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A general modular framework for resource allocation in IEEE 802.16

Erta, Alessandro (2008) A general modular framework for resource allocation in IEEE 802.16. Advisor: Lenzini, Prof. Luciano. Coadvisor: Gregori, Dr. Enrico . pp. 108. [IMT PhD Thesis]

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Abstract

The IEEE 802.16 MAC protocol is centralized, that is, a single Base Station (BS) controls the communication to and from a number of Subscriber Stations (SSs). The BS is responsible for guaranteeing the QoS requirements of each SS. However, the QoS objective is often in contrast with the system factors and constraints which can depend on the most heterogeneous system characteristics. These include the duplexing mode, the specific air interface used and, even, the SS hardware capabilities. In this work, the problem of meeting the QoS requirements of each SS while, at the same time, satisfying the overall system constraints will be referred to as resource allocation. Through a detailed analysis of the standard, we show that the latter is an overly complex task. To tackle the complexity, we thus propose to subdivide the overall resource allocation process into distinct, though sometimes strictly coupled, sub-problems. Hence, we developed a general modular framework where all the sub-problems can be solved by independent sub-tasks which can be combined together in a pipeline. We identified three main sub-tasks, i.e., grant scheduling, grant arrangement and grant allocation. We call our framework PIPER which recalls the pipelined organization. We will show that our approach greatly reduces the complexity of the resource allocation problem and can be successfully adopted in many different contexts. Within the PIPER framework we also propose two grant allocation algorithms, namely Half-Duplex Allocation (HDA) and Sample Data Region Allocation (SDRA) for IEEE 802.16 FDD with half-duplex SSs and IEEE 802.16e TDD for mobility support, respectively. We will evaluate the performance our solutions through extensive simulation.

Item Type: IMT PhD Thesis
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
PhD Course: Computer Science and Engineering
Identification Number: 10.6092/imtlucca/e-theses/17
NBN Number: urn:nbn:it:imtlucca-27053
Date Deposited: 05 Jul 2012 13:55
URI: http://e-theses.imtlucca.it/id/eprint/17

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