Effective Capacity Maximization With Statistical Delay and Effective Energy Efficiency Requirements

This paper presents the three-fold energy, rate and delay tradeoff in mobile multimedia fading channels. In particular, we propose a rate-efficient power allocation strategy for delay-outage limited applications with constraints on energy-per-bit consumption of the system. For this purpose, at a target delay-outage probability, the link-layer energy efficiency, referred to as effective-EE, is measured by the ratio of effective capacity (EC) and the total expenditure power, including the transmission power and the circuit power. At first, the maximum effective-EE of the channel at a target delay-outage probability is found. Then, the optimal power allocation strategy is obtained to maximize EC subject to an effective-EE constraint with the limit set at a certain ratio of the maximum achievable effective-EE of the channel. We then investigate the effect of the circuit power level on the maximum EC. Further, to set a guideline on how to choose the effective-EE limit, we obtain the transmit power level at which the rate of increasing EC (as a function of transmit power) matches a scaled rate of losing effective-EE. Analytical results show that a considerable EC-gain can be achieved with a small sacrifice in effective-EE from its maximum value. This gain increases considerably as the delay constraint becomes tight

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

The Impact of QoS Constraints on the Energy Efficiency of Fixed-Rate Wireless Transmissions

Transmission over wireless fading channels under quality of service (QoS) constraints is studied when only the receiver has channel side information. Being unaware of the channel conditions, transmitter is assumed to send the information at a fixed rate. Under these assumptions, a two-state (ON-OFF) transmission model is adopted, where information is transmitted reliably at a fixed rate in the ON state while no reliable transmission occurs in the OFF state. QoS limitations are imposed as constraints on buffer violation probabilities, and effective capacity formulation is used to identify the maximum throughput that a wireless channel can sustain while satisfying statistical QoS constraints. Energy efficiency is investigated by obtaining the bit energy required at zero spectral efficiency and the wideband slope in both wideband and low-power regimes assuming that the receiver has perfect channel side information (CSI). In both wideband and low-power regimes, the increased energy requirements due to the presence of QoS constraints are quantified. Comparisons with variable-rate/fixed-power and variable-rate/variable-power cases are given. Energy efficiency is further analyzed in the presence of channel uncertainties. The optimal fraction of power allocated to training is identified under QoS constraints. It is proven that the minimum bit energy in the low-power regime is attained at a certain nonzero power level below which bit energy increases without bound with vanishing power