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El. knyga: Interference Calculus: A General Framework for Interference Management and Network Utility Optimization

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This book develops a mathematical framework for modeling and optimizing interference-coupled multiuser systems. At the core of this framework is the concept of general interference functions, which provides a simple means of characterizing interdependencies between users. The entire analysis builds on the two core axioms scale-invariance and monotonicity. The proposed network calculus has its roots in power control theory and wireless communications. It adds theoretical tools for analyzing the typical behavior of interference-coupled networks. In this way it complements existing game-theoretic approaches. The framework should also be viewed in conjunction with optimization theory. There is a fruitful interplay between the theory of interference functions and convex optimization theory. By jointly exploiting the properties of interference functions, it is possible to design algorithms that outperform general-purpose techniques that only exploit convexity. The title network calculus refers to the fact that the theory of interference functions constitutes a generic theoretical framework for the analysis of interference coupled systems. Certain operations within the framework are closed, that is, combinations of interference functions are interference functions again. Also, certain properties are preserved under such operations. This, provides a methodology for analyzing different multiuser performance measures that can be expressed as interference functions or combinations of interference functions.

Recenzijos

From the reviews:

The book provides an overview of recent advances in the field with particular emphasis on analysing the elementary structure properties of interference functions . Generally, the targeted audience includes graduate students of engineering and applied mathematics, as well as academic and industrial researchers in the field of wireless communications, networking, control and game theory. No particular background is needed for reading the book, except for some familiarity with basic concepts from convex analysis and linear algebra. (Vangelis Grigoroudis, Zentralblatt MATH, Vol. 1251, 2012)

1 Introduction
1(16)
1.1 Notation
3(1)
1.2 Basic Axiomatic Framework of Interference Functions
4(1)
1.3 Convexity, Concavity, and Logarithmic Convexity
5(2)
1.4 Examples - Interference in Wireless Networks
7(10)
2 Systems of Coupled Interference Functions
17(22)
2.1 Combinations of Interference Functions
18(1)
2.2 Interference Coupling
18(3)
2.3 Strict Monotonicity and Strict Log-Convexity
21(2)
2.4 Standard Interference Functions and Power Control
23(3)
2.5 Continuity
26(3)
2.6 QoS Regions, Feasibility, and Fixed Point Characterization
29(3)
2.7 Power-Constrained QoS Regions
32(3)
2.8 The QoS Balancing Problem
35(4)
3 The Structure of Interference Functions and Comprehensive Sets
39(60)
3.1 General Interference Functions
40(6)
3.2 Synthesis of General Interference Functions
46(4)
3.3 Concave Interference Functions
50(11)
3.4 Convex Interference Functions
61(8)
3.5 Expressing Utility Sets as Sub-/Superlevel Sets of Convex/Concave Interference Functions
69(3)
3.6 Log-Convex Interference Functions
72(10)
3.7 Application to Standard Interference Functions
82(7)
3.8 Convex and Concave Approximations
89(10)
4 Nash Bargaining and Proportional Fairness for Log-Convex Utility Sets
99(56)
4.1 Nash Bargaining for Strictly Log-Convex Utility Sets
100(9)
4.2 The SIR Region of Log-Convex Interference Functions
109(13)
4.3 Proportional Fairness - Boundedness, Existence, and Strict Log-Convexity
122(16)
4.4 SINR Region under a Total Power Constraint
138(2)
4.5 Individual Power Constraints - Pareto Optimality and Strict Convexity
140(15)
5 QoS-Constrained Power Minimization
155(28)
5.1 Matrix-Based Iteration
157(7)
5.2 Super-Linear Convergence
164(7)
5.3 Convergence of the Fixed Point Iteration
171(6)
5.4 Worst-Case Interference and Robust Designs
177(6)
6 Weighted SIR Balancing
183(14)
6.1 The Max-Min Optimum
184(4)
6.2 Principal Eigenvector (PEV) Iteration
188(4)
6.3 Fixed Point Iteration
192(3)
6.4 Convergence Behavior of the PEV Iteration
195(2)
A Appendix
197(30)
A.1 Irreducibility
197(1)
A.2 Equivalence of Min-Max and Max-Min Optimization
198(1)
A.3 Log-Convex QoS Sets
199(2)
A.4 Derivatives of Interference Functions
201(1)
A.5 Non-Smooth Analysis
202(1)
A.6 Ratio of Sequences
203(1)
A.7 Optimizing a Ratio of Linear Functions
204(1)
A.8 Continuations of Interference Functions
205(3)
A.9 Proofs
208(19)
References 227(8)
Index 235