Applications with deterministic quality of service (QoS) requirements are becoming widespread, driving the evolution of wireless networks to meet strict performance demands. Wi-Fi 7, the latest generation of IEEE 802.11 standard, introduces Restricted Target Wake Time (R-TWT). It serves latency-sensitive traffic by providing contention-free channel access for certain devices and reducing their energy consumption. This paper evaluates the performance of R-TWT across diverse service types and network sizes in terms of worst-case latency, energy efficiency, collision rate, and throughput. The results, generated using the ns-3 simulator, show that R-TWT achieves bounded latency for sensitive traffic types, such as Internet of Things (IoT) and real-time (RT) applications. Moreover, R-TWT outperforms legacy mechanisms, i.e., Power Saving Mode (PSM) and Distributed Coordination Function (DCF), by achieving higher energy efficiency and a lower collision rate. Furthermore, R-TWT maintains stable and scalable performance as network size increases. This makes it a robust solution for latency-sensitive and energy-efficient wireless applications.

The next generation of Wi-Fi, i.e., the IEEE 802.11bn (aka Wi-Fi 8), is not only expected to increase its performance and provide extended capabilities but also aims to offer a reliable service. Given that one of the main sources of unreliability in IEEE 802.11 stems from the current distributed channel access, which is based on Listen-BeforeTalk (LBT), the development of novel contention schemes gains importance for Wi-Fi 8 and beyond. In this paper, we propose a new channel contention mechanism, “It's Your Turn” (IYT), that extends the existing Distributed Coordination Function (DCF) and aims at improving the reliability of distributed LBT by providing ordered device transmissions thanks to neighboring activity awareness. Using simulation results, we show that our mechanism strives to provide reliable performance by controlling the channel access delay. We prove the versatility of IYT against different topologies and densities, and when coexisting with legacy 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).

The increasing cloudification and softwarization of networks foster the interplay among multiple independently managed deployments. An appealing reason for such an interplay lies in distributed Machine Learning (ML), which allows the creation of robust ML models by leveraging collective intelligence and computational power. In this paper, we study the application of the two cornerstones of distributed learning, namely Federated Learning (FL) and Knowledge Distillation (KD), on the Wi-Fi Access Point (AP) load prediction use case. The analysis conducted in this paper is done on a dataset that contains real measurements from a large Wi-Fi campus network, which we use to train the ML model under study based on different strategies. Performance evaluation includes relevant aspects for the suitability of distributed learning operation in real use cases, including the predictive performance, the associated communication overheads, or the energy consumption. In particular, we prove that distributed learning can improve the predictive accuracy centralized ML solutions by up to 93% while reducing the communication overheads and the energy cost by 80%.

In view of the need to find novel means to utilize the unlicensed spectrum to meet the rising latency and reliability requirements of new applications, we propose a novel mechanism that allows devices to transmit anytime that a packet has to be delivered. The proposed mechanism, Contention-free with Power Adaptation (ConPA), aims to bypass the contention periods of current Listen-Before-Talk (LBT) approaches, which are the main source of unreliability in unlicensed technologies like Wi-Fi. To assess the feasibility of ConPA, we provide an analytical method based on Markov chains, which allows deriving relevant performance metrics, including throughput, airtime, and quality of transmissions. Using such a model, we study the performance of ConPA in various scenarios, and compare it to baseline channel access approaches like the Distributed Coordination Function (DCF) and the IEEE 802.11ax Overlapping Basic Service Set (OBSS) Packet Detect (PD)-based Spatial Reuse (SR). Our results prove the effectiveness of ConPA in reusing the space to offer substantial throughput gains with respect to the baselines (up to 76% improvement).

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.

In this article, we evaluate the performance of the parameterized spatial reuse (PSR) framework of IEEE 802.11ax, mainly focusing on its impact on transmission latency. Based on detailed standard-compliant system-level simulations, we provide a realistic analysis of the effects of PSR considering different scenario densities, traffic loads, and access points (APs) antenna capabilities to quantify its performance gains under various scenarios. Our results show that, in medium-density scenarios, PSR can offer up to a 3.8× reduction in the 5% worst-case latencies for delay-sensitive stations with respect to an 802.11ax system without PSR. Moreover, our study demonstrates that, for low-latency communications, providing the network with PSR capabilities may be an appealing alternative to the deployment of more costly multi-antenna APs.

Wi-Fi technology is continuously evolving to keep the pace with the fast-increasing demand for new digital services and applications. In particular, Wi-Fi 6 is becoming widely available in residential and enterprise scenarios supporting up to eight spatial streams. At the same time, large antenna arrays have already shown their ability and benefits when serving a large number of devices simultaneously. Since enterprise owners are already upgrading their indoor private networks with the next generation of Wi-Fi products, it becomes crucial to understand the capacity limits and the benefits associated to different deployment strategies and large antenna array configurations. The scope of this paper is to provide concrete insights to internet service providers and enterprise owners on how to upgrade, deploy, and efficiently operate their networks with next-generation Wi-Fi access points, showing their potential performance improvements and providing a set of clear guidelines.

In this paper, we investigate the use of highly directional, hybrid antenna arrays in residential Wi-Fi mesh deployments to further improve their performance in challenging conditions where high wall losses are encountered. We also formulate a metric to quantify the quality of the Wi-Fi coverage, and present a deployment procedure to automatically select extender AP locations to maximise such metric. Using the proposed deployment procedure, the performance of highly directional, hybrid antenna arrays in residential Wi-Fi mesh deployments is evaluated through simulations. Compared with the benchmark of omni-directional antennas, we show that using the proposed array increases the areas achieving peak throughput by more than 3 times.

Indoor areas, such as offices and shopping malls, are a natural environment for initial millimeter-wave (mmWave) deployments. Although we already have the technology that enables us to realize indoor mmWave deployments, there are many remaining challenges associated with system-level design and planning for such. The objective of this article is to bring together multiple strands of research to provide a comprehensive and integrated framework for the design and performance evaluation of indoor mmWave systems. This article introduces the framework with a status update on mmWave technology, including ongoing fifth generation (5G) wireless standardization efforts and then moves on to experimentally validated channel models that inform performance evaluation and deployment planning. Together these yield insights on indoor mmWave deployment strategies and system configurations, from feasible deployment densities to beam management strategies and necessary capacity extensions.

A key aspect of the fifth-generation wireless communication network will be the integration of different services and technologies to provide seamless connectivity. In this paper, we consider using massive multiple-input multiple-output (mMIMO) to provide backhaul links to a dense deployment of self-backhauling (s-BH) small cells (SCs) that provide cellular access within the same spectrum resources of the backhaul. Through a comprehensive system-level simulation study, we evaluate the interplay between access and backhaul and the resulting end-to-end user rates. Moreover, we analyze the impact of different SCs deployment strategies, while varying the time resource allocation between radio access and backhaul links. We finally compare the above mMIMO-based s-BH approach to a mMIMO direct access (DA) architecture accounting for the effects of pilot reuse schemes, together with their associated overhead and contamination mitigation effects. The results show that dense SCs deployments supported by mMIMO s-BH provide significant rate improvements for cell-edge users (UEs) in ultra-dense deployments with respect to mMIMO DA, while the latter outperforms mMIMO s-BH from the median UEs' standpoint.

Reliable command and control channels to unmanned aerial vehicles (UAVs) are needed to allow beyond visual line of sight (LoS) operations. Cellular networks, with their almost ubiquitous coverage, are an obvious candidate to provide such conditions. However, up to which extent the current networks designed for ground users can support UAV communications is an open question. In this paper, we provide a comprehensive theoretical analysis, using stochastic geometry, of the performance that operators could expect from traditional cellular networks with omnidirectional antennas when supporting UAV downlink command and control channels. Our study employs the latest UAV height-dependent path loss model defined by the 3GPP, with LoS and non-LoS transmissions and a probabilistic model to switch between them. We derive analytical expressions for the coverage probability and area spectral efficiency, while accounting for base stations with idle mode capabilities, a practical finite UAV density, and different UAV heights. Results show that networks based on base stations with omnidirectional coverage can support low-height UAVs but will struggle with high-height ones. Network densification helps to provide a better performance.

Providing consistently high wireless capacity is becoming increasingly important to support the applications required by future digital enterprises. In this paper, we propose Eigen-direction-aware ZF (EDA-ZF) with partial coordination among base stations (BSs) and distributed interference suppression as a practical approach to achieve this objective. We compare our solution with Zero Forcing (ZF), entailing neither BS coordination or inter-cell interference mitigation, and Network MIMO (NeMIMO), where full BS coordination enables centralized inter-cell interference management. We also evaluate the performance of said schemes for three sub-6 GHz deployments with varying BS densities — sparse, intermediate, and dense — all with fixed total number of antennas and radiated power. Extensive simulations show that: (i) indoor massive MIMO implementing the proposed EDA-ZF provides uniformly good rates for all users; (ii) indoor network densification is detrimental unless full coordination is implemented; (iii) deploying NeMIMO pays off under strong outdoor interference, especially for cell-edge users.

To guarantee the success of massive multiple-input multiple-output (MIMO), one of the main challenges to solve is the efficient management of pilot contamination. Allocation of fully orthogonal pilot sequences across the network would provide a solution to the problem, but the associated overhead would make this approach infeasible in practical systems. Ongoing fifth-generation (5G) standardisation activities are debating the amount of resources to be dedicated to the transmission of pilot sequences, focussing on uplink sounding reference signals (UL SRSs) design. In this paper, we evaluate the performance of various UL SRS allocation strategies in practical deployments, shedding light on their strengths and weaknesses. Furthermore, we introduce a novel UL SRS fractional reuse (FR) scheme, denoted neighbour-aware (FR-NA). The proposed FR-NA generalizes the fixed reuse paradigm, and entails a trade-off between i) aggressively sharing some UL SRS resources, and ii) protecting other UL SRS resources with the aim of relieving neighbouring BSs from pilot contamination. Said features result in a cell throughput improvement over both fixed reuse and state-of-the-art FR based on a cell-centric perspective.

We consider cellular base stations (BSs) equipped with a large number of antennas and operating in the unlicensed band. We denote such system as massive MIMO unlicensed (mMIMO-U). We design the key procedures required to guarantee coexistence between a cellular BS and nearby Wi-Fi devices. These include: neighboring Wi-Fi channel covariance estimation, allocation of spatial degrees of freedom for interference suppression, and enhanced channel sensing and data transmission phases. We evaluate the performance of the so-designed mMIMO-U, showing that it allows simultaneous cellular and Wi-Fi transmissions by keeping their mutual interference below the regulatory threshold. The same is not true for conventional listen-before-talk (LBT) operations. As a result, mMIMO-U boosts the aggregate cellular-plus-Wi-Fi data rate in the unlicensed band with respect to conventional LBT, exhibiting increasing gains as the number of BS antennas grows.

Massive multiple-input multiple-output (massive MIMO) system or so-called large scale antenna system (LSAS) has been identified as one of the promising candidates for 5G wireless communications systems. In general, a massive MIMO architecture can be split into two main parts, the massive MIMO baseband digital platform and the massive MIMO radio platform. Although several studies have been already performed on the achievable theoretical results of the technology and associated impairments, fewer has been done so far in the area of real implementation complexity analysis, reduced cost research prototype, hardware and software required functional blocks and interactions. The object of this paper is to introduce a low-cost scalable massive MIMO research platform with flexible co-operated hardware (HW) and software (SW) baseband processing. The proposed solution plays an important role in exploring the optimal configuration of a massive MIMO baseband digital system, processing algorithm complexity reduction, procedure and protocols definition towards a high performance software-defined massive MIMO system. The experimental HW and SW results of the key processing units preliminarily verify the feasibility and achievable performance of the proposed flexible and scalable massive MIMO research platform, which was built with a co-operated general purpose processor (GPP) workstation and a middle-range field programmable gate array (FPGA) evaluation board.

We propose to operate massive multiple-input multiple-output (MIMO) cellular base stations (BSs) in unlicensed bands. We denote such systems as massive MIMO unlicensed (mMIMO-U) ones. We design the key procedures required at a cellular BS to guarantee coexistence with nearby Wi-Fi devices operating in the same band. In particular, spatial reuse is enhanced by actively suppressing interference toward neighboring Wi-Fi devices. Wi-Fi interference rejection is also performed during an enhanced listen-before-talk phase. These operations enable Wi-Fi devices to access the channel as though no cellular BSs were transmitting, and vice versa. Under concurrent Wi-Fi and BS transmissions, the downlink rates attainable by cellular user equipment (UEs) are degraded by the Wi-Fi-generated interference. To mitigate this effect, we select a suitable set of UEs to be served in the unlicensed band accounting for a measure of the Wi-Fi/UE proximity. Our results show that the so-designed mMIMO-U allows simultaneous cellular and Wi-Fi transmissions by keeping their mutual interference below the regulatory threshold. Compared with a system without interference suppression, Wi-Fi devices enjoy a median interference power reduction of between 3 dB with 16 antennas and 18 dB with 128 antennas. With mMIMO-U, cellular BSs can also achieve large data rates without significantly degrading the performance of Wi-Fi networks deployed within their coverage area.

Interference mitigation and adaptive multi-user resource allocation are among the most promising technological breakthroughs that should improve capacity of future broadband wireless communications. In a multi-cell scenario, where co-channel interference is the performance limiting factor, discrete-rate resource allocation algorithms, selecting those channels with best Signal-to-Interference and Noise-Ratio (SINR), can reduce the transmission power in each base station, acting indirectly on the co-channel interference levels. In this paper we investigate multi-cell systems in which power adaptation acts as a positive factor for the interference reduction. We are interested here in the convergence properties of the dynamic model of the system and in the role of the number and position of SINR thresholds of the discrete-rate profiles. We find that, in multi-cell scenarios, the application of power reduction makes the spectral efficiency of the system relatively insensitive to the number of discrete-rate profiles, once fixed the minimum and maximum SINR thresholds.

Adaptive multi-user resource allocation is one of the key features towards high speed wireless network based on Orthogonal Frequency Division Multiplexing Access (OFDMA). According to IEEE 802.16e (WiMAX) standard radio, resource allocation problem has to be performed on a two-dimensional space (frequency and time) with the constraint that each transmitted burst should occupy a contiguous portion of the frame. The paper introduces two different strategies and it investigates the advantages, drawbacks and challenges of the radio resource allocation procedure in two dimensions.

Adaptive multi-user resource allocation is one of the most promising technological breakthroughs that could improve performance of future broadband wireless communications. In a multi-cell scenario, where co-channel interference is the performance limiting factor, resource allocation algorithms select those channels with best Signal-to Interference and Noise-Ratio (SINR) and adapt transmission power, acting indirectly on the interference levels. The paper introduces an analytical procedure for evaluating how the distribution of co-channel interference is modified by different resource allocation algorithms. This procedure can be used for deriving a model of interference or for providing a deeper insight on the performance limits of the system.

IEEE 802.16 (WiMAX) is an emerging technology for medium-range wireless communications. Among the technological breakthroughs that could improve its performance, adaptive multi-user resource allocation is one of the most promising. The paper introduces a novel algorithm and provides an insight into some aspects and design issues related to this application. Numerical results rely on the channel models adopted by IEEE 802.16 and highlight the advantages and drawbacks of the selected strategies.