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008			170308s2017 sz ob 001 0 eng d
020			_a3319503898 _q(electronic bk.)
020			_a9783319503899 _q(electronic bk.)
020			_z3319503871
020			_z9783319503875 _q(print)
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050		4	_aTK5103.4873 _b2017 EB
100	1		_aParsaeefard, Saeedeh, _eautor
245	1	0	_aRobust resource allocation in future wireless networks _cSaeedeh Parsaeefard, Ahmad Reza Sharafat, Nader Mokari.
264		1	_aCham, Switzerland _bSpringer _c2017.
300			_a1 recurso en línea
336			_aTexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_atext file _bPDF _2rda
500			_aSpringerLink _bSpringer Engineering eBooks 2017 English+International
504			_aIncluye referencias bibliográficas e índice
505	0		_aPreface; Contents; Notations and Symbols; Abbreviations; 1 Introduction; 1.1 Motivation; 1.2 Formulating Resource Allocation Problems; 1.3 Mathematical Background; 1.3.1 Stochastic Robust Optimization; 1.3.2 Worst-Case Robust Optimization; 1.3.2.1 General Norm; 1.3.2.2 Polyhedron Model; 1.3.3 Hybrid Approach: Bounded Uncertainty and Probabilistic Constraints; 1.3.3.1 Chance-Constrained Approach; 1.3.3.2 D-Norm Approach; 1.4 Generic System Model; 1.4.1 System Model for Wireless Networks with Homogeneous Users; 1.4.2 System Model for Wireless Networks with Heterogeneous Users.
505	8		_a1.4.2.1 Underlay Cognitive Radio Network1.4.2.2 Wireless Networks with Heterogeneous Users in Unlicensed Bands; 1.4.3 Physical Layer Security in Wireless Channels; 1.5 Cost of Robustness; 1.6 Organization of This Book; References; 2 Robust Cooperative Resource Allocation; 2.1 Introduction; 2.2 Single-Channel Cellular Cognitive Radio Networks; 2.2.1 Robust Problem; 2.2.1.1 Iterative Algorithm for Solving Nominal and Robust Problems; 2.2.1.2 Reduced Throughput in Robust Solution; 2.2.1.3 Distributed Robust Solutions and Extra Message Passing; 2.2.1.4 Infrequent Message Passing.
505	8		_a2.3 Multi-channel Cognitive Radio Networks2.3.1 Robust Problems; 2.3.1.1 Social Utility of Robust Solutions Versus Uncertainty Levels; 2.3.2 Trade-Off Algorithms; 2.3.2.1 Trade-Off in D-Norm Approach; 2.3.2.2 Trade-off in Chance-Constrained Approach; 2.4 Overview of Other Works on Robust Cooperative Resource Allocation; 2.5 Concluding Remarks; Appendices; Appendix 1: Proof of Proposition 2.2; Appendix 2: Convexity of (9); Appendix 3: Proof of Proposition 2.3; Appendix 4: Proof of Lemma 2.1; Appendix 5: Proof of Proposition 2.4; Appendix 6: Proof of Lemma 2.2; Appendix 7: Proof of Lemma 2.3.
505	8		_a3.3.1.2 Social Utility (Sum Rate)3.3.1.3 Distributed Algorithms; 3.3.1.4 Overview of Other Works on Robust Noncooperative Games with Homogeneous Users; 3.3.2 Robust Power Control in Noncooperative CRNs; 3.3.2.1 Existence and Uniqueness of RNE; 3.3.2.2 Social Utility (Sum Rate); 3.3.2.3 Distributed Algorithms; 3.3.2.4 Overview of Other Works on Robust Noncooperative CRNs; 3.3.3 Robust Power Control for Noncooperative Heterogeneous Users; 3.3.3.1 Robust Stackelberg Games; 3.3.3.2 Single-Leader/Single-Follower Robust Stackelberg Games; 3.3.3.3 Multi-user Stackelberg Games.
505	8		_aAppendix 8: Proof of Proposition 2.5References; 3 Robust Noncooperative Resource Allocation; 3.1 Introduction; 3.2 Overview of Nominal Noncooperative Strategic Games; 3.2.1 Existence and Uniqueness of NE; 3.2.1.1 Existence of NE; 3.2.1.2 Uniqueness of NE; 3.2.1.3 Existence and Uniqueness of NE in Nominal Noncooperative Power Control Games with Homogeneous Users; 3.2.2 Social Utility (Sum Rate) at NE; 3.2.3 Distributed Algorithms; 3.3 Worst-Case Robust Power Control in Noncooperative Games; 3.3.1 Robust Power Control for Noncooperative Homogeneous Users; 3.3.1.1 Existence and Uniqueness of RNE.
520	3		_aThis book presents state-of-the-art research on robust resource allocation in current and future wireless networks. The authors describe the nominal resource allocation problems in wireless networks and explain why introducing robustness in such networks is desirable. Then, depending on the objectives of the problem, namely maximizing the social utility or the per-user utility, cooperative or competitive approaches are explained and their corresponding robust problems are considered in detail. For each approach, the costs and benefits of robust schemes are discussed and the algorithms for reducing their costs and improving their benefits are presented. Considering the fact that such problems are inherently non-convex and intractable, a taxonomy of different relaxation techniques is presented, and applications of such techniques are shown via several examples throughout the book. Finally, the authors argue that resource allocation continues to be an important issue in future wireless networks, and propose specific problems for future research.
650		7	_aSistemas de comunicación inalámbricos _2embne _0(OCoLC)fst01745903 _0 _9158044
700	1		_aMokari, Nader, _eautor
700	1		_aSharafat, Ahmad Reza, _eautor
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=http://link.springer.com/10.1007/978-3-319-50389-9 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
988			_aEBOOK, asignarmaterias, EBSPRINGER_2017C
998			_b02/2018 _dz _e- _zSI
999			_c95528 _d95528 _x1