Wireless Throughput and Energy Efficiency under QoS Constraints

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

Energy-Efficient Resource Allocation in Wireless Networks with Quality-of-Service Constraints

A game-theoretic model is proposed to study the cross-layer problem of joint power and rate control with quality of service (QoS) constraints in multiple-access networks. In the proposed game, each user seeks to choose its transmit power and rate in a distributed manner in order to maximize its own utility while satisfying its QoS requirements. The user's QoS constraints are specified in terms of the average source rate and an upper bound on the average delay where the delay includes both transmission and queuing delays. The utility function considered here measures energy efficiency and is particularly suitable for wireless networks with energy constraints. The Nash equilibrium solution for the proposed non-cooperative game is derived and a closed-form expression for the utility achieved at equilibrium is obtained. It is shown that the QoS requirements of a user translate into a "size" for the user which is an indication of the amount of network resources consumed by the user. Using this competitive multiuser framework, the tradeoffs among throughput, delay, network capacity and energy efficiency are studied. In addition, analytical expressions are given for users' delay profiles and the delay performance of the users at Nash equilibrium is quantified.Comment: Accpeted for publication in the IEEE Transactions on Communication

Energy-Efficient Resource Allocation in Wireless Networks: An Overview of Game-Theoretic Approaches

An overview of game-theoretic approaches to energy-efficient resource allocation in wireless networks is presented. Focusing on multiple-access networks, it is demonstrated that game theory can be used as an effective tool to study resource allocation in wireless networks with quality-of-service (QoS) constraints. A family of non-cooperative (distributed) games is presented in which each user seeks to choose a strategy that maximizes its own utility while satisfying its QoS requirements. The utility function considered here measures the number of reliable bits that are transmitted per joule of energy consumed and, hence, is particulary suitable for energy-constrained networks. The actions available to each user in trying to maximize its own utility are at least the choice of the transmit power and, depending on the situation, the user may also be able to choose its transmission rate, modulation, packet size, multiuser receiver, multi-antenna processing algorithm, or carrier allocation strategy. The best-response strategy and Nash equilibrium for each game is presented. Using this game-theoretic framework, the effects of power control, rate control, modulation, temporal and spatial signal processing, carrier allocation strategy and delay QoS constraints on energy efficiency and network capacity are quantified.Comment: To appear in the IEEE Signal Processing Magazine: Special Issue on Resource-Constrained Signal Processing, Communications and Networking, May 200

Energy-efficient wireless communication

In this chapter we present an energy-efficient highly adaptive network interface architecture and a novel data link layer protocol for wireless networks that provides Quality of Service (QoS) support for diverse traffic types. Due to the dynamic nature of wireless networks, adaptations in bandwidth scheduling and error control are necessary to achieve energy efficiency and an acceptable quality of service. In our approach we apply adaptability through all layers of the protocol stack, and provide feedback to the applications. In this way the applications can adapt the data streams, and the network protocols can adapt the communication parameters

Energy and bursty packet loss tradeoff over fading channels: a system-level model

Energy efficiency and quality of service (QoS) guarantees are the key design goals for the 5G wireless communication systems. In this context, we discuss a multiuser scheduling scheme over fading channels for loss tolerant applications. The loss tolerance of the application is characterized in terms of different parameters that contribute to quality of experience (QoE) for the application. The mobile users are scheduled opportunistically such that a minimum QoS is guaranteed. We propose an opportunistic scheduling scheme and address the cross-layer design framework when channel state information (CSI) is not perfectly available at the transmitter and the receiver. We characterize the system energy as a function of different QoS and channel state estimation error parameters. The optimization problem is formulated using Markov chain framework and solved using stochastic optimization techniques. The results demonstrate that the parameters characterizing the packet loss are tightly coupled and relaxation of one parameter does not benefit the system much if the other constraints are tight. We evaluate the energy-performance tradeoff numerically and show the effect of channel uncertainty on the packet scheduler design