Energy Efficiency of Fixed-Rate Wireless Transmissions under QoS Constraints

Abstract

Abstract-1 Transmission over wireless fading channels under quality of service (QoS) constraints is studied when only the receiver has perfect 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 arrival rate that a wireless channel can sustain while satisfying statistical QoS constraints. Energy efficiency is investigated by obtaining the minimum bit energy and wideband slope expressions in both low-power and wideband 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. Overall, an energydelay tradeoff for fixed-rate transmission systems is provided.I. INTRODUCTION Efficient use of limited energy resources is of paramount importance in most wireless systems. From an informationtheoretic perspective, the energy required to reliably send one bit is a metric that can be adopted to measure the energy efficiency. Generally, energy-per-bit requirement is minimized, and hence the energy efficiency is maximized, if the system operates in the low-power or wideband regimes. Recently, Verdú in [1] has determined the minimum bit energy required for reliable communications over a general class of channels, and studied the spectral efficiency-bit energy tradeoff in the wideband regime.While providing powerful results, information-theoretic studies generally do not address delay and quality of service (QoS) constraints [2]. However, the impact upon the queue length and queueing delay of transmission using codes with large blocklength, which are required to achieve the information-theoretic performance limits, can be significant. Situation is even further exacerbated in wireless channels in which the ergodic capacity has an operational meaning only if the codewords are long enough to span all fading states. Hence, in slow fading environments, large delays can be experienced in order to achieve the ergodic capacity. Due to these considerations, performance metrics such as capacity versus outage [3] and delay limited capacity [4] have been considered in the literature for slow fading scenarios.

Performance Analysis of the Uplink of a Two User NOMA Network under QoS Delay Constraints

“…1 show that as the normalized delay exponent β i , i = {1, 2} decreases (i.e., the application has stricter delay-constraints), the value of the EC for both users decreases, i.e., the achievable data link layer rates while guaranteeing a certain level of delay QoS constraint decrease. This result is in agreement with the respective trend in OMA networks [11].…”

Effective Capacity Maximization in Multi-Antenna Channels with Covariance Feedback

“…In [13], an adaptive resource allocation using this performance measure is studied. Moreover, the effective capacity at low SNR, considering energy efficiency, is studied in [14]. QoS based power allocation in a cognitive radio scenario is considered in [15].…”

Energy Efficiency of Fixed-Rate Wireless Transmissions under Queueing Constraints and Channel Uncertainty

“…4, we compare the performance of this system with those in which the channel is perfectly-known and fixed-or variable-rate transmission is employed. The latter models have been studied in [8] and [9]. This figure demonstrates the energy costs of not knowing the channel and sending the information at fixed-rate.…”

“…Effective capacity formulation uses the large deviations theory and incorporates the statistical queueing constraints by capturing the rate of decay of the buffer occupancy probability for large queue lengths. The analysis and application of effective capacity in various settings have attracted much interest recently (see e.g., [5]- [9] and references therein).…”