Submodular rate region models for multicast communication in wireless networks /
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| Author / Creator: | Riemensberger, Maximilian, author. |
|---|---|
| Imprint: | Cham : Springer, ©2018. |
| Description: | 1 online resource |
| Language: | English |
| Series: | Foundations in signal processing, communications and networking, 1863-8538 ; v. 14 Foundations in signal processing, communications and networking ; v. 14. |
| Subject: | |
| Format: | E-Resource Book |
| URL for this record: | http://pi.lib.uchicago.edu/1001/cat/bib/11541586 |
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| 100 | 1 | |a Riemensberger, Maximilian, |e author. | |
| 245 | 1 | 0 | |a Submodular rate region models for multicast communication in wireless networks / |c Maximilian Riemensberger. |
| 260 | |a Cham : |b Springer, |c ©2018. | ||
| 300 | |a 1 online resource | ||
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| 490 | 1 | |a Foundations in signal processing, communications and networking, |x 1863-8538 ; |v v. 14 | |
| 505 | 0 | |a Preface; Contents; List of Figures; List of Tables; 1 Introduction; 1.1 Preliminaries and Notation; 1.2 List of Symbols and Operators; References; 2 Submodular Information Flow Models for Multicast Communication; 2.1 Cut Model; 2.2 Graph Model; 2.3 Hypergraph Model; 2.4 Polymatroid Broadcast Model; 2.5 Transformation of Models; 2.6 Generalized Cut Model; 2.7 Penalized Polymatroid Broadcast Model; 2.8 Rate Region Properties and Equivalence; 2.9 Cut Rate Sandwiched Multicast Source Rate Regions; 2.10 Extension to Per-terminal Cut Models; 2.11 Proofs; 2.11.1 Polymatroid Max-Flow Min-Cut Theorem. | |
| 505 | 8 | |a 2.11.2 Transformation of Models2.11.3 Rate Region Properties and Equivalence; 2.11.4 Cut Rate Sandwiched Multicast Source Rate Regions; References; 3 Network Utility Maximization via Submodular Dual Decomposition; 3.1 Concave Network Utility Maximization; 3.2 Dual Decomposition Approach for Min-Cut Rate Regions; 3.3 Dual Decomposition Approach for Max-Flow Regions; 3.4 Connections Between the Dual Decomposition Approaches; 3.5 Dual Decomposition Approach for Hyperarc Rate Regions; 3.6 Convexity and Comprehensiveness; 3.7 Upper Bound for Nonsubmodular Cut Rate Regions. | |
| 505 | 8 | |a 3.8 Counting Set Function Evaluations3.9 Discussion and Related Dual Decomposition Methods; 3.10 Extension to Per-terminal Cut Models; 3.11 Proofs and Appendices; 3.11.1 Utility Characterization of the Multicast Rate Region; 3.11.2 Network Utility Maximization Problem; 3.11.3 Dual Decomposition Approaches; 3.11.4 Convexity and Comprehensiveness; References; 4 Network Coding Bounds and Submodularity; 4.1 Discrete Memoryless Multicast Networks; 4.1.1 Cut-Set Outer Bound; 4.1.2 Noisy Network Coding Inner Bound; 4.1.3 Elementary Hypergraph Decomposition Inner Bound. | |
| 505 | 8 | |a 4.1.4 Weighted Sum Multicast Rate Maximization4.2 Networks of Independent Broadcast Channels; 4.2.1 Cut-Set Outer Bound; 4.2.2 Noisy Network Coding Inner Bound; 4.2.3 Elementary Broadcast Decomposition Inner Bound; 4.2.4 Elementary Broadcast Decomposition for Less Noisy Channels; 4.2.5 Weighted Sum Multicast Rate Maximization; 4.3 Discrete Memoryless Networks with Known State Sequence; 4.3.1 Cut-Set Outer Bound; 4.3.2 Noisy Network Coding Inner Bound; 4.4 Proofs; 4.4.1 Cut-Set Outer Bound; 4.4.2 Noisy Network Coding Inner Bound; 4.4.3 Networks of Independent Broadcast Channels; References. | |
| 505 | 8 | |a 5 Deterministic and Linear Finite Field Networks5.1 Deterministic Networks; 5.1.1 Bounds on the Multicast Capacity Region; 5.1.2 Weighted Sum Source Rate Maximization; 5.2 Networks of Independent Deterministic Broadcast Channels; 5.2.1 Broadcast Representation of the Capacity Region; 5.2.2 Insufficiency of the Hyperarc Model; 5.2.3 Weighted Sum Source Rate Maximization; 5.3 Noisy Linear Finite Field Networks; 5.3.1 Cut-Set Outer Bound; 5.3.2 Noisy Network Coding Inner Bound; 5.3.3 Tightness of Inner and Outer Bounds; 5.3.4 Deterministic Linear Finite Field Networks. | |
| 504 | |a Includes bibliographical references. | ||
| 588 | 0 | |a Print version record. | |
| 520 | |a This book proposes representations of multicast rate regions in wireless networks based on the mathematical concept of submodular functions, e.g., the submodular cut model and the polymatroid broadcast model. These models subsume and generalize the graph and hypergraph models. The submodular structure facilitates a dual decomposition approach to network utility maximization problems, which exploits the greedy algorithm for linear programming on submodular polyhedra. This approach yields computationally efficient characterizations of inner and outer bounds on the multicast capacity regions for various classes of wireless networks. | ||
| 650 | 0 | |a Wireless communication systems. |0 http://id.loc.gov/authorities/subjects/sh92006740 | |
| 650 | 0 | |a Multicasting (Computer networks) |0 http://id.loc.gov/authorities/subjects/sh97007256 | |
| 650 | 7 | |a TECHNOLOGY & ENGINEERING |x Mechanical. |2 bisacsh | |
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| 650 | 7 | |a Information retrieval. |2 bicssc | |
| 650 | 7 | |a Functional analysis & transforms. |2 bicssc | |
| 650 | 7 | |a Communications engineering |x telecommunications. |2 bicssc | |
| 650 | 7 | |a Multicasting (Computer networks) |2 fast |0 (OCoLC)fst01028804 | |
| 650 | 7 | |a Wireless communication systems. |2 fast |0 (OCoLC)fst01176209 | |
| 655 | 4 | |a Electronic books. | |
| 776 | 0 | 8 | |i Print version: |a Riemensberger, Maximilian. |t Submodular rate region models for multicast communication in wireless networks. |d Cham : Springer, ©2018 |z 9783319652313 |z 3319652311 |w (OCoLC)994639262 |
| 830 | 0 | |a Foundations in signal processing, communications and networking ; |v v. 14. |0 http://id.loc.gov/authorities/names/no2008050216 | |
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