Date of Award

August 2017

Degree Type


Degree Name

Doctor of Philosophy (PhD)


Electrical Engineering and Computer Science


Mustafa C. Gursoy


Energy Efficiency, Markovian Source Models, QoS Provisioning, Wireless Communications, Wireless Throughput

Subject Categories



Mobile data traffic has experienced unprecedented growth recently and is predicted to grow even further over the coming years. As one of the main driving forces behind this growth, wireless transmission of multimedia content has significantly increased in volume and is expected to be the dominant traffic in data communications. Such wireless multimedia traffic requires certain quality-of-service (QoS) guarantees.

With these motivations, in the first part of the thesis, throughput and energy efficiency in fading channels are studied in the presence of randomly arriving data and statistical queueing constraints. In particular, Markovian arrival models including discrete-time Markov, Markov fluid, and Markov-modulated Poisson sources are considered, and maximum average arrival rates in the presence of statistical queueing constraints are characterized. Furthermore, energy efficiency is analyzed by determining the minimum energy per bit and wideband slope in the low signal-to-noise ratio (SNR) regime.

Following this analysis, energy-efficient power adaptation policies in fading channels are studied when data arrivals are modeled as Markovian processes and statistical QoS constraints are imposed. After formulating energy efficiency (EE) as maximum throughput normalized by the total power consumption, optimal power control policies that maximize EE are obtained for different source models.

Next, throughput and energy efficiency of secure wireless transmission of delay sensitive data generated by random sources are investigated. A fading broadcast model in which the transmitter sends confidential and common messages to two receivers is considered. It is assumed that the common and confidential data, generated from Markovian sources, is stored in buffers prior to transmission, and the transmitter operates under constraints on buffer/delay violation probability. Under such statistical QoS constraints, the throughput is determined. In particular, secrecy capacity is used to describe the service rate of buffers containing confidential messages. Moreover, energy efficiency is studied in the low signal-to-noise (SNR) regime.

In the final part of the thesis, throughput and energy efficiency are addressed considering the multiuser channel models. Five different channel models, namely, multiple access, broadcast, interference, relay and cognitive radio channels, are considered. In particular, throughput regions of multiple-access fading channels are characterized when multiple users, experiencing random data arrivals, transmit to a common receiver under statistical QoS constraints. Throughput regions of fading broadcast channels with random data arrivals in the presence of QoS requirements are studied when power control is employed at the transmitter. It is assumed that superposition coding with power control is performed at the transmitter with interference cancellation at the receivers. Optimal power control policies that maximize the weighted combination of the average arrival rates are investigated in the two-user case. Energy efficiency in two-user fading interference channels is studied when the transmitters are operating subject to QoS constraints. Specifically, energy efficiency is characterized by determining the corresponding minimum energy per bit requirements and wideband slope regions. Furthermore, transmission over a half-duplex relay channel with secrecy and QoS constraints is studied. Secrecy throughput is derived for the half duplex two-hop fading relay system operating in the presence of an eavesdropper. Fundamental limits on the energy efficiency of cognitive radio transmissions are analyzed in the presence of statistical quality of service (QoS) constraints. Minimum energy per bit and wideband slope expressions are obtained in order to identify the performance limits in terms of energy efficiency.


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