Coordinated Multi-Armed Bandits for Improved Spatial Reuse in Wi-Fi
Nokia Bell Labs（诺基亚贝尔实验室）；Universitat Pompeu Fabra（庞培法布拉大学）；AGH University of Krakow（克拉科夫AGH大学）；Centre Tecnològic de Telecomunicacions de Catalunya（加泰罗尼亚电信技术中心）
Francesc Wilhelmi, Boris Bellalta, Szymon Szott, Katarzyna Kosek-Szott, Sergio Barrachina-Muñoz
Multi-Access Point Coordination (MAPC) and Artificial Intelligence and Machine Learning (AI/ML) are expected to be key features in future Wi-Fi, such as the forthcoming IEEE 802.11bn (Wi-Fi~8) and beyond. In this paper, we explore a coordinated solution based on online learning to drive the optimization of Spatial Reuse (SR), a method that allows multiple devices to perform simultaneous transmissions by controlling interference through Packet Detect (PD) adjustment and transmit power control. In particular, we focus on a Multi-Agent Multi-Armed Bandit (MA-MAB) setting, where multiple decision-making agents concurrently configure SR parameters from coexisting networks by leveraging the MAPC framework, and study various algorithms and reward-sharing mechanisms. We evaluate different MA-MAB implementations using Komondor, a well-adopted Wi-Fi simulator, and demonstrate that AI-native SR enabled by coordinated MABs can improve the network performance over current Wi-Fi operation: mean throughput increases by 15%, fairness is improved by increasing the minimum throughput across the network by 210%, while the maximum access delay is kept below 3 ms.
IEEE 802.11be networks (aka Wi-Fi 7) will have to cope with new bandwidth-hungry and low-latency services such as eXtended Reality and multi-party cloud gaming. With this goal in mind, transmit opportunity (TXOP) sharing between coordinated access points (APs) may contribute to alleviating inter-AP contention, hence increasing the overall network throughput. This paper evaluates two coordinated TXOP sharing strategies: coordinated time division multiple access (c-TDMA) and coordinated-TDMA with spatial reuse (c-TDMA/SR). We show that, while c-TDMA alone does not result in any significant impro…
The exponential increase of wireless devices with highly demanding services such as streaming video, gaming and others has imposed several challenges to Wireless Local Area Networks (WLANs). In the context of Wi-Fi, IEEE 802.11ax brings high-data rates in dense user deployments. Additionally, it comes with new flexible features in the physical layer as dynamic Clear-Channel-Assessment (CCA) threshold with the goal of improving spatial reuse (SR) in response to radio spectrum scarcity in dense scenarios. In this paper, we formulate the Transmission Power (TP) and CCA configuration problem with …
Caching high-frequency reuse contents at the edge servers in the mobile edge computing (MEC) network omits the part of backhaul transmission and further releases the pressure of data traffic. However, how to efficiently decide the caching contents for edge servers is still an open problem, which refers to the cache capacity of edge servers, the popularity of each content, and the wireless channel quality during transmission. In this paper, we discuss the influence of unknown user density and popularity of content on the cache placement solution at the edge server. Specifically, towards the imp…
An Asynchronous Triggered MAC Protocol for Underwater Acoustic Networks
College of Computer Science and Technology, Jilin University（吉林大学计算机科学与技术学院）；College of Software Engineering, Jilin University（吉林大学软件学院）；School of Electronic and Information Engineering, Beihang University（北京航空航天大学电子工程学院）；Department of Electrical and Computer Engineering, University of Houston（休斯顿大学电气与计算机工程系）
In this paper, we present Sense-Bandits, an AI-based framework for distributed adaptation of the sensing thresholds (STs) over shared spectrum. This framework specifically targets the coexistence of heterogenous technologies, e.g., Wi-Fi, 4G Licensed-Assisted Access (LAA), and 5G New Radio Unlicensed (NR-U), over unlicensed channels. To access the channel, a device compares the measured power with a predefined ST value and accordingly decides if the channel is idle or not. Improper setting of the ST values creates asymmetric sensing floors, resulting in collisions due to hidden terminals and/o…
