Intelligent reflective surface (IRS) technologies help mitigate undesirable effects in wireless links by steering the communication signal between transmitters and receivers. IRS elements are configured to adjust the phase of the reflected signal for a user’s location and enhance the perceived signal-to-noise ratio (SNR). In this way, an IRS improves the communication link but inevitably introduces more communication overhead. This occurs especially in mobile scenarios, where the user’s position must be frequently estimated to re-adjust the IRS elements periodically. Such an operation requires balancing the amount of training versus the data time slots to optimize the communication performance in the link. Aiming to study this balance with the age of information (AoI) framework, we address the question of how often an IRS needs to be updated with the lowest possible overhead and the maximum of freshness of information. We derive the corresponding analytical solution for a mobile scenario, where the transmitter is static and the mobile user (MU) follows a random waypoint mobility model. We provide a closed-form expression for the average peak age of information (PAoI), as a metric to evaluate the impact of the IRS update frequency. As for the performance evaluation, we consider a realistic scenario following the IEEE 802.11ad standard, targeting the mmWave band. Our results reveal that the minimum achievable average PAoI is in the microsecond range and the optimal IRS update period is in the seconds range, causing 9% overhead in the link when the MU moves at a velocity of 1m/s.

Most works on intelligent reconfigurable surface (IRS)-assisted networks consider link-level simulations and do not address the upper protocol layers. This limitation becomes particularly relevant in practical systems like 802.11 Wi-Fi, where channel access is based on listen-before-talk (LBT) scheme, making conventional IRS scheduling strategies (time-division or centralized coordination) difficult to apply. Given these reasons, we shift the focus to random channel access based on carrier sense multiple access with collision avoidance (CSMA/CA) to explore how an IRS can be beneficial in such scenarios. We first discover that improving the SNR of links from stations (STAs) to an access point (AP) introduces the potential risk of hidden terminals among the STAs in the uplink. To analyze this, we introduce ns3IRS, a framework that integrates a model of an IRS into the ns-3 network simulator, which allows us to run the full WiFi stack within an IRS-assisted wireless network. We propose two solutions to mitigate the hidden terminal problem caused by the IRS also by assuring mutual carrier sensing: (i) splitting a single centralized IRS, or (ii) using additional small IRSs nearby the STAs – to create direct links among them, with the purpose of enabling mutual carrier sensing. Results show that these two solutions can improve the throughput compared to the traditional approach where virtual carrier sensing, i.e., CSMA/CA with Request-to-Send/Clear-to-Send (RTS/CTS), is used. For instance, for a system with four users, the proposed approaches improve the throughput from 25Mbit/s to around 35Mbit/s compared to the baseline scenario with RTS/CTS. Additionally, latency and jitter are decreased. However, as the number of users increases, achieving performance gains requires a larger IRS, since the gain scales with the number of reflecting elements, especially for the centralized IRS. In scenarios where scaling the IRS is impractical, CSMA/CA with RTS/CTS may become a more effective alternative.

Channel state information (CSI) is widely used for joint communication and sensing in sub-6 GHz wireless networks, but its application at mmWave frequencies remains under-explored. This work applies a quantized amplitude-based CSI similarity metric to data from a 28 GHz indoor testbed, showing the feasibility of CSI-based ambient sensing in next-generation wireless networks.

Millimeter wave (mmWave) spectrum is associated with abundance of available spectrum and excellent spectrum reuse, but also has the significant downside of decreased resilience. Communication can be disrupted when the line of sight (LOS) path is blocked, or the link quality may degrade due to obstacles. These issues are exacerbated by mobility. One possible countermeasure against such signal shadowing and blockage is the use of intelligent reconfigurable surfaces (IRSs). However, while IRSs have the advantage to form a beam directly targeting the user, user-tracking and the need to orchestrate the IRS are very challenging. A practical solution towards improving the resilience is the use of non-reconfigurable reflecting surfaces (NRRSs), which enable communication through reflections by creating additional signal paths via a pre-configured reflection pattern. With sufficient number of reflections through NRRSs, the probability of communication outage is significantly reduced. The additional signal paths in NRRS-assisted networks can be very useful in scenarios characterized by repetitive mobility patters, especially since the cost and complexity are heavily reduced compared to IRS. While the benefits of IRS deployment have been extensively studied, most analyses are limited to the simulation domain. In contrast, this paper provides practical insights derived from measurements conducted on a mmWave band testbed. Results reveal that even with a few NRRSs, the resilience of a mmWave communication link could be dramatically improved resulting in close-to-zero packet loss. However, the channel becomes highly frequency-selective, which makes the use of advanced physical layers like IEEE 802.11be with adaptive modulation & coding per resource unit (RU) a necessity.

After a rapid deployment worldwide over the past few years, 5G is expected to have reached a mature deployment stage to provide measurable improvement of network performance and user experience over its predecessors. In this study, we aim to assess 5G deployment maturity via three conditions: (1) Does 5G performance remain stable over a long time span (1 year)? (2) Does 5G provide better performance than its predecessor Long-Term Evolution (LTE)? (3) Does the technology offer similar performance across diverse geographic areas and cellular operators? We answer this important question by conducting two year-long measurement campaigns of 5G uplink performance leveraging a custom Android app: one crowd-sourced, cross-sectional campaign spanning 8 major cities in 7 countries and two different continents (Europe and North America), and one controlled campaign focusing on mmWave deployment at a fixed location in the downtown area of Boston, MA. Our datasets show that 5G deployment in major cities appears to have matured, with no major performance improvements observed over a one-year period, but 5G does not provide consistent, superior measurable performance over LTE, especially in terms of latency, and further there exists clear uneven 5G performance across the 8 cities. Our study suggests that, while 5G deployment appears to have stagnated, it is short of delivering its promised performance and user experience gain over its predecessor.