Reliable wireless communications are crucial for ensuring workers’ safety in underground tunnels and mines. Visible light communications (VLC) have been proposed as auxiliary systems for short-range wireless communications in underground environments due to their seamless availability, immunity to electromagnetic interference, and illumination capabilities. Although multiple VLC channel models have been proposed for underground mines (UM) so far, none of these models have considered the wavelength dependence of the underground mining VLC channel (UM-VLC). In this paper, we propose a single-input, single-output (SISO), wavelength-dependent UM-VLC channel model considering the wavelength dependence of the light source, reflections, light scattering, and the attenuation due to dust and the photodetector. Since wavelength dependence allows us to model VLC systems more accurately with color-based modulation, such as color-shift keying (CSK), we also propose a wavelength-dependent CSK-based UM-VLC channel model. We define a simulation scenario in an underground mine roadway and calculate the received power, channel impulse response (CIR), signal-to-noise ratio (SNR), signal-to-interference ratio (SIR), root mean square (RMS) delay, and bit error rate (BER). For comparison, we also calculate these parameters for a monochromatic state-of-the-art UM-VLC channel and use it as a reference channel. We find that the inclusion of wavelength-dependency in CSK-based UM-VLC systems plays a significant role in their performance, introducing color distortion that the color calibration algorithm defined in the IEEE 802.15.7 VLC standard finds harder to revert than the linear color distortion induced by monochromatic CSK channels.

Today, we live in a connected world, in our office, on the streets, and in our homes; we access information and services of all kinds at any time. Some engineers design office networks and some design the mobile networks we use on the streets, but who designs our home networks? Is the network capable of offering the level of service that users require? The services that grew the most during the pandemic world were remote conferencing, VPN, video streaming, gaming and social sharing, all intensive services, so it is important to analyze what happens in modern residential networks and in particular, how IEEE 802.11 can help resolve performance issues. In this paper, we evaluate the efficiency of multi-user downlink transmissions in a residential scenario. We compare IEEE 802.11ac with IEEE 802.11ax, to see how Wi-Fi 5 performs and how the new Wi-Fi 6 enhancements better cope with this intensive use scenario.

The rapid adoption of QUIC as a transport protocol has transformed content delivery by reducing latency, enhancing congestion control (CC), and enabling more efficient multiplexing. With the advent of 5G networks, which support ultra-low latency and high bandwidth, streaming high-resolution video at 4K and beyond has become increasingly viable. However, optimizing Quality of Experience (QoE) in mobile networks remains challenging due to the complex interactions among Adaptive Bit Rate (ABR) schemes at the application layer, CC algorithms at the transport layer, and Radio Link Control (RLC) queuing at the link layer in the 5G network. While prior studies have largely examined these components in isolation, this work presents a comprehensive analysis of the impact of modern active queue management (AQM) strategies, such as RED and L4S, on video streaming over diverse QUIC implementations—focusing particularly on their interaction with the RLC buffer in 5G environments and the interplay between CC algorithms and ABR schemes. Our findings demonstrate that the effectiveness of AQM strategies in improving video streaming QoE is intrinsically linked to their dynamic interaction with QUIC implementations, CC algorithms and ABR schemes—highlighting that isolated optimizations are insufficient. This intricate interdependence necessitates holistic, cross-layer adaptive mechanisms capable of real-time coordination between network, transport and application layers, which are crucial for leveraging the capabilities of 5G networks to deliver robust, adaptive, and high-quality video.

Real life data from three Mobile Operators has been used to successfully test a New Model of Quality of Experience (QoE) in Broadband Services. The Platform utilized is based on Open Source Tools and it generates Key Quality Indicators (KQI) simulating the final user's perception of the service. The detailed characterization of: a) the consolidated usage profile, b) the transport and application protocols and c) the final service, are the main components of the model that complement the typical network Key Performance Indicators (KPIs). This work also studies how different connection-oriented transport protocols affect the QoE. This provides the operator with an objective comparison of the impact the different protocols have on the QoE metric. The final results are representative KQIs that allow indirect measurements of real life services and service behavior prediction under simulated scenarios. The set of KQIs varies depending upon the market segments and the specific services that each Mobile Operator offers to its customers. From the Regulator's standpoint, when considering several Operators with the same service, this methodology allows the benchmark of QoE.

The widespread adoption of cellular networks has played an important role in the integration of road safety applications, capitalizing on the ubiquitous use of this technology by road users and its extensive market penetration. This paper presents the formulation of an analytical model to assess the awareness of vulnerable road users (VRU) defined as VRU Awareness Probability (VAP) achieved by vehicles communicating via 5G New Radio (NR) cellular vehicle-to-everything C-V2X networks at urban intersections. The main assumption in our model is that all VRU are connected to a 5G network. Our analytical model is designed to represent the dynamics of the 5G NR network operating in communication mode 2 in an urban intersection setting; we consider the influencing factors of signal propagation, such as obstacles created by buildings and realistic mobility patterns for vehicles and VRU based on SUMO traces. Our research shows that the proposed model exhibits high accuracy in intersection scenarios without buildings and maintains this efficiency in partially and highly obstructed scenarios, showing a Root Mean Square Error (RMSE) of 0.0265 and 0.0309, respectively; using the fitted model as a baseline in the non-obstructed scenario. The efficiency of this model can facilitate the study of the impact of the implementation and development of road safety applications on the safety of VRU. This VRU-centered approach allows for evaluating VRU awareness in different traffic density contexts, communication network conditions, and architectures where safety applications can be deployed.