Reinforcement Learning Approaches to Improve Spatial Reuse in Wireless Local Area Networks

The ubiquitous deployment of IEEE 802.11 based Wireless Local Area Networks (WLANs) or WiFi networks has resulted in dense deployments of Access Points (APs) in an effort to provide wireless links with high data rates to users. This, however, causes APs and users/stations to experience a higher interference level. This is because of the limited spectrum in which WiFi networks operate, resulting in multiple APs operating on the same channel. This in turn affects the signal-tonoise-plus interference ratio (SINR) at APs and users, leading to low data rates that limit their quality of service (QoS). To improve QoS, interference management is critical. To this end, a key metric of interest is spatial reuse. A high spatial reuse means multiple transmissions are able to transmit concurrently, which leads to a high network capacity. One approach to optimize spatial reuse is by tuning the clear channel access (CCA) threshold employed by the carrier sense multiple access with collision avoidance (CSMA/CA) medium access control (MAC) protocol. Specifically, the CCA threshold of a node determines whether it is allowed to transmit after sensing the channel. A node may increase its CCA threshold, causing it to transmit even when there are other ongoing transmissions. Another parameter to be tuned is transmit power. This helps a transmitting node lower its interference to neighboring cells, and thus allows nodes in these neighboring cells to transmit as well. Apart from that, channel bonding can be applied to improve transmission rate. In particular, by combining/aggregating multiple channels together, the resulting channel has a proportionally higher data rate than the case without channel bonding. However, the issue of spatial reuse remains the same whereby the focus is to maximize the number of concurrent transmissions across multiple channels

Programación lineal binaria para la planificación de sistemas inalámbricos

Locating access points for Wi-Fi networks in a post-pandemic scenario proposes an application in the planning and restructuring of existing wireless systems. Education strategies such as the flipped classroom, among others, demand the overall performance of the system. In this work, we propose a methodology using binary linear programming as a strategy to achieve the planning of a Wi-Fi system that can have the objectives of coverage, user capacity and channel interference. The results show a better coverage, higher speed per user and optimized the amount of equipment per sector in the laboratories of the University of Magdalena.La localización de puntos de acceso para redes Wi-Fi en un escenario postpandemia propone una aplicación en la planificación y reestructuración de los sistemas inalámbricos existentes. Las estrategias educativas como el aula invertida, entre otras, exigen el desempeño integral del sistema. En este trabajo se propone una metodología utilizando programación lineal binaria como estrategia para lograr la planificación de un sistema Wi-Fi que pueda tener los objetivos de cobertura, capacidad de usuarios e interferencia de canales. Los resultados muestran una mejor cobertura, mayor velocidad por usuario y una cantidad optimizada de equipos por sector en los laboratorios de la Universidad del Magdalena

QoS based Radio Resource Management Techniques for Next Generation MU-MIMO WLANs: A Survey

IEEE 802.11 based Wireless Local Area Networks (WLANs) have emerged as a popular candidate that offers Internet services for wireless users. The demand of data traffic is increasing every day due to the increase in the use of multimedia applications, such as digital audio, video, and online gaming. With the inclusion of Physical Layer (PHY) technologies, such as the OFDM and MIMO, the current 802.11ac WLANs are claiming Gigabit speeds. Hence, the existing Medium Access Control (MAC) must be in a suitable position to convert the offered PHY data rates for efficient throughput. Further, the integration of cellular networks with WLANs requires unique changes at MAC layer. It is highly required to preserve the Quality of Service (QoS) in these scenarios. Fundamentally, many QoS issues arise from the problem of effective Radio Resource Management (RRM). Although IEEE 802.11 has lifted PHY layer aspects, there is a necessity to investigate MAC layer issues, such as resource utilization, scheduling, admission control and congestion control. In this survey, a literature overview of these techniques, namely the resource allocation and scheduling algorithms are briefly discussed in connection with the QoS at MAC layer. Further, some anticipated enhancements proposed for Multi-User Multiple-Input and Multiple-Output (MU-MIMO) WLANs are discussed

Specification of Cooperative Access Points Functionalities version 2

The What to do With the Wi-Fi Wild West H2020 project (Wi-5) combines research and innovation to propose an architecture based on an integrated and coordinated set of smart Wi-Fi networking solutions. The resulting system will be able to efficiently reduce interference between neighbouring Access Points (APs) and provide optimised connectivity for new and emerging services. The project approach is expected to develop and incorporate a variety of different solutions, which will be made available through academic publications, in addition to other dissemination channels. This deliverable presents the specification of the second version of the Cooperative AP Functionalities that are being designed in the context of Work Package (WP) 4 of the Wi-5 project. Specifically, we present a general cooperative framework that includes functionalities for a Radio Resource Management (RRM) algorithm, which provides channel assignment and transmit power adjustment strategies, an AP selection policy, and a solution for vertical handover. The RRM achieves an important improvement for network performance in terms of several parameters through the channel assignment approach, that can be further improved by including the transmit power adjustment. The AP selection solution extends the approach presented in deliverable D4.1 based on the Fittingness Factor (FF) concept, which is a parameter for efficiently matching the suitability of the available spectrum resource to the application requirements. Moreover, the preliminary details, which will allow us to extend AP selection towards vertical handover functionality including 3G/4G networks, are also presented. The assessment of the algorithms proposed in this deliverable is illustrated through the analysis of several performance results in a simulated environment against other strategies found in the literature. Finally, a set of monitoring capabilities implemented on the Wi-5 APs and on the Wi-5 controller are illustrated. These capabilities will enable the correct deployment of the cooperative APs functionalities proposed in this deliverable in realistic scenarios

Location, Location, Location: Maximizing mmWave LAN Performance through Intelligent Wireless Networking Strategies

The main objective of this dissertation is to design and evaluate intelligent techniques to maximize mmWave wireless local-area network (WLAN) performance. To meet the ever-increasing data demand of various bandwidth-hungry applications, we propose techniques to enable consistently ultra-high-rate mmWave communication in the wireless environment. However, the weak diffraction of mmWave signals makes them extremely sensitive to blockage effects caused by real-world obstacles, and this is a primary challenge to overcome for the feasibility of mmWave communications. To this end, we exploit location sensitivity to explore robust mmWave WLAN designs that expedite the full realization of ubiquitous mmWave wireless connectivity. The techniques investigated to exploit location sensitivity are the use of multiple access points (APs), controlled mobility, AP-user association mechanisms, and environment-aware prediction We first develop optimal multi-AP planning approaches to maximize line-of-sight connectivity and aggregate throughput in mmWave WLANs, and then study multi-AP association mechanisms to achieve low-overhead and blockage-robust mmWave wireless communications among multiple users and multiple APs. Furthermore, we explore the potential benefits achievable from AP mobility technology, which yields insights on the best configurations of mobile APs. We also develop an environment-aware link-quality predictor to accurately derive dynamic mmWave link quality due to static blockages and small changes in device locations, which provides a basis for the development of anticipatory networking with proactive resource-allocation schemes. In a complementary direction for evaluating the performance of mmWave networks, we develop and implement advanced features for dense wireless networks that increasingly characterize many mmWave scenarios of interest in the widely-used network simulator ns-3, including a sparse cluster-based wireless channel model that statistically models multi-path components in mmWave WLANs.Ph.D