BS-Breath: Respiration Sensing with Cell-free Massive MIMO

This paper demonstrates the feasibility of respiration pattern estimation utilizing a communication-centric cellfree massive MIMO OFDM Base Station (BS). The sensing target is typically positioned near the User Equipment (UE), which transmits uplink pilots to the BS. Our results demonstrate the potential of massive MIMO systems for accurate and reliable vital sign estimation. Initially, we adopt a single antenna sensing solution that combines multiple subcarriers and a breathing projection to align the 2D complex breathing pattern to a single displacement dimension. Then, Weighted Antenna Combining (WAC) aggregates the 1D breathing signals from multiple antennas. The results demonstrate that the combination of space-frequency resources specifically in terms of subcarriers and antennas yields higher accuracy than using only a single antenna or subcarrier. Our results significantly improved respiration estimation accuracy by using multiple subcarriers and antennas. With WAC, we achieved an average correlation of 0.8 with ground truth data, compared to 0.6 for single antenna or subcarrier methods, a 0.2 correlation increase. Moreover, the system produced perfect breathing rate estimates. These findings suggest that the limited bandwidth (18 MHz in the testbed) can be effectively compensated by utilizing spatial resources, such as distributed antennas.

Beamforming with Oversampled Time-Modulated Arrays

The time-modulated array (TMA) is a simple array architecture in which each antenna is connected via a multi-throw switch. The switch acts as a modulator switching state faster than the symbol rate. The phase shifting and beamforming is achieved by a cyclic shift of the periodical modulating signal across antennas. In this paper, the TMA mode of operation is proposed to improve the resolution of a conventional phase shifter. The TMAs are analyzed under constrained switching frequency being a small multiple of the symbol rate. The presented generic signal model gives insight into the magnitude, phase and spacing of the harmonic components generated by the quantized modulating sequence. It is shown that the effective phase-shifting resolution can be improved multiplicatively by the oversampling factor ($O$) at the cost of introducing harmonics. Finally, the array tapering with an oversampled modulating signal is proposed. The oversampling provides $O+1$ uniformly distributed tapering amplitudes.

Frequency Diverse Array OFDM System for Joint Communication and Sensing

The frequency-diverse array (FDA) offers a time-varying beamforming capability without the use of phase shifters. The autoscanning property is achieved by applying a frequency offset between the antennas. This paper analyzes the performance of an FDA joint communication and sensing system with the orthogonal frequency-division multiplexing (OFDM) modulation. The performance of the system is evaluated against the scanning frequency, number of antennas and number of subcarriers. The utilized metrics; integrated sidelobe level (ISL) and error vector magnitude (EVM) allow for straightforward comparison with a standard single-input single-output (SISO) OFDM system.

AoI in Context-Aware Hybrid Radio-Optical IoT Networks

With the surge in IoT devices ranging from wearables to smart homes, prompt transmission is crucial. The Age of Information (AoI) emerges as a critical metric in this context, representing the freshness of the information transmitted across the network. This paper studies hybrid IoT networks that employ Optical Communication (OC) as a reinforcement medium to Radio Frequency (RF). We formulate a quadratic convex optimization that adopts a Pareto optimization strategy to dynamically schedule the communication between devices and select their corresponding communication technology, aiming to balance the maximization of network throughput with the minimization of energy usage and the frequency of switching between technologies. To mitigate the impact of dominant sub-objectives and their scale disparity, the designed approach employs a regularization method that approximates adequate Pareto coefficients. Simulation results show that the OC supplementary integration alongside RF enhances the network's overall performances and significantly reduces the Mean AoI and Peak AoI, allowing the collection of the freshest possible data using the best available communication technology.

User-Movement-Robust Virtual Reality Through Dual-Beam Reception in mmWave Networks

Utilizing the mmWave band can potentially achieve the high data rate needed for realistic and seamless interaction within a virtual reality (VR) application. To this end, beamforming in both the access point (AP) and head-mounted display (HMD) sides is necessary. The main challenge in this use case is the specific and highly dynamic user movement, which causes beam misalignment, degrading the received signal level and potentially leading to outages. This study examines mmWave-based coordinated multi-point networks for VR applications, where two or multiple APs cooperatively transmit the signals to an HMD for connectivity diversity. Instead of using omnireception, we propose dual-beam reception based on the analog beamforming at the HMD, enhancing the receive beamforming gain towards serving APs while achieving diversity. Evaluation using actual HMD movement data demonstrates the effectiveness of our approach, showcasing a reduction in outage rates of up to 13% compared to quasi-omnidirectional reception with two serving APs, and a 17% decrease compared to steerable single-beam reception with a serving AP. Widening the separation angle between two APs can further reduce outage rates due to head rotation as rotations can still be tracked using the steerable multi-beam, albeit at the expense of received signal levels reduction during the non-outage period.

Balanced Space- and Time-based Duty-cycle Scheduling for Light-based IoT

In this work, we propose a Multiple Access Control (MAC) protocol for Light-based IoT (LIoT) networks, where the gateway node orchestrates and schedules batteryless nodes duty-cycles based on their location and sleep time. The LIoT concept represents a sustainable solution for massive indoor IoT applications, offering an alternative communication medium through Visible Light Communication (VLC). While most existing scheduling algorithms for intermittent batteryless IoT aim to maximize data collection and enhance dataset size, our solution is tailored for environmental sensing applications, such as temperature, humidity, and air quality monitoring, optimizing measurement distribution and minimizing blind spots to achieve comprehensive and uniform environmental sensing. We propose a Balanced Space and Time-based Time Division Multiple Access scheduling (BST-TDMA) algorithm, which addresses environmental sensing challenges by balancing spatial and temporal factors to improve the environmental sensing efficiency of batteryless LIoT nodes. Our measurement-based results show that BST-TDMA was able to efficiently schedule duty-cycles with given intervals.

Building a real-time physical layer labeled data logging facility for 6G research

This work describes the architecture and vision of designing and implementing a new test infrastructure for 6G physical layer research at KU Leuven. The Testbed is designed for physical layer research and experimentation following several emerging trends, such as cell-free networking, integrated communication, sensing, open disaggregated Radio Access Networks, AI-Native design, and multiband operation. The software is almost entirely based on free and open-source software, making contributing and reusing any component easy. The open Testbed is designed to provide real-time and labeled data on all parts of the physical layer, from raw IQ data to synchronization statistics, channel state information, or symbol/bit/packet error rates. Real-time labeled datasets can be collected by synchronizing the physical layer data logging with a positioning and motion capture system. One of the main goals of the design is to make it open and accessible to external users remotely. Most tests and data captures can easily be automated, and experiment code can be remotely deployed using standard containers (e.g., Docker or Podman). Finally, the paper describes how the Testbed can be used for our research on joint communication and sensing, over-the-air synchronization, distributed processing, and AI in the loop.

Cell-free Massive MIMO with Sequential Fronthaul Architecture and Limited Memory Access Points

Cell-free massive multiple-input multiple-output (CFmMIMO) is a paradigm that can improve users' spectral efficiency (SE) far beyond traditional cellular networks. Increased spatial diversity in CFmMIMO is achieved by spreading the antennas into small access points (APs), which cooperate to serve the users. Sequential fronthaul topologies in CFmMIMO, such as the daisy chain and multi-branch tree topology, have gained considerable attention recently. In such a processing architecture, each AP must store its received signal vector in the memory until it receives the relevant information from the previous AP in the sequence to refine the estimate of the users' signal vector in the uplink. In this paper, we adopt vector-wise and element-wise compression on the raw or pre-processed received signal vectors to store them in the memory. We investigate the impact of the limited memory capacity in the APs on the optimal number of APs. We show that with no memory constraint, having single-antenna APs is optimal, especially as the number of users grows. However, a limited memory at the APs restricts the depth of the sequential processing pipeline. Furthermore, we investigate the relation between the memory capacity at the APs and the rate of the fronthaul link.

Batteryless BLE and Light-based IoT Sensor Nodes for Reliable Environmental Sensing

The sustainable design of Internet of Things (IoT) networks encompasses considerations related to energy efficiency and autonomy as well as considerations related to reliable communications, ensuring no energy is wasted on undelivered data. Under these considerations, this work proposes the design and implementation of energy-efficient Bluetooth Low Energy (BLE) and Light-based IoT (LIoT) batteryless IoT sensor nodes powered by an indoor light Energy Harvesting Unit (EHU). Our design intends to integrate these nodes into a sensing network to improve its reliability by combining both technologies and taking advantage of their features. The nodes incorporate state-of-the-art components, such as low-power sensors and efficient System-on-Chips (SoCs). Moreover, we design a strategy for adaptive switching between active and sleep cycles as a function of the available energy, allowing the IoT nodes to continuously operate without batteries. Our results show that by adapting the duty cycle of the BLE and LIoT nodes depending on the environment's light intensity, we can ensure a continuous and reliable node operation. In particular, measurements show that our proposed BLE and LIoT node designs are able to communicate with an IoT gateway in a bidirectional way, every 19.3 and 624.6 seconds, respectively, in an energy-autonomous and reliable manner.

Distributed PMCW Radar Network in Presence of Phase Noise

In Frequency Modulated Continuous Waveform (FMCW) radar systems, the phase noise from the Phase-Locked Loop (PLL) can increase the noise floor in the Range-Doppler map. The adverse effects of phase noise on close targets can be mitigated if the transmitter (Tx) and receiver (Rx) employ the same chirp, a phenomenon known as the range correlation effect. In the context of a multi-static radar network, sharing the chirp between distant radars becomes challenging. Each radar generates its own chirp, leading to uncorrelated phase noise. Consequently, the system performance cannot benefit from the range correlation effect. Previous studies show that selecting a suitable code sequence for a Phase Modulated Continuous Waveform (PMCW) radar can reduce the impact of uncorrelated phase noise in the range dimension. In this paper, we demonstrate how to leverage this property to exploit both the mono- and multi-static signals of each radar in the network without having to share any signal at the carrier frequency. The paper introduces a detailed signal model for PMCW radar networks, analyzing both correlated and uncorrelated phase noise effects in the Doppler dimension. Additionally, a solution for compensating uncorrelated phase noise in Doppler is presented and supported by numerical results.