Energy-Efficient Power Control in Fading Channels With Markovian Sources and QoS Constraints

Abstract

In this paper, energy-efficient power adaptation policies in fading channels are analyzed when data arrivals are modeled as Markovian processes (namely, discrete Markov, Markov fluid, and discrete and fluid Markov modulated Poisson processes) and statistical quality of service (QoS) constraints are imposed on buffer overflow probabilities. In the analysis, both transmission and circuit power consumptions are considered. 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. The impact of source randomness on EE is determined. Optimal power control schemes maximizing the throughput under EE or average power constraints are also investigated. With this, tradeoff between throughput and EE is studied. Finally, the analysis is extended to multichannel scenarios. Overall, the influence of source statistics, QoS constraints, and number of subchannels on the optimal power control policies, throughput, and EE performance is identified.