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Context Awareness for Enhancing Heterogeneous Access Management and Self-Optimizing Networks

  • The heterogeneity of today's access possibilities to wireless networks imposes challenges for efficient mobility support and resource management across different Radio Access Technologies (RATs). The current situation is characterized by the coexistence of various wireless communication systems, such as GSM, HSPA, LTE, WiMAX, and WLAN. These RATs greatly differ with respect to coverage, spectrum, data rates, Quality of Service (QoS), and mobility support. In real systems, mobility-related events, such as Handover (HO) procedures, directly affect resource efficiency and End-To-End (E2E) performance, in particular with respect to signaling efforts and users' QoS. In order to lay a basis for realistic multi-radio network evaluation, a novel evaluation methodology is introduced in this thesis. A central hypothesis of this thesis is that the consideration and exploitation of additional information characterizing user, network, and environment context, is beneficial for enhancing Heterogeneous Access Management (HAM) and Self-Optimizing Networks (SONs). Further, Mobile Network Operator (MNO) revenues are maximized by tightly integrating bandwidth adaptation and admission control mechanisms as well as simultaneously accounting for user profiles and service characteristics. In addition, mobility robustness is optimized by enabling network nodes to tune HO parameters according to locally observed conditions. For establishing all these facets of context awareness, various schemes and algorithms are developed and evaluated in this thesis. System-level simulation results demonstrate the potential of context information exploitation for enhancing resource utilization, mobility support, self-tuning network operations, and users' E2E performance. In essence, the conducted research activities and presented results motivate and substantiate the consideration of context awareness as key enabler for cognitive and autonomous network management. Further, the performed investigations and aspects evaluated in the scope of this thesis are highly relevant for future 5G wireless systems and current discussions in the 5G infrastructure Public Private Partnership (PPP).

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Metadaten
Author:Andreas Klein
URN (permanent link):urn:nbn:de:hbz:386-kluedo-40213
ISBN:978-3-8439-2030-8
Publisher:Dr. Hut
Place of publication:München
Advisor:Hans D. Schotten
Document Type:Doctoral Thesis
Language of publication:English
Publication Date:2015/03/10
Year of Publication:2015
Publishing Institute:Technische Universität Kaiserslautern
Granting Institute:Technische Universität Kaiserslautern
Acceptance Date of the Thesis:2014/12/01
Date of the Publication (Server):2015/03/11
Tag:fuzzy Q-learning; fuzzy logic; handover optimzaiion; heterogeneous access management; mobility robustness optimization; reinforcement learning; self-optimizing networks
GND-Keyword:context awareness; context management; wireless networks
Number of page:XVIII, 292
Faculties / Organisational entities:Fachbereich Elektrotechnik und Informationstechnik
DDC-Cassification:6 Technik, Medizin, angewandte Wissenschaften / 620 Ingenieurwissenschaften und Maschinenbau
Licence (German):Standard gemäß KLUEDO-Leitlinien vom 13.02.2015