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Efficient control signaling for resource allocation in OFDMA networks
Dissertation   Open access

Efficient control signaling for resource allocation in OFDMA networks

Gwanmo Ku
Doctor of Philosophy (Ph.D.), Drexel University
Jun 2014
DOI:
https://doi.org/10.17918/etd-4553
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Abstract

Electrical engineering Orthogonal frequency division multiplexing Signals and signaling Wireless Communication Systems
This thesis designs efficient control signaling for resource allocation in OFDMA networks, with special attention given to improving the resource controller in the LTE standard. We are interested in two aspects of resource controller design, the amount of control information a resource controller utilizes, and the performance, for instance the data spectral efficiency, it attains. Our overall aim is to understand the fundamental tradeoff between these two quantities, and to learn how to design resource controllers that approach this tradeoff. To get a sense of the state of the art in resource controller design, we first investigate the resource controller in the LTE standard, evaluating the amount of control information it requires. We thoroughly catalog the physical layer signals related to resource allocation and link adaptation with a focus on the location and formatting of the pertinent reference and control signals, as well as the decisions they enable. This enables us to determine the fraction of the time frequency resource grid spent on control information. This control signaling overhead in LTE occupies a large percentage of the time-frequency footprint of wireless network traffic and is not efficiently encoded. After this, we set about determining the fundamental tradeoff between the amount of control information and the spectral efficiency by modeling the problem using information theory. In order to design more efficient control signaling schemes, we will model the control signals as messages in a distributed lossy source code, for which the rate distortion function describes an optimum tradeoff between a rate, reflecting the overhead, and a distortion, reflecting the performance. Although there is no closed form expression for the rate region, we derive a novel adaptation of the Blahut-Arimoto algorithm to the CEO model with independent sources, and use it to numerically calculate the rate distortion function. The developed algorithm is then utilized to calculate the rate distortion function for a series of simple resource allocation models. Finally, for these physical layer resource allocation models, we design practical distributed quantizers that yield control signaling encodings for a resource controller that approaches the fundamental overhead performance tradeoff limit calculated.

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