CDMA Systems Capacity Engineering

218 Pages·2005·4.032 MB·English

by  Kiseon Kim, I.S. Koo

CDMA Systems Capacity Engineering
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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.
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International Standard Book Number: 1-58053-812-6
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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
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