communicationsisanindispensabletechnologytoprocessandtransmitinfor- mation.Obviously,communicationtechnologyneedstobesustainableinthesense ofefficiency,notonlytopreservetheinformationwithinthequalityrequirements, butalsotoexpressthesamecontentswiththeminimumresources.Observingthat theglobalresourcesofcommunicationtechnology,suchasfrequenciesandenergy, are diminishing further and further, it will be greatly beneficial if engineers really understand the issues of sustainability to implement communication systems and satisfactorysystemperformance.Thecommunicationresourcescanberepresented byvirtueofcapacity,andquantitativeexpressionsofcapacitycanbeimplemented by such sentences as: (cid:127) Howmanyuserscanbeincludedinacommunicationsystemasanindication of the capacity of the system? (cid:127) Howmanycallscanbehandledbyacommunicationsystemasanindication of the capacity of the system? Byponderingthecapacityissuesofcommunicationsystems,alongwithvarious qualityrequirementssuchastransmissionerrorrate,transmissionspeed,necessary bandwidth, and required power, we may develop sustainable systems, optimized ix

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