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Advanced Communication Networks (ACN)5 ECTS (englische Bezeichnung: Advanced Communication Networks)
Modulverantwortliche/r: Laura Cottatellucci Lehrende:
Laura Cottatellucci
Start semester: |
SS 2019 | Duration: |
1 semester | Cycle: |
jährlich (SS) |
Präsenzzeit: |
60 Std. | Eigenstudium: |
90 Std. | Language: |
Englisch |
Lectures:
Empfohlene Voraussetzungen:
It is recommended to finish the following modules before starting this module:
Digital Communications (WS 2018/2019)
Inhalt:
Telecommunications have become ubiquitous in daily life and wireless networks play a fundamental role thanks to their capability to support mobility. In a wireless medium, the concept of link does not exist. The users radiate energy and communicate through the superposition of each other’s transmissions creating interference. Compared to wireline networks this scenario is extremely challenging but also offers unpredictable opportunities for the development of new technologies, e.g., massive MIMO, cognitive radio, and exploitation of new features, e.g., opportunistic communications and multiuser diversity. The exponentially increasing request of higher and higher throughput per unit area is satisfied densifying the networks and allowing more and more interference but adopting advanced techniques and innovative resource allocation to mitigate its detrimental effects. Objective of this course is to introduce the student to advanced techniques for medium access control, coordinated or contention based, and radio resource management in both cellular systems and mesh or ad-hoc networks. Power allocation, rate adaptation and scheduling will be discussed both in centralized and distributed settings. Some mathematical methods play a fundamental role in resource allocation, namely, classical Perron-Frobenius theory for nonnegative matrices, convex and nonconvex constrained optimization, distributed optimization and game theory. The course introduces the student to such methods and exemplifies their application to various resource allocation problems. Additionally, the course addresses relevant aspects of resource allocation in wireless networks such as fairness and cross-layer design. Technical Content
• Properties and challenges of the wireless medium.
• Basic concepts of communication networks: the layered architecture
• The 802.11 wireless architecture
• Evolution of wireless cellular network architectures: From Global System for Mobile to Advanced-Long Term Evolution
• Multiple Access Schemes: CSMA variants, TDMA, FDMA, CDMA, OFDMA, SC-FDMA, SDMA
• Uplink-downlink duality
• Opportunistic scheduling and multiuser diversity
• Advanced concepts: small cells and heterogeneous networks, relaying and cooperation, network coding, cognitive radio networks
• Basics of resource allocation: power allocation, rate adaptation, and scheduling
• Classical resource allocation techniques: Centralized and distributed power control based on the Perron-Frobenius theorem
Lernziele und Kompetenzen:
The student • Describes and/or recognizes wireless channel models
• Compares different CSMA schemes in various communication media and explains how to combat the hidden node effect in wireless systems
• Criticizes the limits of the a layered architecture in wireless systems
• Defends the use of cross-layer design in wireless network
• Applies rate adaptation schemes to maximize the throughput in IEEE 802.11
• Compares handover schemes of different cellular architectures
• Appraises and compares the distribution of functionalities in network entities for different architectures
• Argue on the pros and contras of different multiple access schemes according to various criteria (e.g. spectral efficiency, power efficiency, robustness to interference)
• Compares and contrasts micro-diversity and various macro-diversity schemes
• Computes the total rate of SDMA with various receivers
• Relates the multiple access in uplink to broadcasting in downlink and justifies the concept of uplink-downlink duality
• Uses uplink-downlink duality to design a precoder and allocate power
• Contrasts multiple access in uplink and broadcasting in downlink in terms of channel state acquisition both for TDD and FDD transmission
• Uses multiuser diversity for opportunistic scheduling
• Compares multiuser diversity for users having identical and different channel statistics
• Contrasts opportunistic scheduling in terms of channel state acquisition and feedback both for uplink and downlink and for both FDD and TDD transmission schemes
• Appraises the impact of multiple antennas on opportunistic scheduling
• Analyses different settings with interference in small cells and designs countermeasures
• Categorizes relaying schemes in LTE
• Analyses performance of relaying schemes
• Argues on possible improvements of relaying schemes via network coding and physical layer network coding
• Uses the Perron-Frobenious theorem to allocate power in a centralized manner
• Judges the feasibility of a power control problems and formulates alternative approaches in case of unfeasibility
• Uses the Perron-Frobenious theorem to design a distributed power control scheme
• Judges the convergences of distributed power control based on the Perron-Frobenius theorem and appraises the robustness of asynchronous power control
• Applies techniques of convex optimization to discriminate convex problems and determine necessary and/or sufficient conditions for global optimality
• Judges the applicability of KKT conditions and duality
• Uses KKT conditions to solve convex optimization problems
• Uses duality to solve convex optimization problems
• Applies convex optimization to resource allocation in wireless communications
• Compares different definitions of fairness and applies them to rate allocation
• Appraises the effect of channel knowledge at the transmitter on different fairness criteria
• Applies KKT conditions for opportunistic user scheduling
• Describes a proportional fair algorithm for opportunistic scheduling
• Applies relaxation to nonconvex quadratic constrained quadratic programming
• Formulates resource allocation problems as constrained optimization programming
• Contrasts various distributed optimization methods
• Applies the concept of best response to determine Nash equilibria
• Argues about existence and uniqueness of Nash equilibria
• Assesses if a given game is a potential game and solves it
• Defends the concept of Pareto optimality in resource
allocation
• Contrasts the concepts of pure and mixed strategies in game theory
• Uses coupled constrained concave game to allocate powers in heterogeneous networks
• Uses discrete time Markov chain to model specific aspects of communication systems
• Discusses the meaning of Markov chain transition matrices interpreting Kolmogorov-Chapman equations
• Contrasts stationary and limiting distributions of a Markov chain and predicts when they coincide in specific cases
• Applies Markov chains to Aloha systems and analyzes a slotted Aloha protocol
• Justifies the usefulness of exponential back-off in CSMA via analysis with Markov chain
Verwendbarkeit des Moduls / Einpassung in den Musterstudienplan: Das Modul ist im Kontext der folgenden Studienfächer/Vertiefungsrichtungen verwendbar:
- Advanced Signal Processing & Communications Engineering (Master of Science)
(Po-Vers. 2016w | TechFak | Advanced Signal Processing & Communications Engineering (Master of Science) | Gesamtkonto | Wahlpflichtmodule | Technical Mandatory Electives)
Studien-/Prüfungsleistungen:
Advanced Communication Networks (Prüfungsnummer: 151664)
(englischer Titel: Advanced Communication Networks)
- Prüfungsleistung, mündliche Prüfung, Dauer (in Minuten): 30, benotet, 5 ECTS
- Anteil an der Berechnung der Modulnote: 100.0 %
- Prüfungssprache: Englisch
- Erstablegung: SS 2019, 1. Wdh.: WS 2019/2020
1. Prüfer: | Laura Cottatellucci |
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