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

TL;DR

This paper examines how QoS constraints affect the energy efficiency of fixed-rate wireless transmissions over fading channels, considering scenarios with perfect and imperfect channel information, and identifies optimal power allocation strategies.

Contribution

It introduces a two-state ON-OFF transmission model under QoS constraints and analyzes energy efficiency metrics, including minimum bit energy and optimal training power allocation.

Findings

QoS constraints increase energy requirements in low-power regimes.

Minimum bit energy is achieved at a nonzero power level, not at zero power.

Optimal training power fraction is identified under QoS constraints.

Abstract

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.