The radio spectrum is characterized by a noticeable variability, which impairs performance and determinism of every wireless communication technology. To counteract this aspect, mechanisms like Minstrel are customarily employed in real Wi-Fi devices, and the adoption of machine learning for optimization is envisaged in next-generation Wi-Fi 8. All these approaches require communication quality to be monitored at runtime. In this paper, the effectiveness of simple techniques based on moving averages to estimate wireless link quality is analyzed, to assess their advantages and weaknesses. Results can be used, e.g., as a baseline when studying how artificial intelligence can be employed to mitigate unpredictability of wireless networks by providing reliable estimates about current spectrum conditions.

Besides extremely high throughput, Wi-Fi 7 is also aimed at providing users a more deterministic behavior, characterized by shorter average latency and smaller jitters. A key mechanism to achieve this is multi-link operation, which brings simultaneous multi-band communication to client stations as well. In this paper, traffic steering policies are briefly reviewed and grouped into general classes, each one with its advantages and limitations. A basic mechanism for supporting dynamic steering is then described, which is simple enough to allow implementation in real Wi-Fi chipsets but highly flexible at the same time. Its operation can be driven by the host on a per-packet basis, and this permits to optimize spectrum usage depending on the requirements of applications and the traffic pattern they generate.

Executable QR codes, also known as eQR codes or just sQRy, are a special kind of QR codes that embed programs conceived to run on mobile devices like smartphones. Since the program is directly encoded in binary form within the QR code, it can be executed even when the reading device is not provided with Internet access. The applications of this technology are manifold, and range from smart user guides to advisory systems. The first programming language made available for eQR is QRtree, which enables the implementation of decision trees aimed, for example, at guiding the user in operating/maintaining a complex machinery or for reaching a specific location. In this work, an additional language is proposed, we term QRind, which was specifically devised for Industry. It permits to integrate distinct computational blocks into the QR code, e.g., machine learning models to enable predictive maintenance and algorithms to ease machinery usage. QRind permits the Industry 4.0/5.0 paradigms to be implemented, in part, also in those cases where Internet is unavailable.

Multi-Link Operation (MLO) in Wi-Fi 7 is expected to tangibly boost throughput while lowering transmission latency at the same time. This is very relevant in industrial scenarios and makes MLO suitable, e.g., to support seamless device mobility. Benefits depend on the ability of multi-link devices to select at run-time the best link, among the available ones, in order to maximize both communication performance and reliability.In this paper an experimental platform is proposed, with the aim of leveraging commercial hardware and open source software, and easing prototyping and evaluation of MLO techniques. The platform has been employed to analyze the transmission quality of two pairs of non-overlapping channels, and in particular to assess whether or not adequate diversity is provided, so that those channels can be exploited to improve reliability. Results point out that correlation between different links is, in most cases, limited, which makes MLO a valuable approach.

The next generation of Wi-Fi is meant to achieve ultra-high reliability for wireless communication. Several approaches are available to this extent, some of which are being considered for inclusion in standards specifications, including coordination of access points to reduce interference.In this paper, we propose a centralized architecture based on digital twins, called WiTwin, with the aim of supporting wireless stations in selecting the optimal association according to a set of parameters. Unlike prior works, we assume that Wi-Fi 7 features like multi-link operation (MLO) are available. Moreover, one of the main goals of this architecture is to preserve communication quality in the presence of mobility, by helping stations to perform reassociation at the right time and in the best way.

QR codes are increasingly used in a plurality of scenarios, and research activities are being successfully carried out to improve this technology and widen its contexts of applicability. After an extensive survey of the state-of-the-art on the subject, this work presents the new, promising possibility to embed a programming language in a QR code. This new kind of executable QR codes, we named eQR codes, enable interaction with end users even in the absence of an Internet connection, and provide a sort of IoT paradigm where intelligence is embedded in the object tag in the form of a program. Among all the possible languages that can be embedded, this work focuses on a powerful but compact (in terms of QR code storage occupation) dialect, termed QRtree, which is aimed at implementing decision trees. The eQR code technology makes a new class of applications possible, e.g., providing hints for navigation or instructions for using rescue devices in places with no network coverage like mountains and caves. Smart interactive user manuals are enabled as well. Besides defining the QRtree language and eQR code structure, this paper describes all the steps needed to generate eQR codes and to manage their execution in end-user devices. A simple yet realistic example and the related code are also presented, to practically show how this technology can be used to solve real-world problems. For the example, the QRtree version of the code takes 234B, less than one-half the size of an equivalent program in Python bytecode (634B).