Optimizing Antenna Arrays for Spatial Multiplexing: Towards 6G Systems

In this paper we discuss the design of antenna arrays to be used for multiplexing applications. In particular, we introduce a suitable performance index to analyze the effect of the antenna geometry and the distribution of users for the overall performance of Multi-User Multiple Input Multiple Output systems. By means of such performance index, antenna arrays can be designed so as to increase the number of multiplexed parallel sub-channels. Numerical results show that a proper design could allow to double the contemporary served users and the overall system throughput

Noncontact Vital Signs Detection

Human health condition can be accessed by measurement of vital signs, i.e., respiratory rate (RR), heart rate (HR), blood oxygen level, temperature and blood pressure. Due to drawbacks of contact sensors in measurement, non-contact sensors such as imaging photoplethysmogram (IPPG) and Doppler radar system have been proposed for cardiorespiratory rates detection by researchers.The UWB pulse Doppler radars provide high resolution range-time-frequency information. It is bestowed with advantages of low transmitted power, through-wall capabilities, and high resolution in localization. However, the poor signal to noise ratio (SNR) makes it challenging for UWB radar systems to accurately detect the heartbeat of a subject. To solve the problem, phased-methods have been proposed to extract the phase variations in the reflected pulses modulated by human tiny thorax motions. Advance signal processing method, i.e., state space method, can not only be used to enhance SNR of human vital signs detection, but also enable the micro-Doppler trajectories extraction of walking subject from UWB radar data.Stepped Frequency Continuous Wave (SFCW) radar is an alternative technique useful to remotely monitor human subject activities. Compared with UWB pulse radar, it relieves the stress on requirement of high sampling rate analog-to-digital converter (ADC) and possesses higher signal-to-noise-ratio (SNR) in vital signs detection. However, conventional SFCW radar suffers from long data acquisition time to step over many frequencies. To solve this problem, multi-channel SFCW radar has been proposed to step through different frequency bandwidths simultaneously. Compressed sensing (CS) can further reduce the data acquisition time by randomly stepping through 20% of the original frequency steps.In this work, SFCW system is implemented with low cost, off-the-shelf surface mount components to make the radar sensors portable. Experimental results collected from both pulse and SFCW radar systems have been validated with commercial contact sensors and satisfactory results are shown

Wi-Fi based people tracking in challenging environments

People tracking is a key building block in many applications such as abnormal activity detection, gesture recognition, and elderly persons monitoring. Video-based systems have many limitations making them ineffective in many situations. Wi-Fi provides an easily accessible source of opportunity for people tracking that does not have the limitations of video-based systems. The system will detect, localise, and track people, based on the available Wi-Fi signals that are reflected from their bodies. Wi-Fi based systems still need to address some challenges in order to be able to operate in challenging environments. Some of these challenges include the detection of the weak signal, the detection of abrupt people motion, and the presence of multipath propagation. In this thesis, these three main challenges will be addressed. Firstly, a weak signal detection method that uses the changes in the signals that are reflected from static objects, to improve the detection probability of weak signals that are reflected from the person’s body. Then, a deep learning based Wi-Fi localisation technique is proposed that significantly improves the runtime and the accuracy in comparison with existing techniques. After that, a quantum mechanics inspired tracking method is proposed to address the abrupt motion problem. The proposed method uses some interesting phenomena in the quantum world, where the person is allowed to exist at multiple positions simultaneously. The results show a significant improvement in reducing the tracking error and in reducing the tracking delay

WiFi Sensing at the Edge Towards Scalable On-Device Wireless Sensing Systems

WiFi sensing offers a powerful method for tracking physical activities using the radio-frequency signals already found throughout our homes and offices. This novel sensing modality offers continuous and non-intrusive activity tracking since sensing can be performed (i) without requiring wearable sensors, (ii) outside the line-of-sight, and even (iii) through the wall. Furthermore, WiFi has become a ubiquitous technology in our computers, our smartphones, and even in low-cost Internet of Things devices. In this work, we consider how the ubiquity of these low-cost WiFi devices offer an unparalleled opportunity for improving the scalability of wireless sensing systems. Thus far, WiFi sensing research assumes costly offline computing resources and hardware for training machine learning models and for performing model inference. To improve the scalability of WiFi sensing systems, this dissertation introduces techniques for improving machine learning at the edge by thoroughly surveying and evaluating signal preprocessing and edge machine learning techniques. Additionally, we introduce the use of federated learning for collaboratively training machine learning models with WiFi data only available on edge devices. We then consider privacy and security concerns of WiFi sensing by demonstrating possible adversarial surveillance attacks. To combat these attacks, we propose a method for leveraging spatially distributed antennas to prevent eavesdroppers from performing adversarial surveillance while still enabling and even improving the sensing capabilities of allowed WiFi sensing devices within our environments. The overall goal throughout this work is to demonstrate that WiFi sensing can become a ubiquitous and secure sensing option through the use of on-device computation on low-cost edge devices

Robust 5G/B5G Millimeter Wave MIMO Communication in a Sparse Scattering Environment

M.S

Cellular, Wide-Area, and Non-Terrestrial IoT: A Survey on 5G Advances and the Road Towards 6G

The next wave of wireless technologies is proliferating in connecting things among themselves as well as to humans. In the era of the Internet of things (IoT), billions of sensors, machines, vehicles, drones, and robots will be connected, making the world around us smarter. The IoT will encompass devices that must wirelessly communicate a diverse set of data gathered from the environment for myriad new applications. The ultimate goal is to extract insights from this data and develop solutions that improve quality of life and generate new revenue. Providing large-scale, long-lasting, reliable, and near real-time connectivity is the major challenge in enabling a smart connected world. This paper provides a comprehensive survey on existing and emerging communication solutions for serving IoT applications in the context of cellular, wide-area, as well as non-terrestrial networks. Specifically, wireless technology enhancements for providing IoT access in fifth-generation (5G) and beyond cellular networks, and communication networks over the unlicensed spectrum are presented. Aligned with the main key performance indicators of 5G and beyond 5G networks, we investigate solutions and standards that enable energy efficiency, reliability, low latency, and scalability (connection density) of current and future IoT networks. The solutions include grant-free access and channel coding for short-packet communications, non-orthogonal multiple access, and on-device intelligence. Further, a vision of new paradigm shifts in communication networks in the 2030s is provided, and the integration of the associated new technologies like artificial intelligence, non-terrestrial networks, and new spectra is elaborated. Finally, future research directions toward beyond 5G IoT networks are pointed out.Comment: Submitted for review to IEEE CS&

A Software Defined Radio Interrogator for Passive Harmonic Transponders

Passive wireless sensors provide an opportunity for long term monitoring of remote environments. Since these devices are not battery powered, they can be deployed for an indefinite amount of time. Such devices are energized by an interrogation signal that enables them to transmit information via a return signal. Some systems (e.g., RFID) utilize the same frequency for interrogation and the return, which causes unwanted interference, particularly in cluttered environments. This work considers an interrogation system for a different class of passive devices, i.e., passive harmonic transponders. Specifically, results are presented for a single-board software defined radio (SDR) interrogation system which transmits an interrogation signal at 1.3 GHz and receives a return at 2.6 GHz. The system is demonstrated with a passive, chip-less device known as a frequency doubling reflectenna (FDR). The SDR platform enables a compact, low-cost, and quickly operating design. The mean absolute error of the proposed interrogator was found to be 1.15 dB when compared with laboratory-grade instrumentation. Additionally, this system is capable of interrogating up to a distance of 70 cm with an EIRP of only 0 dBm. This thesis presents an SDR system made with the open-source software package, GNURadio, capable of interrogating harmonic transponders with a single, full-duplex board. All signal processing is conducted on a laptop computer, eliminating the need for expensive laboratory instrumentation. The size of the system interrogator was also minimized, reducing the form factor of the whole interrogator to be only 25 $\times$ 15 cm. Furthermore, a new harmonic transponder was designed using transmission line matching methods, eliminating the need for discrete matching components. This harmonic transponder has a conversion loss of 31.04 dB at an input power of -28.21 dBm as demonstrated with the SDR interrogator

SHM with DOFS of the TMB L-9 tunnel affected by nearby building construction

Degut a la construcció d´un edifici proper, el túnel de la línia 9 es pot veure afectat en el seu estat de deformació i tensional. Per tal de fer un seguiment continuu durant tot el periode de treballs, es planteja una monitorització de la volta i llossa del túnel amb un sensor de fibra òptica distribuïda, que permetrà obtenir les deformacions al formigó amb una resolució de l´ordre de 1 centímetr