A PERFORMANCE ANALYSIS OF IEEE 802.11ax NETWORKS

The paper is focused on the forthcoming IEEE 802.11ax standard and its influence on Wi-Fi networks performance. The most important features dedicated to improve transmission effectiveness are presented. Furthermore, the simulation results of a new transmission modes are described. The comparison with the legacy IEEE 802.11n/ac standards shows that even partial implementation of a new standard should bring significant throughput improvements

Lyapunov Optimization-Based Latency-Bounded Allocation Using Deep Deterministic Policy Gradient for 11ax Spatial Reuse

With the growing demand for wireless local area network (WLAN) applications that require low latency, orthogonal frequency-division multiple access (OFDMA) has been adopted for uplink and downlink transmissions in the IEEE 802.11ax standard to improve the spectrum efficiency and reduce the latency. In IEEE 802.11ax WLANs, OFDMA resource allocation that guarantees latency, called latency-bounded resource allocation, is more challenging than that in cellular networks because severe unmanaged interference from overlapping basic service sets is enhanced due to the concurrent-transmission mechanism newly employed in IEEE 802.11ax. To improve the downlink OFDMA resource allocation with the unmanaged interference caused by IEEE 802.11ax concurrent transmissions, we propose Lyapunov optimization-based latency-bounded allocation with reinforcement learning (RL). We focus on the transmission-queue size for each station (STA) at the access point that determines the STA latency. Using Lyapunov optimization, we formulate the resource-allocation problem with the queue-size constraints in a form that can be solved using RL (i.e., a Markov decision process) and prove the upper bound of the queue size. Our simulation results demonstrated that the proposed method, which uses an RL algorithm with a deep deterministic policy gradient, satisfied the queue-size constraints. This means that the proposed method met the latency requirements, while some baseline methods failed to meet them. Furthermore, the proposed method achieved a higher fairness index than the baseline methods

WI-FI 6: CARACTERÍSTICAS Y ASPECTOS PARTICULARES DEL ESTÁNDAR (IEEE-802.11AX WI-FI 6: CHARACTERISTICS AND PARTICULAR ASPECTS OF THE IEEE-802.11AX STANDARD)

ResumenEl estándar IEEE 802.11 de red de área local inalámbrica se ha desarrollado por más de 28 años desde su primera versión con velocidad a 2 Mbit/s. La última versión de Wi-Fi está por aparecer, la versión ax, que alcanza la velocidad de 10 Gbit/s. IEEE 802.11ax fue concebido en 2014 con el objetivo de mejorar el rendimiento por área en escenarios de alta densidad. Describiremos las principales características de 802.11ax. En este trabajo se hace una revisión bibliográfica de las principales diferencias entre este nuevo estándar y las versiones anteriores. Entre las diferencias se pueden mencionar las siguientes; el enfoque de acceso aleatorio con división de frecuencia ortogonales, nuevas técnicas de reutilización de canales espaciales y control de potencia. Además, se destacarán otras mejoras significativas seleccionadas; incluyendo mejoras en la capa física, múltiples usuarios con múltiples entradas y salidas, avances en el ahorro de energía, etc. que hacen este estándar una mejora importante con respecto a su predecesor 802.11ac.Palabras clave: Ahorro de potencia, Calidad de servicio, OFDMA, MU-MIMO, Redes de alta densidad, Redes de alta eficiencia. AbstractThe IEEE 802.11 wireless local area network standard has been developed for more than 28 years since its first version with a speed of 2 Mbit / s. The latest version of Wi-Fi is about to appear, the ax version, which reaches the speed of 10 Gbps. IEEE 802.11ax was conceived in 2014 with the objective of improving performance per area in high density scenarios. We will describe the main features of 802.11ax, among which may be mentioned the following; the random access approach with orthogonal frequency division, new spatial channel reuse techniques and power control. In addition, other significant improvements selected will be highlighted; including improvements in the physical layer, multiple users with multiple inputs and outputs, advances in energy saving, etc. that make this standard a significant improvement over its predecessor 802.11ac.Keywords: High density networks, High efficiency networks, OFDMA, MU-MIMO, QoS, Power saving

Insights on the Next Generation WLAN: High Experiences (HEX)

Wireless local area network (WLAN) witnesses a very fast growth in the past 20 years by taking the maximum throughput as the key technical objective. However, the quality of experience (QoE) is the most important concern of wireless network users. In this article, we point out that poor QoE is the most challenging problem of the current WLAN, and further analyze the key technical problems that cause the poor QoE of WLAN, including fully distributed networking architecture, chaotic random access, awkward ``high capability'', coarse-grained QoS architecture, ubiquitous and complicated interference, ``no place'' for artificial intelligence (AI), and heavy burden of standard evolving. To the best of our knowledge, this is the first work to point out that poor QoE is the most challenging problem of the current WLAN, and the first work to systematically analyze the technical problems that cause the poor QoE of WLAN. We highly suggest that achieving high experiences (HEX) be the key objective of the next generation WLAN

Usage of Network Simulators in Machine-Learning-Assisted 5G/6G Networks

Without any doubt, Machine Learning (ML) will be an important driver of future communications due to its foreseen performance when applied to complex problems. However, the application of ML to networking systems raises concerns among network operators and other stakeholders, especially regarding trustworthiness and reliability. In this paper, we devise the role of network simulators for bridging the gap between ML and communications systems. In particular, we present an architectural integration of simulators in ML-aware networks for training, testing, and validating ML models before being applied to the operative network. Moreover, we provide insights on the main challenges resulting from this integration, and then give hints discussing how they can be overcome. Finally, we illustrate the integration of network simulators into ML-assisted communications through a proof-of-concept testbed implementation of a residential Wi-Fi network

IEEE 802.11ba -- Extremely Low Power Wi-Fi for Massive Internet of Things: Challenges, Open Issues, Performance Evaluation

Many recent activities of IEEE 802.11 Working group have been focused on improving power efficiency of Wi-Fi to make it favorable for massive Internet of Things scenarios, in which swarms of battery supplied sensors rarely communicate with remote servers. The latest step towards this direction is the work on a new IEEE 802.11ba amendment to the Wi-Fi standard, which introduces Wake-Up Radio. This radio is an additional interface with extremely low power consumption that is used to transmit control information from the access point to stations while their primary radio is switched off. This paper describes the IEEE 802.11ba protocol, discusses its open issues, investigates several approaches to provide energy efficient data transmission with 802.11ba, and evaluates how much 802.11ba improves energy efficiency and even reduces channel time consumption