This paper evaluates the performance of Wi-Fi networks for interactive Virtual Reality (VR) streaming with adaptive bitrate control. It focuses on the interaction between VR traffic characteristics and Wi-Fi link-layer mechanisms, studying how this relationship impacts key performance indicators such as throughput, latency, and user scalability. We begin by outlining the architecture, operation, traffic patterns, and performance demands of cloud/edge split-rendering VR systems. Then, using simulations, we investigate both single-user scenarios—examining the effects of modulation and coding schemes (MCSs) and user-to-access point (AP) distance on bitrate sustainability and latency—and multi-user scenarios, assessing how many concurrent VR users a single AP can support. Results show that the use of adaptive bitrate (ABR) streaming, as exemplified by our NeSt-VR algorithm, significantly outperforms constant bitrate (CBR) approaches, enhancing user capacity and resilience to changing channel propagation conditions. To validate the simulation findings, we conduct an experimental evaluation using Rooms, an open-source eXtended Reality (XR) content creation platform. The experimental results closely match the simulations, reinforcing the conclusion that adaptive bitrate control substantially improves Wi-Fi’s ability to support reliable, multiuser interactive VR streaming.

In this article, we explore communication problems in virtual reality (VR) systems from the perspective of wireless networking. Our starting point is that the dynamics of real-time interaction between the physical and virtual worlds cannot be fully captured by the frame rate. Particularly, the frame rate can be very high, but the actual user experience can be disappointing. We argue that the key idea is to think of VR as the mediator of the senses, especially vision, rather than a conventional video streaming application. This is indeed a remarkable opportunity to recall Weaver's classification and define three fundamental problems in VR systems: i) responsiveness, ii) timeliness, and iii) effectiveness. Responsiveness refers to the delay between an action in the physical world and its display in the virtual world. Timeliness is related to the frequency of updates imposed by the frame rate. Effectiveness considers the visual content of a video frame and its likelihood of extrapolation. Our framework offers a concise and objective description of VR systems, that allows us to evaluate performance, identify potential issues, and design impactful solutions.

We study the peeker's advantage in first-person shooters, a classic problem in multiplayer games. A player, the peeker, who first observes another player, the defender, has a strategic advantage. The peeker has the opportunity to aim and shoot first, as the defender is not aware of the peeker's presence for a short amount of time. Formally, the peeker's advantage is the length of time that the peeker sees the defender without being seen. This is an inherent problem of multiplayer games, where each player runs their own instance of the game and relies on updates from an authoritative game server to get informed about the global game state. In this article, we explore the peeker's advantage with extensive simulations, by varying the system delays, the network delays, and the reaction times of the players. First, we present our multiplayer abstraction that captures the essence of first-person shooters, including client and server logic as well as the exchanged messages. Next, we show that the game frame rate is the most influential factor, while the game server tick rate and network delays have minimal impact. Specifically, we show that by using 120 fps in the game and 60 ticks/s on the game server, the peeker's advantage can be dropped below 100 ms. Finally, using realistic, standards-compliant simulations, we show that this advantage is consistent across multiple configurations, both in local area networks and over the Internet.

Cloud-based Virtual Reality (VR) streaming presents significant challenges for 802.11 networks due to its high throughput and low latency requirements. When multiple VR users share a Wi-Fi network, the resulting uplink and downlink traffic can quickly saturate the channel. This paper investigates the capacity of 802.11 networks for supporting realistic VR streaming workloads across varying frame rates, bitrates, codec settings, and numbers of users. We develop an emulation framework that reproduces Air Light VR (ALVR) operation, where real HEVC video traffic is fed into an 802.11 simulation model. Our findings explore Wi-Fi’s performance anomaly and demonstrate that Intra-refresh (IR) coding effectively reduces latency variability and improves QoS, supporting up to 4 concurrent VR users with Constant Bitrate (CBR) 100 Mbps before the channel is saturated.

The densification of Wi-Fi deployments means that fully distributed random channel access is no longer sufficient for high and predictable performance. Therefore, the upcoming IEEE 802.11bn amendment introduces multi-access point coordination (MAPC) methods. This paper addresses a variant of MAPC called coordinated spatial reuse (C-SR), where devices transmit simultaneously on the same channel, with the power adjusted to minimize interference. The C-SR scheduling problem is selecting which devices transmit concurrently and with what settings. We provide a theoretical upper bound model, optimized for either throughput or fairness, which finds the best possible transmission schedule using mixed-integer linear programming. Then, a practical, probing-based approach is proposed which uses multi-armed bandits (MABs), a type of reinforcement learning, to solve the C-SR scheduling problem. We validate both classical (flat) MAB and hierarchical MAB (H-MAB) schemes with simulations and in a testbed. Using H-MABs for C-SR improves aggregate throughput over legacy IEEE 802.11 (on average by 80% in random scenarios), without reducing the number of transmission opportunities per station. Finally, our framework is lightweight and ready for implementation in Wi-Fi devices.

Today, Wi-Fi is over 25 years old. Yet, despite sharing the same branding name, today’s Wi-Fi boasts entirely new capabilities that were not even on the roadmap 25 years ago. This article aims to provide a holistic and comprehensive technical and historical tutorial on Wi-Fi, beginning with Institute of Electrical and Electronics Engineers 802.11b (Wi-Fi 1) and looking forward to IEEE 802.11bn (Wi-Fi 8). This is the first tutorial article to span these eight generations. Rather than a generation-by-generation exposition, we describe the key mechanisms that have advanced Wi-Fi. We begin by discussing spectrum allocation and coexistence, and detailing the IEEE 802.11 standardization cycle. Second, we provide an overview of the physical layer (PHY) and describe key elements that have enabled data rates to increase by over 1000×. Third, we describe how Wi-Fi medium access control (MAC) has been enhanced from the original distributed coordination function (DCF) to now include capabilities spanning from frame aggregation to wideband spectrum access. Fourth, we describe how Wi-Fi 5 first broke the one-user-at-a-time paradigm and introduced multi-user (MU) access. Fifth, given the increasing use of mobile, battery-powered devices, we describe Wi-Fi’s energy-saving mechanisms over the generations. Sixth, we discuss how Wi-Fi was enhanced to seamlessly aggregate spectrum across 2.4-, 5-, and 6-GHz bands to improve throughput, reliability, and latency. Finally, we describe how Wi-Fi enables nearby access points (APs) to coordinate in order to improve performance and efficiency. In the Appendix, we further discuss Wi-Fi developments beyond 802.11bn, including integrated millimeter-wave (IMMW) operations, sensing, security and privacy extensions, and the adoption of artificial intelligence (AI)/machine learning (ML).

Large-scale virtual reality (VR) enables novel art forms in large physical environments. A key technical solution in such cases is to split the rendering process between a client and a streamer. In this article, we focused on the peculiarities of VR split rendering and particularly on the performance of Wi-Fi. First, we calculated the network delay budget and then conducted a set of experiments to evaluate the single-user and multi-user performance of VR split rendering systems over Wi-Fi in terms of latency. Our findings were summarized as recommendations on: i) the frame rate, ii) the encoding bitrate, iii) the signal strength, iv) the channel bandwidth, and v) the multiple access techniques. In particular, our multi-user tests highlighted cases where using the highest settings or latest features of Wi-Fi can compromise performance. Finally, we applied our recommendations to a large-scale multi-user case study that took place physically in the multi-purpose hall of our university campus and virtually in the Turret Singers environment of SteamVR Home. This article serves as a reference to the critical aspects of VR split rendering systems over Wi-Fi.

Hitting a high frame rate is the holy grail of virtual reality (VR). Indeed, a high frame rate offers an amazing experience, but also pushes current technology to its limits. This is particularly true for networked VR gaming systems which rely on split rendering between a client and a server. In this paper, we investigate the impact of frame rate on such systems in terms of responsiveness and timeliness, using both experiments and simulations. Responsiveness refers to how quickly the information is exchanged, while timeliness refers to the frequency of updates. In terms of responsiveness, we show that 90 fps and 120 fps may tolerate up to 6 ms network delay. In terms of timeliness, we show that the best choices are 120 fps when network delay is low and 60 fps when network delay is high.

Interactive Virtual Reality (VR) streaming over Wi-Fi networks encounters significant challenges due to bandwidth fluctuations caused by channel contention and user mobility. Adaptive BitRate (ABR) algorithms dynamically adjust video encoding bitrate based on the available network capacity, aiming to maximize image quality while mitigating congestion and preserving the user's Quality of Experience (QoE). In this paper, we experiment with ABR algorithms for VR streaming using Air Light VR (ALVR), an open-source VR streaming solution. We extend ALVR with a comprehensive set of metrics that provide a robust characterization of the network state, enabling more informed bitrate adjustments. To demonstrate the utility of these performance indicators, we develop and test the Network-aware Step-wise ABR algorithm for VR streaming (NeSt-VR). Results validate the accuracy of the implemented network performance metrics and demonstrate NeSt-VR's adaptation capabilities.

Wi-Fi 7, based on the IEEE 802.11be amendment, is designed to increase the maximum achievable throughput, expand the range of operating frequencies, and improve latency and jitter in worst-case scenario. In the context of the discussions to shape what Wi-Fi 8 will be, the IEEE 802.11 WG is evaluating multi-AP coordination as a strategy to further improve network performance in several aspects. MAC-driven multi-AP coordination strategies include coordinated Orthogonal Frequency Division Multiple Access (c-OFDMA), coordinated Time Division Multiple Access (c-TDMA), and coordinated Spatial Reuse (c-SR). In c-OFDMA, a set of APs transmit during a Transmission Opportunity on different channels, whereas in c-TDMA, the APs take turns transmitting on the same channel during a Transmission Opportunity. Instead, in c-SR, a set of APs transmit simultaneously on the same channel and during the same Transmission Opportunity. In this paper, we focus on c-SR. We introduce a c-SR interference model and present a strategy based on the proposed model for estimating groups of APs that can transmit successfully simultaneously. We implemented the proposed approach in the multi-AP coordination framework of ns-3 that we developed to analyze c-TDMA. We then thoroughly evaluate the performance of the proposed c-SR scheme via ns-3 simulations. The proposed scheme allows increasing the system throughput of a dense deployment up to 2.3 times as well as substantially reducing the Head of Line delay.

Virtual Reality (VR) streaming enables end-users to seamlessly immerse themselves in interactive virtual environments using even low-end devices. However, the quality of the VR experience heavily relies on Wireless Fidelity (Wi-Fi) performance, since it serves as the last hop in the network chain. Our study delves into the intricate interplay between Wi-Fi and VR traffic, drawing upon empirical data and leveraging a Wi-Fi simulator. In this work, we further evaluate Wi-Fi’s suitability for VR streaming in terms of the Quality of Service (QoS) it provides. In particular, we employ Unity Render Streaming to remotely stream real-time VR gaming content over Wi-Fi 6 using Web Real-Time Communication (WebRTC), considering a server physically located at the network’s edge, near the end user. Our findings demonstrate the system’s sustained network performance, showcasing minimal round-trip time (RTT) and jitter at 60 and 90 frames per second (fps). In addition, we uncover the characteristics and patterns of the generated traffic streams, unveiling a distinctive video transmission approach inherent to WebRTC-based services: the systematic packetization of video frames (VFs) and their transmission in discrete batches at regular intervals, regardless of the targeted frame rate. This interval-based transmission strategy maintains consistent video packet delays across video frame rates but leads to increased Wi-Fi airtime consumption. Our results demonstrate that shortening the interval between batches is advantageous, as it enhances Wi-Fi efficiency and reduces delays in delivering complete frames.

In this article, we investigate the real-world capability of the multi-link operation (MLO) framework—one of the key MAC-layer features included in the IEEE 802.11be amendment—by using a large dataset containing 5 GHz spectrum occupancy measurements on multiple channels. Our results show that when both available links are often busy, as is the case in ultra-dense and crowded scenarios, MLO attains the highest throughput gains over single-link operation (SLO) since it is able to leverage multiple intermittent transmission opportunities. As for latency, if the two links exhibit statistically the same level of occupancy, MLO can outperform SLO by one order of magnitude. In contrast, in asymmetrically occupied links, MLO can sometimes be detrimental and even increase latency. We study this somewhat unexpected phenomenon, and find its origins to be packets suboptimally mapped to either link before carrying out the backoff, with the latter likely to be interrupted on the busier link. We cross validate our study with real-time traffic generated by a cloud gaming application and quantify MLO’s benefits for latency-sensitive applications.

Will Wi-Fi 7, conceived to support extremely high throughput, also deliver consistently low delay? The best hope seems to lie in allowing next-generation devices to access multiple channels via multi-link operation (MLO). In this paper, we aim to advance the understanding of MLO, placing the spotlight on its packet delay performance. We show that MLO devices can take advantage of multiple contention-free links to significantly reduce their transmission time, but also that they can occasionally starve one another and surprisingly incur a higher delay than that of a well planned legacy single link operation. We examine and explain this anomaly, also putting forth practical workarounds.

Wi-Fi 7 is already in the making, and Multi-Link Operation (MLO) is one of the main features proposed in its correspondent IEEE 802.11be amendment. MLO will allow devices to coordinate multiple radio interfaces to access separate channels through a single association, aiming for improved throughput, network delay, and overall spectrum reuse efficiency. In this work, we study three reference scenarios to evaluate the performance of the two main MLO implementations— Multi-Link Multi-Radio (MLMR) and Multi-Link Single-Radio (MLSR)—, the interplay between multiple nodes employing them, and their coexistence with legacy Single-Link devices. Importantly, our results reveal that the potential of MLMR is mainly unleashed in isolated deployments or under unloaded network conditions. Instead, in medium- to high-load scenarios, MLSR may prove more effective in reducing the latency while guaranteeing fairness with contending Single-Link nodes.

The pioneering field of tactile Internet (TI) will enable the transfer of human skills over long distances through haptic feedback. Realizing this demands a roundtrip latency of sub-5 ms. In this work, we investigate the capability of Wi-Fi 6 and existing TI scheduling/multiplexing schemes in meeting this stringent latency constraint. Taking the concrete example of the state-of-the-art video-haptic multiplexer (VH-multiplexer), we highlight the pitfalls of relying on the existing Wi-Fi 6 systems for TI communication. To circumvent this, we propose video-tactile latency scheduler (ViTaLS)—a novel link layer framework for tuning the video-tactile frame transmissions to suit their heterogeneous Quality of Service requirements. We present a mathematical model to characterize the packet transmission duration of ViTaLS. Using a custom simulator, we validate our model and measure the objective performance improvement of ViTaLS over VH-multiplexer. We also present ViTaLS-optimal—a variant of ViTaLS, for further 4 reducing the tactile latency. Objectively, we show that ViTaLS-optimal yields a latency improvement of up to 82 %. Based on experiments conducted on a real TI testbed, we subjectively demonstrate that ViTaLS-optimal outperforms the VH-multiplexer.

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 improvement in terms of the WLAN throughput, it lays the groundwork to implement coordinated SR (c-SR) techniques. To evaluate the performance of c-TDMA/SR, we propose a fair scheduler able to select the best subset of parallel transmissions in WLAN deployments, as well as the appropriate power levels to be used by APs and stations (STAs), leading to maximum performance. The results obtained for c-TDMA/SR show significant throughput gains compared with c-TDMA, with values higher than 140% in 90% of the considered scenarios.

Will Multi-Link Operation (MLO) be able to improve the latency of Wi-Fi networks? MLO is one of the most disruptive MAC-layer techniques included in the IEEE 802.11be amendment. It allows a device to use multiple radios simultaneously and in a coordinated way, providing a new framework to improve the WLAN throughput and latency. In this paper, we investigate the potential latency benefits of MLO by using a large dataset containing 5 GHz spectrum occupancy measurements. Experimental results show that when the channels are symmetrically occupied, MLO can improve latency by one order of magnitude. In contrast, in asymmetrically occupied channels, MLO can sometimes be detrimental and increase latency. This is a result of packets being assigned to an interface before carrying out the backoff, which is more likely to be interrupted on the busier link. We overcome this issue by allowing multiple backoffs to run in parallel, assigning the packet to the particular interface where the backoff expires first, which also achieves lower latency overall.

Interactive, real-time, and high-quality cloud video games pose a serious challenge to the Internet due to simultaneous high-throughput and low round trip delay requirements. In this paper, we investigate the traffic characteristics of Stadia, the cloud-gaming solution from Google, which is likely to become one of the dominant players in the gaming sector. To do that, we design several experiments, and perform an extensive traffic measurement campaign to obtain all required data. Our first goal is to gather a deep understanding of Stadia traffic characteristics by identifying the different protocols involved for both signaling and video/audio contents, the traffic generation patterns, and the packet size and inter-packet time probability distributions. Then, our second goal is to understand how different Stadia games and configurations, such as the video codec and the video resolution selected, impact on the characteristics of the generated traffic. We also evaluate the ability of Stadia to adapt to different link capacity conditions, including cases where the capacity drops suddenly, as well as sudden increases in the network latency. Our results and findings, besides illustrating the characteristics of Stadia traffic, are also valuable for planning and dimensioning future networks, as well as for designing new resource management strategies. Finally, we compare Stadia traffic to other video streaming applications, showcasing the main differences between them, and introduce a traffic model using our captures. We show that this model can be used in simulations to further investigate the network performance in presence of Stadia traffic.

Terahertz (THz) communication is widely considered as a key enabler for future 6G wireless systems. However, THz links are subject to high propagation losses and inter-symbol interference due to the frequency selectivity of the channel. Massive multiple-input multiple-output (MIMO) along with orthogonal frequency division multiplexing (OFDM) can be used to deal with these problems. Nevertheless, when the propagation delay across the base station (BS) antenna array exceeds the symbol period, the spatial response of the BS array varies over the OFDM subcarriers. This phenomenon, known as beam squint, renders narrowband combining approaches ineffective. Additionally, channel estimation becomes challenging in the absence of combining gain during the training stage. In this work, we address the channel estimation and hybrid combining problems in wideband THz massive MIMO with uniform planar arrays. Specifically, we first introduce a low-complexity beam squint mitigation scheme based on true-time-delay. Next, we propose a novel variant of the popular orthogonal matching pursuit (OMP) algorithm to accurately estimate the channel with low training overhead. Our channel estimation and hybrid combining schemes are analyzed both theoretically and numerically. Moreover, the proposed schemes are extended to the multi-antenna user case. Simulation results are provided showcasing the performance gains offered by our design compared to standard narrowband combining and OMP-based channel estimation.

In this paper, we present WACA, the first system to simultaneously measure all 24 Wi-Fi channels that allow channel bonding at 5 GHz with microsecond scale granularity. With WACA, we perform a first-of-its-kind measurement study in areas including urban hotspots, residential neighborhoods, universities, and even a game in Futbol Club Barcelona’s Camp Nou, a sold-out stadium with 98,000 fans and 12,000 simultaneous Wi-Fi connections. We study channel bonding in this environment, and our experimental findings reveal the underpinning factors controlling throughput gain, including channel bonding policy and spectrum occupancy statistics. We then show the significance of the gathered dataset for finding insights, which would not be possible otherwise, given that simple channel occupancy models severely underestimate the available gains. Likewise, we characterize the risks of channel bonding due to other BSS’s, including their missed transmission opportunities and potential collisions due to imperfect sensing of bonded transmissions. We explore 802.11ax which imposes constraints on bonded channels to avoid fragmentation and defines different modes that can trade implementation complexity for throughput. Lastly, we show that the stadium, while seemingly too highly occupied for channel bonding gains, has transient gaps yielding impressive gains.

We study the uplink performance of massive multiple-input multiple-output (MIMO) when users are equipped with multiple antennas. To this end, we consider a generalized channel model that accounts for line-of-sight propagation and spatially correlated multipath fading. Most importantly, we employ the Weichselberger correlation model, which has been shown to alleviate the deficiencies of the popular Kronecker model. The main contribution of this paper is a rigorous closed-form expression for the uplink spectral efficiency using maximum-ratio combining and minimum mean square error channel estimation. Our result is a non-trivial generalization of previous results on massive MIMO with spatially correlated channels, thereby enabling us to have suitable designs for future massive MIMO systems. Numerical simulations corroborate our analysis and provide useful insights on how different propagation conditions affect system performance.

In this paper, we discuss the effects on throughput and fairness of dynamic channel bonding (DCB) in spatially distributed high-density wireless local area networks (WLANs). First, we present an analytical framework based on continuous-time Markov networks (CTMNs) for depicting the behavior of different DCB policies in spatially distributed scenarios, where nodes are not required to be within the carrier sense range of each other. Then, we assess the performance of DCB in high-density IEEE 802.11ac/ax WLANs by means of simulations. We show that there may be critical interrelations among nodes in the spatial domain-even if they are located outside the carrier sense range of each other-in a chain reaction manner. Results also reveal that, while always selecting the widest available channel normally maximizes the individual long-term throughput, it often generates unfair situations where other WLANs starve. Moreover, we show that there are scenarios where DCB with stochastic channel width selection improves the latter approach both in terms of individual throughput and fairness. It follows that there is not a unique optimal DCB policy for every case. Instead, smarter bandwidth adaptation is required in the challenging scenarios of next-generation WLANs.

WiFi densification leads to the existence of multiple overlapping coverage areas, which allows user stations (STAs) to choose between different Access Points (APs). The standard WiFi association method makes the STAs select the AP with the strongest signal, which in many cases leads to underutilization of some APs while overcrowding others. To mitigate this situation, Reinforcement Learning techniques such as Multi-Armed Bandits can be used to dynamically learn the optimal mapping between APs and STAs, and so redistribute the STAs among the available APs accordingly. This is an especially challenging problem since the network response observed by a given STA depends on the behavior of the others, and so it is very difficult to predict without a global view of the network. In this paper, we focus on solving this problem in a decentralized way, where STAs independently explore the different APs inside their coverage range, and select the one that better satisfy its needs. To do it, we propose a novel approach called opportunistic $\varepsilon$-greedy with Stickiness that halts the exploration when a suitable AP is found, then, the STA remains associated to that same AP while it is satisfied, only resuming the exploration after several unsatisfactory association periods. With this approach, we reduce significantly the network response variability, improving the ability of the STAs to find a solution faster, as well as achieving a more efficient use of the network resources.

Next generation of wireless local area networks (WLANs) will operate in dense, chaotic and highly dynamic scenarios that in a significant number of cases may result in a low user experience due to uncontrolled high interference levels. Flexible network architectures, such as the software-defined networking (SDN) paradigm, will provide WLANs with new capabilities to deal with users' demands, while achieving greater levels of efficiency and flexibility in those complex scenarios. On top of SDN, the use of machine learning (ML) techniques may improve network resource usage and management by identifying feasible configurations through learning. ML techniques can drive WLANs to reach optimal working points by means of parameter adjustment, in order to cope with different network requirements and policies, as well as with the dynamic conditions. In this paper we overview the work done in SDN for WLANs, as well as the pioneering works considering ML for WLAN optimization. Finally, in order to demonstrate the potential of ML techniques in combination with SDN to improve the network operation, we evaluate different use cases for intelligent-based spatial reuse and dynamic channel bonding operation in WLANs using Multi-Armed Bandits.

A fundamental problem arising in dense wireless networks is the high co-channel interference. Interference alignment (IA) was recently proposed as an effective way to combat interference in wireless networks. The concept of IA, though, is originated by the capacity study of interference channels and as such, its performance is mainly assessed under ideal assumptions, such as instantaneous and perfect channel state information (CSI) at all nodes, and a homogeneous signal-to-noise ratio (SNR) regime, i.e., all users have the same average SNR. Consequently, the performance of IA under realistic conditions has not been completely investigated yet. In this paper, we aim at filling this gap by evaluating the performance of spatial IA in practical systems. Specifically, we derive a closed-form expression for the IA average sum-rate when CSI is acquired through training and users have heterogeneous SNR. A main insight from our analysis is that IA can indeed provide significant spectral efficiency gains over traditional approaches in a wide range of dense network scenarios. To demonstrate this, we consider the examples of linear, grid and random network topologies.

Despite being a relatively new communication technology, Low-Power Wide Area Networks (LPWANs) have shown their suitability to empower a major part of Internet of Things applications. Nonetheless, most LPWAN solutions are built on star topology (or single-hop) networks, often causing lifetime shortening in stations located far from the gateway. In this respect, recent studies show that multi-hop routing for uplink communications can reduce LPWANs' energy consumption significantly. However, it is a troublesome task to identify such energetically optimal routing through trial-and-error brute-force approaches because of time and, especially, energy consumption constraints. In this work we show the benefits of facing this exploration/exploitation problem by running centralized variations of the multi-arm bandit's e-greedy, a well-known online decision-making method that combines best known action selection and knowledge expansion. Important energy savings are achieved when proper randomness parameters are set, which are often improved when conveniently applying similarity, a concept introduced in this work that allows harnessing the gathered knowledge by sporadically selecting unexplored routing combinations akin to the best known one.

Reinforcement Learning is gaining attention by the wireless networking community due to its potential to learn good-performing configurations only from the observed results. In this work we propose a stateless variation of Q-learning, which we apply to exploit spatial reuse in a wireless network. In particular, we allow networks to modify both their transmission power and the channel used solely based on the experienced throughput. We concentrate in a completely decentralized scenario in which no information about neighbouring nodes is available to the learners. Our results show that although the algorithm is able to find the best-performing actions to enhance aggregate throughput, there is high variability in the throughput experienced by the individual networks. We identify the cause of this variability as the adversarial setting of our setup, in which the most played actions provide intermittent good/poor performance depending on the neighbouring decisions. We also evaluate the effect of the intrinsic learning parameters of the algorithm on this variability.

Dynamic Channel Bonding (DCB) allows for the dynamic selection and use of multiple contiguous basic channels in Wireless Local Area Networks (WLANs). A WLAN operating under DCB can enjoy a larger bandwidth, when available, and therefore achieve a higher throughput. However, the use of larger bandwidths also increases the contention with adjacent WLANs, which can result in longer delays in accessing the channel and consequently, a lower throughput. In this paper, a scenario consisting of multiple WLANs using DCB and operating within carrier-sensing range of one another is considered. An analytical framework for evaluating the performance of such networks is presented. The analysis is carried out using a Markov chain model that characterizes the interactions between adjacent WLANs with overlapping channels. An algorithm is proposed for systematically constructing the Markov chain corresponding to any given scenario. The analytical model is then used to highlight and explain the key properties that differentiate DCB networks of WLANs from those operating on a single shared channel. Furthermore, the analysis is applied to networks of IEEE 802.11ac WLANs operating under DCB-which do not fully comply with some of the simplifying assumptions in our analysis-to show that the analytical model can give accurate results in more realistic scenarios.

Collisions are a main cause of throughput degradation in wireless local area networks. The current contention mechanism used in the IEEE 802.11 networks is called carrier sense multiple access with collision avoidance (CSMA/CA). It uses a binary exponential backoff technique to randomize each contender attempt of transmitting, effectively reducing the collision probability. Nevertheless, CSMA/CA relies on a random backoff that while effective and fully decentralized, in principle is unable to completely eliminate collisions, therefore degrading the network throughput as more contenders attempt to share the channel. To overcome these situations, carrier sense multiple access with enhanced collision avoidance (CSMA/ECA) is able to create a collision-free schedule in a fully decentralized manner using a deterministic backoff after successful transmissions. Hysteresis and fair share are two extensions of CSMA/ECA to support a large number of contenders in a collision-free schedule. CSMA/ECA offers better throughput than CSMA/CA and short-term throughput fairness. This paper describes CSMA/ECA and its extensions. In addition, it provides the first evaluation results of CSMA/ECA with non-saturated traffic, channel errors, and its performance when coexisting with CSMA/CA nodes. Furthermore, it describes the effects of imperfect clocks over CSMA/ECA and presents a mechanism to leverage the impact of channel errors and the addition/withdrawal of nodes over collision-free schedules. Finally, the experimental results on throughput and lost frames from a CSMA/ECA implementation using commercial hardware and open-source firmware are presented.

Collisions are a main cause of throughput degradation in Wireless LANs. The current contention mechanism for these networks is based on a random backoff strategy to avoid collisions with other transmitters. Even though it can reduce the probability of collisions, the random backoff prevents users from achieving Collision-Free schedules, where the channel would be used more efficiently. Modifying the contention mechanism by waiting for a deterministic timer after successful transmissions, users would be able to construct a Collision-Free schedule among successful contenders. This work shows the experimental results of a Collision-Free MAC (CF-MAC) protocol for WLANs using commercial hardware and open firmware for wireless network cards which is able to support many users. Testbed results show that the proposed CF-MAC protocol leads to a better distribution of the available bandwidth among users, higher throughput and lower losses than the unmodified WLANs clients using a legacy firmware.

Wireless Sensor Networks (WSNs) are composed of nodes that gather metrics such as temperature, pollution or pressure from events generated by external entities. Localization in WSNs is paramount, given that the collected metrics must be related to the place of occurrence. This work presents an alternative way towards localization in randomly deployed WSNs based on the combination of individual position estimation protocols (composability). Our solution provides a flexible approach towards the localization problem in WSNs, which by means of composability it is able to locate more nodes than exclusively using a single localization protocol, while maintaining the same low levels of battery consumption.

The two main drawbacks of receiver-initiated Medium Access Control (MAC) protocols for Wireless Sensor Networks (WSNs) are that i) they require all nodes to send a beacon each time they wake up, and that ii) broadcast traffic is not efficiently supported. In this work, we propose addressing these limitations by extending receiver-initiated MAC protocols with scheduling, i.e, coordinating sensor nodes to wake up at nearly the same instant. Following this approach, only one sensor node in the neighborhood sends a beacon per wake-up period and, as all nodes are awake at the same time, broadcast transmissions are naturally supported. A distributed learning technique is used to establish the order of beacon transmissions. We present the protocol description and the time to convergence when a fully connected network is considered.

The traditional IEEE 802.11 DCF allows only one node to access the channel each time. In order to take the benefit of multiple simultaneous uplink transmissions when the AP is equipped with multiple antennas, a new MAC protocol called DCF/USDMA is presented in this paper. DCF/USDMA extends the IEEE 802.11 Distributed Coordination Function (DCF) by introducing a second contention round, which is used to accommodate the multiple simultaneous transmissions from multiple stations. Results show that the DCF/USDMA protocol is able to achieve a significant performance gain compared to that of the conventional DCF, the analysis of which also provides some insights about how the different parameters that control the DCF/USDMA operation can be optimized.

Carrier Sense Multiple Access with Enhanced Collision Avoidance (CSMA/ECA) is a recently proposed modification to the well-known CSMA/CA protocol. By using a deterministic backoff after successful transmissions, the number of collisions decreases. This article presents a model that captures the behaviour of CSMA/ECA in both saturated and non-saturated scenarios. The results, which are validated by simulations, show that CSMA/ECA effectively prevents collisions and, therefore, it can deliver a higher throughput than CSMA/CA.

Multi-user MIMO allows the simultaneous transmission of several link-layer frames directed to different users by exploiting the channel's spatial streams, increasing proportionally the effective channel capacity. Nevertheless, the system performance can be further increased if several frames directed to the same user are combined together on a temporal scale (i.e. packet aggregation), taking benefit from both space and time dimensions. In this paper, a novel finitebuffer space-time general-distributed batch-service queueing model for such a system is presented. Results show the flexibility and accuracy of our queuing model, providing also a first insight on the relation between the space and temporal aggregation parameters and how they can be adjusted to maximise the system performance.

CSMA with Enhanced Collision Avoidance (CSMA/ECA) uses a deterministic backoff after successful transmissions to significantly reduce the number of collisions. This paper assesses by means of simulations the throughput and conditional collision probability obtained from a single-hop ad-hoc network using CSMA/ECA. A comparison with the legacy CSMA/CA reveals that the proposed protocol outperforms the legacy one in all considered scenarios. Specifically, it is shown that CSMA/ECA presents advantages for both rigid and elastic flows.

A novel flow admission control mechanism for infrastructure IEEE 802.11e EDCA-based WLANs is presented. The proposed admission control works jointly with a tuning algorithm which decides the most suitable configuration of the MAC parameters each time a new flow arrives or leaves the system. It is designed to work in heterogeneous scenarios with both elastic and real-time flows, so it aims to: i) guarantee the QoS requirements for real-time flows (like VoIP) and ii) maximize the best-effort throughput (such as TCP web browsing or P2P transfers). Results, compared with the use of the DCF (distributed coordination function) and EDCA (enhanced distributed channel access) with static parameters, show a clear improvement on the overall HotSpot performance. Our mechanism provides better QoS, uplink versus downlink fairness and a more efficient use of the transmission resources.

GSM/GPRS networks have been designed to carry both voice and data traffic. Our aims are to study the behaviour of the GPRS mechanisms (RLC/MAC layer and radio resource scheduler) when the application layer carries packetized voice, and determine if the quality of service provided by the network is suitable for the VoIP service. The paper includes a discussion about the voice source model, an analysis of the effects in capacity of a GPRS carrier when feed with VoIP packets, measurements of statistical parameters of the voice traffic stream and a discussion of the influence in the quality of the service.