Improving Energy Efficiency in Idle Listening of IEEE 802.11 WLANs

Abstract

This paper aims to improve energy efficiency of IEEE 802.11 wireless local area networks (WLANs) by effectively dealing with idle listening (IL), which is required for channel sensing and is unavoidable in a contention-based channel access mechanism. Firstly, we show that IL is a dominant source of energy drain in WLANs and it cannot be effectively alleviated by the power saving mechanism proposed in the IEEE 802.11 standard. To solve this problem, we propose an energy-efficient mechanism that combines three schemes in a systematic way: downclocking, frame aggregation, and contention window adjustment. The downclocking scheme lets a station remain in a semisleep state when overhearing frames destined to neighbor stations, whereby the station consumes the minimal energy without impairing channel access capability. As well as decreasing the channel access overhead, the frame aggregation scheme prolongs the period of semisleep time. Moreover, by controlling the size of contention window based on the number of stations, the proposed mechanism decreases unnecessary IL time due to collision and retransmission. By deriving an analysis model and performing extensive simulations, we confirm that the proposed mechanism significantly improves the energy efficiency and throughput, by up to 2.8 and 1.8 times, respectively, compared to the conventional power saving mechanisms.

Energy-Efficient mm-Wave Backhauling via Frame Aggregation in Wide Area Networks

“…The number of WGNs decreases with increasing values of R [11], which explains the descending trend in the latency and power consumption 4 . However, certain nonlinearities are introduced in the trend since the total number of RNs does not monotonically decrease with R. For instance, an abrupt increase in the latency and the power consumption is seen in both surveys around R = 570 m. This is due to the fact that the outage probability threshold in (35) can only be met by the introduction of additional RNs. Hence, although it may seem counter-intuitive that the power consumption would increase despite a drop in the number of WGNs, it is important to consider the number of RNs that are required to sustain reliable and real-time acquisition for larger values of R.…”

“…However, the aspect of power conservation has not been considered in the above studies. FA is employed in [35], [36] to conserve power by reducing the period of idle listening, albeit only for stations that receive frames which are not intended for them. Analytical expressions for the latency and energy consumption have been derived in [37] for a sensor network employing the S-MAC protocol with frame aggregation.…”

“…Constraint (34) ensures a stable queue model and a minimum sleep duration of t min sl . Constraint (35) enforces a maximum outage probability of p th,out . The time threshold for real-time acquisition is denoted by L max , implying that (36) represents the latency constraint at the DCC.…”

“…Solving the above problem is a challenging task in the presence of CCI, primarily due to the interdependency between various sub-links in (1) which in turn renders constraint (35) to be non-differentiable. In order to yield a more tractable problem, an important assumption is made wherein the presence of CCI is ignored (p cci l ′ = 0).…”