In Wireless Local Area Networks (WLANs), Access point (AP) transmit power
influences (i) received signal quality for users and thus user throughput, (ii)
user association and thus load across APs and (iii) AP coverage ranges and thus
interference in the network. Despite decades of academic research, transmit
power levels are still, in practice, statically assigned to satisfy uniform
coverage objectives. Yet each network comes with its unique distribution of
users in space, calling for a power control that adapts to users' probabilities
of presence, for example, placing the areas with higher interference
probabilities where user density is the lowest. Although nice on paper, putting
this simple idea in practice comes with a number of challenges, with gains that
are difficult to estimate, if any at all. This paper is the first to address
these challenges and evaluate in a production network serving thousands of
daily users the benefits of a user-aware transmit power control system. Along
the way, we contribute a novel approach to reason about user densities of
presence from historical IEEE 802.11k data, as well as a new machine learning
approach to impute missing signal-strength measurements. Results of a thorough
experimental campaign show feasibility and quantify the gains: compared to
state-of-the-art solutions, the new system can increase the median signal
strength by 15dBm, while decreasing airtime interference at the same time. This
comes at an affordable cost of a 5dBm decrease in uplink signal due to lack of
terminal cooperation.

本文是第一篇在生产网络环境中使用基于用户感知的传输功率控制系统的研究，提出了一种新的方法来评估用户密度和研究了一种新的机器学习方法以估算缺失信号强度测量值。实验表明，相较于现有技术方案，该新系统可以提高 15dBm 的中位信号强度，同时降低空间干扰，代价是由于终端不合作性导致的上行信号强度下降了 5dBm。