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Radio Resource Management in Cellular Systems PDF

243 Pages·2001·16.725 MB·English
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RADIO RESOURCE MANAGEMENT IN CELLULAR SYSTEMS THE KLUWER INTERNATIONAL SERIES IN ENGINEERING AND COMPUTER SCIENCE RADIO RESOURCE MANAGEMENT IN CELLULAR SYSTEMS by Nishith D. Tripathi Nortel Networks Jeffrey H. Reed Virginia Polytechnic Institute and State University Hugh F. VanLandingham Virginia Polytechnic Institute and State University KLUWER ACADEMIC PUBLISHERS NEW YORK, BOSTON, DORDRECHT, LONDON, MOSCOW eBookISBN: 0-306-47318-6 Print ISBN: 0-792-37374-X ©2002 Kluwer Academic Publishers New York, Boston, Dordrecht, London, Moscow All rights reserved No part of this eBook may be reproduced or transmitted in any form or by any means, electronic, mechanical, recording, or otherwise, without written consent from the Publisher Created in the United States of America Visit Kluwer Online at: http://www.kluweronline.com and Kluwer's eBookstore at: http://www.ebooks.kluweronline.com To Our Families CONTENTS PREFACE xiii CHAPTER 1 HANDOFF AND RADIO RESOURCE MANAGEMENT IN CELLULAR SYSTEMS 1.1 INTRODUCTION TO HANDOFF 1 1.2 DESIRABLE FEATURES AND COMPLEXITIES OF HANDOFF 4 1.3 CELLULAR SYSTEM DEPLOYMENT SCENARIOS 7 1.3.1 Macrocells 7 1.3.2 Microcells 8 1.3.3 Macrocell/Microcell Overlays 11 1.3.4 SpecialArchitectures 13 1.3.5 Integrated Wireless Systems 16 1.4 HANDOFF CRITERIA 18 1.5 CONVENTIONAL HANDOFF ALGORITHMS 19 1.5.1 Signal Strength Based Algorithms 20 1.5.2 Distance Based Algorithm 23 1.5.3 SIRBased Algorithms 23 1.5.4 Velocity Adaptive Algorithms 24 1.5.5 Direction-Biased Algorithms 25 1.5.6 Minimum Power Algorithms 25 1.5.7 RSS and BER Based Algorithms 26 1.6 EMERGING HANDOFF ALGORITHMS 26 1.6.1 Dynamic Programming Based Handoff Algorithms 26 1.6.2 Pattern Recognition Based HandoffAlgorithms 27 1.6.3 Prediction-Based Handoff Algorithms 28 1.6.4 Neural HandoffAlgorithms 28 1.6.5 Fuzzy HandoffAlgorithms 29 1.7 HANDOFF PRIORITIZATION 29 1.7.1 Introduction toHandoffPriority 29 1.7.2 Handoff Priority Schemes 30 1.8 HANDOFF AND RADIO RESOURCE MANAGEMENT 31 1.8.1 Introduction to Resource Management 31 1.8.2 Integrated Radio Resource Management Algorithms 34 Contents 1.9 HANDOFF PROTOCOLS 35 1.9.1 Network Controlled Handoff 35 1.9.2 Mobile Assisted Handoff 36 1.9.3 Soft Handoff 38 1.9.4 Mobile Controlled Handoff 40 1.10 MULTIPLE ACCESS SCHEMES IN CELLULAR SYSTEMS 40 1.11 SUMMARY 42 CHAPTER 2 FUZZY LOGIC AND NEURAL NETWORKS 2.1 INTRODUCTION TO FUZZY LOGIC 43 2.2 INTRODUCTION TO NEURAL NETWORKS 48 2.2.1 Fundamentals of ANNs 48 2.2.2 Paradigms of ANNs 49 2.2.3 Training Methods for the MLP and the RBFN 52 2.3 CONCLUSION 56 CHAPTER 3 ANALYSIS OF HANDOFF AND RADIO RESOURCE MANAGEMENTALGORITHMS 3.1 SYSTEM PERFORMANCE MEASURES 57 3.2 HANDOFF EVALUATION MECHANISMS 59 3.2.1 Analytical Approach 59 3.2.2 Simulation Approach 60 3.2.3 Emulation Approach 65 3.2.4 A Macrocellular Simulation Model 66 3.2.5 A Microcellular Simulation Model 69 3.2.6 An Overlay Simulation Model 71 3.2.7 A Soft Handoff Simulation Model 73 3.3 AN EVALUATION MECHANISM FOR RADIO RESOURCEMANAGEMENT 74 3.4 SUMMARY 81 CHAPTER 4 A GENERIC FUZZY LOGIC BASED HANDOFF ALGORITHM 4.1 HANDOFFALGORITHMS: DESIGN AND ANALYSIS ISSUES 83 4.2 A CLASS OF FUZZY LOGIC BASED Contents ADAPTIVE HANDOFF ALGORITHMS 84 4.2.1 Design Procedure 84 4.2.2 Analysis of Proposed Class of Algorithms 93 4.3 PERFORMANCE ANALYSIS OF PROPOSED AND CONVENTIONAL ALGORITHMS 94 4.3.1 Interference Adaptation 95 4.3.2 Traffic Adaptation 97 4.3.3 Velocity Adaptation 98 4.3.4 Combined Interference, Traffic, and Velocity Adaptation 99 4.4 CONCLUSION 100 CHAPTER 5 A NEURAL ENCODED FUZZY LOGIC ALGORITHM 5.1 INTRODUCTION TO AN ADAPTIVE HANDOFF ALGORITHM 101 5.2 APPLICATION OF NEURAL NETWORKS TO HANDOFF 104 5.3 PERFORMANCE EVALUATION 109 5.4 CONCLUSION 114 CHAPTER 6 A UNIFIED HANDOFF CANDIDACY ALGORITHM 6.1 AN ADAPTIVE FUZZY HANDOFF ALGORITHM WITH ADAPTIVE DIRECTION-BIASING 115 6.2 PERFORMANCE ANALYSIS OF PROPOSED ALGORITHMS 120 6.2.1 Performance Evaluation of FL, DBFL, and TDBFL Algorithms 120 6.2.2 Performance Evaluation of FL, DBFL, and ADBFL Algorithms 123 6.3 CONCLUSION 126 CHAPTER 7 PATTERN CLASSIFICATION BASED HANDOFF ALGORITHMS 7.1 HANDOFF AS A PATTERN CLASSIFICATION PROBLEM 127 7.2 DESIGN OF A PATTERN CLASSIFIER FOR HANDOFF 129 7.2.1 Determination of the Training Data Set 129 7.2.2 Pattern Classifier: Structure Contents and Actual Operation of Classification 132 7.2.3 Details of the PC-Based Handoff Algorithms 132 7.3 PERFORMANCE EVALUATION 134 7.3.1 Evaluation of a Fuzzy Logic Pattern Classifier Handoff Algorithm 135 7.3.2 Evaluation of an MLP Pattern Classifier Handoff Algorithm 136 7.3.3 Evaluation of an RBFN Pattern Classifier Handoff Algorithm 138 7.3.4 Evaluation of a Direction-Biased MLP Pattern Classifier Handoff Algorithm 139 7.4 CONCLUSION 140 CHAPTER 8 MICROCELLULARHANDOFF ALGORITHMS 8.1 INTRODUCTION TO HANDOFFS IN MICROCELLS 141 8.2 ADAPTIVE HANDOFF ALGORITHMS 143 8.2.1 A Generic Microcellular Algorithm 144 8.2.2 A Microcellular Algorithm with Interference, Traffic, and Mobility Adaptation 149 8.3 SIMULATION RESULTS 151 8.3.1 LOS And NLOS PerformanceEvaluation of the Microcellular Algorithms 151 8.3.2 Performance Evaluation of the Microcellular Algorithm with Interference, Traffic, and Mobility Adaptation 152 8.4 CONCLUSION 156 CHAPTER 9 OVERLAY HANDOFF ALGORITHMS 9.1 INTRODUCTION TO HANDOFFS IN OVERLAYS 157 9.2 CONVENTIONAL AND ADAPTIVE OVERLAY HANDOFF ALGORITHMS 159 9.3 SIMULATION RESULTS FOR OVERLAY ALGORITHMS 165 9.4 CONCLUSION 168 CHAPTER 10 SOFT HANDOFF ALGORITHMS 10.1 INTRODUCTION TO SOFT HANDOFF 169 10.2 ADAPTIVE SOFT HANDOFF ALGORITHMS 172

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