ISBN 978-3-8439-2036-0

978-3-8439-2036-0, Reihe Elektrotechnik

Christian Mannweiler
Context-Enabled Optimization of Energy-Autarkic Networks for Carrier-Grade Wireless Backhauling

283 Seiten, Dissertation Technische Universität Kaiserslautern (2014), Softcover, A5

Zusammenfassung / Abstract

Christian Mannweiler: Context-enabled Optimization of Energy-autarkic Networks for Wireless Backhauling

This work establishes the novel category of coordinated Wireless Backhaul Networks (WBNs) for energy-autarkic point-to-point radio backhauling. The networking concept is based on three major building blocks: cost-efficient radio transceiver hardware, a self-organizing network operations framework, and power supply from renewable energy sources. The aim of this novel backhauling approach is to combine carrier-grade network performance with reduced maintenance effort as well as independent and self-sufficient power supply. In order to facilitate the success prospects of this concept, the thesis comprises the following major contributions: Formal, multi-domain system model and evaluation methodology

First, adapted from the theory of cyber-physical systems, the author devises a multi-domain evaluation methodology and a system-level simulation framework for energy-autarkic coordinated WBNs, including a novel balanced scorecard concept. Second, the thesis specifically addresses the topic of Topology Control (TC) in point-to-point radio networks and how it can be exploited for network management purposes. Given a set of network nodes equipped with multiple radio transceivers and known locations, TC continuously optimizes the setup and configuration of radio links between network nodes, thus supporting initial network deployment, network operation, as well as topology re-configuration. In particular, the author shows that TC in WBNs belongs to the class of NP-hard quadratic assignment problems and that it has significant impact in operational practice, e.g., on routing efficiency, network redundancy levels, service reliability, and energy consumption. Two novel algorithms focusing on maximizing edge connectivity of network graphs are developed.

Finally, this work carries out an analytical benchmarking and a numerical performance analysis of the introduced concepts and algorithms. The author analytically derives minimum performance levels of the the developed TC algorithms. For the analyzed scenarios of remote Alpine communities and rural Tanzania, the evaluation shows that the algorithms improve energy efficiency and more evenly balance energy consumption across backhaul nodes, thus significantly increasing the number of available backhaul nodes compared to state-of-the-art TC algorithms.