Rate, power and carrier-sense threshold coordinated management for high-density IEEE 802.11 networks

Abstract

Nowadays, trying to obtain better coverage and performance, and allowed by the low-hardware prices, it is common to deploy a large number of IEEE 802.11 devices in offices, meeting rooms or auditoriums configuring the so called highdensity networks. In such a scenario, the shared nature of the transmission medium causes interference problems. Some physicallayer-and link-layer-adaptation mechanisms to palliate those problems have been developed, however, most of them have not been independently implemented and assessed. In this paper, we implement in a simulator some of the existent solutions, compare them in a simulation environment and show that, in some situations, the existing solutions can lead to a starvation problem. Finally, we propose a new mechanism that manages datarate, transmit power and carrier-sense threshold to ameliorate this problem.

On the energy efficiency of rate and transmission power control in 802.11

“…3 As stated before, RA is a very prolific research line in the literature, but the main corpus is dedicated to the MCS adjustment without taking into account the TXP [4]. There is some work considering TPC, but the motivation is typically the performance degradation due to network densification, and the aim is interference mitigation [14] and not energy efficiency. Given that we are interested in assessing RA implementations with TPC support, we consider only open-source algorithms that can be tested using the NS3 Network Simulator.…”

“…• Robust Rate and Power Adaptation Algorithm (RRPAA) and Power, Rate and Carrier-Sense Control (PRCS) [14], which are based on Robust Rate Adaptation Algorithm (RRAA) [17]. RRAA consists of two functional blocks, namely, rate adaptation and collisions elimination.…”

“…This evaluation is publicly available, 4 and builds upon the code provided by Richart et al in [14]. 5 .…”

“…12a normalised where t sim is the simulation time and max(MCS) is 54 Mbps in our case. The same concept can be applied to the TXP: TXP = 1 max(TXP) • t sim tsim 0 TXP(t)dt (14) where max(TXP) is 17 dBm in our case. Both MCS and TXP are unitless scores between 0 and 1, and lower values mean a more conservative algorithm.…”