892 research outputs found
Autonomous Radar-based Gait Monitoring System
Features related to gait are fundamental metrics of human motion [1]. Human gait has been shown to be a valuable and feasible clinical marker to determine the risk of physical and mental functional decline [2], [3]. Technologies that detect changes in peopleâs gait patterns, especially older adults, could support the detection, evaluation, and monitoring of parameters related to changes in mobility, cognition, and frailty. Gait assessment has the potential to be leveraged as a clinical measurement as it is not limited to a specific health care discipline and is a consistent and sensitive test [4].
A wireless technology that uses electromagnetic waves (i.e., radar) to continually measure gait parameters at home or in a hospital without a clinicianâs participation has been proposed as a suitable solution [3], [5]. This approach is based on the interaction between electromagnetic waves with humans and how their bodies impact the surrounding and scattered wireless signals. Since this approach uses wireless waves, people do not need to wear or carry a device on their bodies. Additionally, an electromagnetic wave wireless sensor has no privacy issues because there is no video-based camera.
This thesis presents the design and testing of a radar-based contactless system that can monitor peopleâs gait patterns and recognize their activities in a range of indoor environments frequently and accurately. In this thesis, the use of commercially available radars for gait monitoring is investigated, which offers opportunities to implement unobtrusive and contactless gait monitoring and activity recognition. A novel fast and easy-to-implement gait extraction algorithm that enables an individualâs spatiotemporal gait parameter extraction at each gait cycle using a single FMCW (Frequency Modulated Continuous Wave) radar is proposed. The proposed system detects changes in gait that may be the signs of changes in mobility, cognition, and frailty, particularly for older adults in individualâs homes, retirement homes and long-term care facilities retirement homes. One of the straightforward applications for gait monitoring using radars is in corridors and hallways, which are commonly available in most residential homes, retirement, and long-term care homes. However, walls in the hallway have a strong âclutterâ impact, creating multipath due to the wide beam of commercially available radar antennas. The multipath reflections could result in an inaccurate gait measurement because gait extraction algorithms employ the assumption that the maximum reflected signals come from the torso of the walking person (rather than indirect reflections or multipath) [6].
To address the challenges of hallway gait monitoring, two approaches were used: (1) a novel signal processing method and (2) modifying the radar antenna using a hyperbolic lens. For the first approach, a novel algorithm based on radar signal processing, unsupervised learning, and a subject detection, association and tracking method is proposed. This proposed algorithm could be paired with any type of multiple-input multiple-output (MIMO) or single-input multiple-output (SIMO) FMCW radar to capture human gait in a highly cluttered environment without needing radar antenna alteration. The algorithm functionality was validated by capturing spatiotemporal gait values (e.g., speed, step points, step time, step length, and step count) of people walking in a hallway. The preliminary results demonstrate the promising potential of the algorithm to accurately monitor gait in hallways, which increases opportunities for its applications in institutional and home environments. For the second approach, an in-package hyperbola-based lens antenna was designed that can be integrated with a radar module package empowered by the fast and easy-to-implement gait extraction method. The system functionality was successfully validated by capturing the spatiotemporal gait values of people walking in a hallway filled with metallic cabinets. The results achieved in this work pave the way to explore the use of stand-alone radar-based sensors in long hallways for day-to-day long-term monitoring of gait parameters of older adults or other populations.
The possibility of the coexistence of multiple walking subjects is high, especially in long-term care facilities where other people, including older adults, might need assistance during walking. GaitRite and wearables are not able to assess multiple peopleâs gait at the same time using only one device [7], [8]. In this thesis, a novel radar-based algorithm is proposed that is capable of tracking multiple people or extracting walking speed of a participant with the coexistence of other people. To address the problem of tracking and monitoring multiple walking people in a cluttered environment, a novel iterative framework based on unsupervised learning and advanced signal processing was developed and tested to analyze the reflected radio signals and extract walking movements and trajectories in a hallway environment. Advanced algorithms were developed to remove multipath effects or ghosts created due to the interaction between walking subjects and stationary objects, to identify and separate reflected signals of two participants walking at a close distance, and to track multiple subjects over time. This method allows the extraction of walking speed in multiple closely-spaced subjects simultaneously, which is distinct from previous approaches where the speed of only one subject was obtained. The proposed multiple-people gait monitoring was assessed with 22 participants who participated in a bedrest (BR) study conducted at McGill University Health Centre (MUHC).
The system functionality also was assessed for in-home applications. In this regard, a cloud-based system is proposed for non-contact, real-time recognition and monitoring of physical activities and walking periods within a domestic environment. The proposed system employs standalone Internet of Things (IoT)-based millimeter wave radar devices and deep learning models to enable autonomous, free-living activity recognition and gait analysis. Range-Doppler maps generated from a dataset of real-life in-home activities are used to train deep learning models. The performance of several deep learning models was evaluated based on accuracy and prediction time, with the gated recurrent network (GRU) model selected for real-time deployment due to its balance of speed and accuracy compared to 2D Convolutional Neural Network Long Short-Term Memory (2D-CNNLSTM) and Long Short-Term Memory (LSTM) models. In addition to recognizing and differentiating various activities and walking periods, the system also records the subjectâs activity level over time, washroom use frequency, sleep/sedentary/active/out-of-home durations, current state, and gait parameters. Importantly, the system maintains privacy by not requiring the subject to wear or carry any additional devices
Ultra-Wideband Trained Artificial Neural Networks for Bluetooth Proximity Detection in Small Crowded Areas
Estimating the distance between indoor users is increasingly important in unexpected ways. One specific example is the need for electronic contact tracing demonstrated during the recent global pandemic. Smartphones are now routinely equipped with Bluetooth Low Energy radios, among other sensors, and these can be used for proximity detection based on received signal strength that is subject to errors due to poor modelling of the indoor propagation environment. Some high-end smartphones have now also been equipped with ultra-wideband ranging radios that provide a much more precise range measurement. This thesis demonstrates the concept of using a limited number of UWB-equipped smartphones to gather data to train Artificial Neural Networks (ANN) to improve short-range distance estimation among Bluetooth users. The trained RSSI to range model can be used for proximity determination by other Bluetooth users in small, crowded areas. Two ANN algorithms were trained using RSSI measurements from three BLE advertising channels and UWB range as ground truth and training data. The initial training and testing were conducted in a semi-empty office laboratory with 2130 observations. The RF model used 1917 samples (90% of data) for training and 213 samples (10%) for testing, while the CNN method used 1704 samples (80% of data) for training and 426 samples (20%) for evaluation. The trained neural network models were tested in two other office environments under different user conditions. The results indicate that the ANN models can estimate proximity in a new environment without further training with a mean error of less than 1.2 metres, within a range of up to 6 metres at line-of-sight (LOS). In highly constrained non-line-of-sight (NLOS) areas in the first office room, the proposed models provided proximity accuracy better than 2.9 metres. Furthermore, during testing across two adjacent office environments, each containing a single BLE device with complex furniture arrangements, the ANN models showed the proximity between the BLE devices with an error of less than 2-3 metres
A Survey on Low-Power GNSS
With the miniaturization of electronics, Global Navigation Satellite Systems (GNSS) receivers are getting more and more embedded into devices with harsh energy constraints. This process has led to new signal processing challenges due to the limited processing power on battery-operated devices and to challenging wireless environments, such as deep urban canyons, tunnels and bridges, forest canopies, increased jamming and spoofing. The latter is typically tackled via new GNSS constellations and modernization of the GNSS signals. However, the increase in signal complexity leads to higher computation requirements to recover the signals; thus, the trade-off between precision and energy should be evaluated for each application. This paper dives into low-power GNSS, focusing on the energy consumption of satellite-based positioning receivers used in battery-operated consumer devices and Internet of Things (IoT) sensors. We briefly overview the GNSS basics and the differences between legacy and modernized signals. Factors dominating the energy consumption of GNSS receivers are then reviewed, with special attention given to the complexity of the processing algorithms. Onboard and offloaded (Cloud/Edge) processing strategies are explored and compared. Finally, we highlight the current challenges of todayâs research in low-power GNSS.Peer reviewe
Localizability Optimization for Multi Robot Systems and Applications to Ultra-Wide Band Positioning
RĂSUMĂ: RĂSUMĂ Les SystĂšmes Multi-Robots (SMR) permettent dâeffectuer des missions de maniĂšre efficace et robuste du fait de leur redondance. Cependant, les robots Ă©tant des vĂ©hicules autonomes, ils nĂ©cessitent un positionnement prĂ©cis en temps rĂ©el. Les techniques de localisation qui utilisent des Mesures Relatives (MR) entre les robots, pouvant ĂȘtre des distances ou des angles, sont particuliĂšrement adaptĂ©es puisquâelles peuvent bĂ©nĂ©ficier dâalgorithmes coopĂ©ratifs au sein du SMR afin dâamĂ©liorer la prĂ©cision pour lâensemble des robots. Dans cette thĂšse, nous proposons des stratĂ©gies pour amĂ©liorer la localisabilitĂ© des SMR, qui est fonction de deux facteurs. PremiĂšrement, la gĂ©omĂ©trie du SMR influence fondamentalement la qualitĂ© de son positionnement pour des MR bruitĂ©es. DeuxiĂšmement, les erreurs de mesures dĂ©pendent fortement de la technologie utilisĂ©e. Dans nos expĂ©riences, nous nous focalisons sur la technologie UWB (Ultra-Wide Band), qui est populaire pour le positionnement des robots en environnement intĂ©rieur en raison de son coĂ»t modĂ©rĂ© et sa haute prĂ©cision. Par consĂ©quent, une partie de notre travail est consacrĂ©e Ă la correction des erreurs de mesure UWB afin de fournir un systĂšme de navigation opĂ©rationnel. En particulier, nous proposons une mĂ©thode de calibration des biais systĂ©matiques et un algorithme dâattĂ©nuation des trajets multiples pour les mesures de distance en milieu intĂ©rieur. Ensuite, nous proposons des Fonctions de CoĂ»t de LocalisabilitĂ© (FCL) pour caractĂ©riser la gĂ©omĂ©trie du SMR, et sa capacitĂ© Ă se localiser. Pour cela, nous utilisons la Borne InfĂ©rieure de CramĂ©r-Rao (BICR) en vue de quantifier les incertitudes de positionnement. Par la suite, nous fournissons des schĂ©mas dâoptimisation dĂ©centralisĂ©s pour les FCL sous lâhypothĂšse de MR gaussiennes ou log-normales. En effet, puisque le SMR peut se dĂ©placer, certains de ses robots peuvent ĂȘtre dĂ©ployĂ©s afin de minimiser la FCL. Cependant, lâoptimisation de la localisabilitĂ© doit ĂȘtre dĂ©centralisĂ©e pour ĂȘtre adaptĂ©e Ă des SMRs Ă grande Ă©chelle. Nous proposons Ă©galement des extensions des FCL Ă des scĂ©narios oĂč les robots embarquent plusieurs capteurs, oĂč les mesures se dĂ©gradent avec la distance, ou encore oĂč des informations prĂ©alables sur la localisation des robots sont disponibles, permettant dâutiliser la BICR bayĂ©sienne. Ce dernier rĂ©sultat est appliquĂ© au placement dâancres statiques connaissant la distribution statistique des MR et au maintien de la localisabilitĂ© des robots qui se localisent par filtrage de Kalman. Les contributions thĂ©oriques de notre travail ont Ă©tĂ© validĂ©es Ă la fois par des simulations Ă grande Ă©chelle et des expĂ©riences utilisant des SMR terrestres. Ce manuscrit est rĂ©digĂ© par publication, il est constituĂ© de quatre articles Ă©valuĂ©s par des pairs et dâun chapitre supplĂ©mentaire. ABSTRACT: ABSTRACT Multi-Robot Systems (MRS) are increasingly interesting to perform tasks eĂżciently and robustly. However, since the robots are autonomous vehicles, they require accurate real-time positioning. Localization techniques that use relative measurements (RMs), i.e., distances or angles, between the robots are particularly suitable because they can take advantage of cooperative schemes within the MRS in order to enhance the precision of its positioning. In this thesis, we propose strategies to improve the localizability of the SMR, which is a function of two factors. First, the geometry of the MRS fundamentally influences the quality of its positioning under noisy RMs. Second, the measurement errors are strongly influenced by the technology chosen to gather the RMs. In our experiments, we focus on the Ultra-Wide Band (UWB) technology, which is popular for indoor robot positioning because of its mod-erate cost and high accuracy. Therefore, one part of our work is dedicated to correcting the UWB measurement errors in order to provide an operable navigation system. In particular, we propose a calibration method for systematic biases and a multi-path mitigation algorithm for indoor distance measurements. Then, we propose Localizability Cost Functions (LCF) to characterize the MRSâs geometry, using the CramĂ©r-Rao Lower Bound (CRLB) as a proxy to quantify the positioning uncertainties. Subsequently, we provide decentralized optimization schemes for the LCF under an assumption of Gaussian or Log-Normal RMs. Indeed, since the MRS can move, some of its robots can be deployed in order to decrease the LCF. However, the optimization of the localizability must be decentralized for large-scale MRS. We also propose extensions of LCFs to scenarios where robots carry multiple sensors, where the RMs deteriorate with distance, and finally, where prior information on the robotsâ localization is available, allowing the use of the Bayesian CRLB. The latter result is applied to static anchor placement knowing the statistical distribution of the MRS and localizability maintenance of robots using Kalman filtering. The theoretical contributions of our work have been validated both through large-scale simulations and experiments using ground MRS. This manuscript is written by publication, it contains four peer-reviewed articles and an additional chapter
Security and Privacy for Modern Wireless Communication Systems
The aim of this reprint focuses on the latest protocol research, software/hardware development and implementation, and system architecture design in addressing emerging security and privacy issues for modern wireless communication networks. Relevant topics include, but are not limited to, the following: deep-learning-based security and privacy design; covert communications; information-theoretical foundations for advanced security and privacy techniques; lightweight cryptography for power constrained networks; physical layer key generation; prototypes and testbeds for security and privacy solutions; encryption and decryption algorithm for low-latency constrained networks; security protocols for modern wireless communication networks; network intrusion detection; physical layer design with security consideration; anonymity in data transmission; vulnerabilities in security and privacy in modern wireless communication networks; challenges of security and privacy in nodeâedgeâcloud computation; security and privacy design for low-power wide-area IoT networks; security and privacy design for vehicle networks; security and privacy design for underwater communications networks
Multipath assisted positioning using machine learning
The multipath propagation of the radio signal was considered a problem for
positioning systems that had to be eliminated. However, a groundbreaking new
approach called multipath assisted positioning caused a paradigm shift, where multipath propagation improves the positioning performance. Moreover, the multipath
assisted positioning algorithm called Channel-SLAM shows the possibility of using
a single physical transmitter in a multipath environment for positioning. In this
thesis, I open a discussion on some problems that have vital importance for multipath assisted positioning algorithms with a focus on pedestrian positioning. Using
the idea of multipath assisted positioning, I present a single frequency network
positioning algorithm. I evaluated the single frequency network-based positioning
algorithm for positioning in a real scenario using a terrestrial digital video broadcasting transmission. I propose a novel pedestrian transition model utilizing the
inertial measurements from a handheld inertial measurement unit. The proposed
pedestrian transition model improves the precision and reliability of the Channel-SLAM. Comparing the proposed transition model with the Rician transition model
previously used in Channel-SLAM quantifies the performance improvement. This
thesis proposes a joint data association technique that overcomes the strong dependence on the radio channel estimation algorithm used in Channel-SLAM. The
joint data association allows reusing the previously observed virtual transmitters
after an outage of multipath component tracking. The evaluation based on the
walking pedestrian scenario shows that the joint data association algorithm provides superior positioning precision. The virtual transmitter position estimation
yields a significant computational load in Channel-SLAM. I propose a method
that represents the virtual transmitter by a Gaussian mixture model and learns
its parameters. The evaluation shows that the proposed method outperforms the
previous approach while decreasing the computational load. Also, the current
methods for radio channel estimation yield a considerable computational load that
prohibits a real-time deployment. The thesis investigates the possibility of using
artificial neural networks trained to estimate the number of multipath components
and corresponding delays in a noisy measurement of a channel impulse response.
The artificial neural network-based delay estimator provides a superresolution performance and faster runtime than the classical approaches. The precision of the
trained artificial neural network architecture is evaluated and compared to the
Cramer-Rao lower bound theoretical limit and classical channel estimation algorithms
Starlink receiver prototyping for opportunistic positioning
openTraditional GNSS systems for positioning (PNT), such as GPS and Galileo, use Medium Earth Orbits (MEO). Recently, the possibility to use Low Earth Orbit (LEO) orbits for PNT has been investigated, which offer several advantages over the traditional MEO, e.g., higher power and wider band.
Among the available signals of opportunity (SOOPs), this thesis project investigates the feasibility of utilizing Starlink signals, primarily designed for global Internet coverage, for positioning purposes.
The Starlink signal structure is not publicly available, but the literature suggests the presence of nine equidistant spectral peaks within a band of approximately 1 MHz in the signal spectrum of each satellite, centered at frequency 11,325 GHz. The method proposed in this thesis involves the acquisition and tracking of these peaks, on a signal sampled at a lower frequency than the estimated bandwidth for the entire Starlink channel of 240 MHz, in order to reduce receiver complexity.
For the acquisition phase, once the IQ components have been extracted from the signal, the optimal acquisition window length is selected as the trade-off between noise and Fast Fourier Transform (FFT) computational performance. The peak detection threshold is chosen based on the Gaussian distribution of noise and a predefined false alarm probability. This enables the selection of peaks above the noise floor in each acquisition instance, facilitating the detection of potential satellites.
Then, similar to standard GNSS receivers, a tracking loop (a third-order PLL assisted by a second-order FLL) is implemented to estimate the Doppler frequency shift of the peaks over the entire captured window. However, as opposed to standard GNSS signals, Starlink does not use a PRN code to identify the individual satellites. To resolve the ambiguity in satellite identification, a method is proposed to compare the Doppler frequency shifts estimated from peak tracking with the Doppler frequency shifts predicted by a visibility prediction tool, which provides the ability to associate each identified peak with a specific Starlink satellite. The tool uses Two-Line Element Sets (TLEs) data and a simplified perturbation model (SGP4) to propagate the satellite orbits.
The method is applied to a signal captured using a basic configuration with a Ku-band Low Noise Block (LNB) converter, and the data acquired consist of raw In-phase and Quadrature-phase (IQ) samples with a bandwidth of 4,096 MHz around 11,325 GHz. The results show that the method allows to acquire several satellites in the captured signal, and to track the corresponding peaks for positioning purposes
Analysis and Design of Silicon based Integrated Circuits for Radio Frequency Identification and Ranging Systems at 24GHz and 60GHz Frequency Bands
This scientific research work presents the analysis and design of radio frequency (RF) integrated circuits (ICs) designed for two cooperative RF identification (RFID) proof of concept systems. The first system concept is based on localizable and sensor-enabled superregenerative transponders (SRTs) interrogated using a 24GHz linear frequency modulated continuous wave (LFMCW) secondary radar. The second system concept focuses on low power components for a 60GHz continuous wave (CW) integrated single antenna frontend for interrogating close range passive backscatter transponders (PBTs).
In the 24GHz localizable SRT based system, a LFMCW interrogating radar sends a RF chirp signal to interrogate SRTs based on custom superregenerative amplifier (SRA) ICs. The SRTs receive the chirp and transmit it back with phase coherent amplification. The distance to the SRTs are then estimated using the round trip time of flight method. Joint data transfer from the SRT to the interrogator is enabled by a novel SRA quench frequency shift keying (SQ-FSK) based low data rate simplex communication. The SRTs are also designed to be roll invariant using bandwidth enhanced microstrip patch antennas. Theoretical analysis is done to derive expressions as a function of system parameters including the minimum SRA gain required for attaining a defined range and equations for the maximum number of symbols that can be transmitted in data transfer mode. Analysis of the dependency of quench pulse characteristics during data transfer shows that the duty cycle has to be varied while keeping the on-time constant to reduce ranging errors. Also the worsening of ranging precision at longer distances is predicted based on the non-idealities resulting from LFMCWchirp quantization due to SRT characteristics and is corroborated by system level measurements. In order to prove the system concept and study the semiconductor technology dependent factors, variants of 24GHz SRA ICs are designed in a 130nm silicon germanium (SiGe) bipolar complementary metal oxide technology (BiCMOS) and a partially depleted silicon on insulator (SOI) technology. Among the SRA ICs designed, the SiGe-BiCMOS ICs feature a novel quench pulse shaping concept to simultaneously improve the output power and minimum detectable input power. A direct antenna drive SRA IC based on a novel stacked transistor cross-coupled oscillator topology employing this concept exhibit one of the best reported combinations of minimum detected input power level of â100 dBm and output power level of 5.6 dBm, post wirebonding. The SiGe stacked transistor with base feedback capacitance topology employed in this design is analyzed to derive parameters including the SRA loop gain for design optimization. Other theoretical contributions include the analysis of the novel integrated quench pulse shaping circuit and formulas derived for output voltage swing taking bondwire losses into account. Another SiGe design variant is the buffered antenna drive SRA IC having a measured minimum detected input power level better than â80 dBm, and an output power level greater than 3.2 dBm after wirebonding. The two inputs and outputs of this IC also enables the design of roll invariant SRTs. Laboratory based ranging experiments done to test the concepts and theoretical considerations show a maximum measured distance of 77m while transferring data at the rate of 0.5 symbols per second using SQ-FSK. For distances less than 10m, the characterized accuracy is better than 11 cm and the precision is better than 2.4 cm. The combination of the maximum range, precision and accuracy are one of the best reported among similar works in literature to the authorâs knowledge.
In the 60GHz close range CW interrogator based system, the RF frontend transmits a continuous wave signal through the transmit path of a quasi circulator (QC) interfaced to an antenna to interrogate a PBT. The backscatter is received using the same antenna interfaced to the QC. The received signal is then amplified and downconverted for further processing. To prove this concept, two optimized QC ICs and a downconversion mixer IC are designed in a 22nm fully depleted SOI technology. The first QC is the transmission lines based QC which consumes a power of 5.4mW, operates at a frequency range from 56GHz to 64GHz and occupies an area of 0.49mm2. The transmit path loss is 5.7 dB, receive path gain is 2 dB and the tunable transmit path to receive path isolation is between 20 dB and 32 dB. The second QC is based on lumped elements, and operates in a relatively narrow bandwidth from 59.6GHz to 61.5GHz, has a gain of 8.5 dB and provides a tunable isolation better than 20 dB between the transmit and receive paths. This QC design also occupies a small area of 0.34mmÂČ while consuming 13.2mW power. The downconversion is realized using a novel folded switching stage down conversion mixer (FSSDM) topology optimized to achieve one of the best reported combination of maximum voltage conversion gain of 21.5 dB, a factor of 2.5 higher than reported state-of-the-art results, and low power consumption of 5.25mW. The design also employs a unique back-gate tunable intermediate frequency output stage using which a gain tuning range of 5.5 dB is attained. Theoretical analysis of the FSSDM topology is performed and equations for the RF input stage transconductance, bandwidth, voltage conversion gain and gain tuning are derived. A feasibility study for the components of the 60GHz integrated single antenna interrogator frontend is also performed using PBTs to prove the system design concept.:1 Introduction 1
1.1 Motivation and Related Work . . . . . . . . . . . . . . . . . . . . . 1
1.2 Scope and Functional Specifications . . . . . . . . . . . . . . . . . 4
1.3 Objectives and Structure . . . . . . . . . . . . . . . . . . . . . . . . 5
2 Features and Fundamentals of RFIDs and Superregenerative Amplifiers 9
2.1 RFID Transponder Technology . . . . . . . . . . . . . . . . . . . . 9
2.1.1 Chipless RFID Transponders . . . . . . . . . . . . . . . . . 10
2.1.2 Semiconductor based RFID Transponders . . . . . . . . . . 11
2.1.2.1 Passive Transponders . . . . . . . . . . . . . . . . 11
2.1.2.2 Active Transponders . . . . . . . . . . . . . . . . . 13
2.2 RFID Interrogator Architectures . . . . . . . . . . . . . . . . . . . 18
2.2.1 Interferometer based Interrogator . . . . . . . . . . . . . . . 19
2.2.2 Ultra-wideband Interrogator . . . . . . . . . . . . . . . . . . 20
2.2.3 Continuous Wave Interrogators . . . . . . . . . . . . . . . . 21
2.3 Coupling Dependent Range and Operating Frequencies . . . . . . . 25
2.4 RFID Ranging Techniques . . . . . . . . . . . . . . . . . . . . . . . 28
2.4.0.1 Received Signal Strength based Ranging . . . . . 28
2.4.0.2 Phase based Ranging . . . . . . . . . . . . . . . . 30
2.4.0.3 Time based Ranging . . . . . . . . . . . . . . . . . 30
2.5 Architecture Selection for Proof of Concept Systems . . . . . . . . 32
2.6 Superregenerative Amplifier (SRA) . . . . . . . . . . . . . . . . . . 35
2.6.1 Fundamentals . . . . . . . . . . . . . . . . . . . . . . . . . . 35
2.6.2 Modes of Operation . . . . . . . . . . . . . . . . . . . . . . 42
2.6.3 Frequency Domain Characteristics . . . . . . . . . . . . . . 45
2.7 Semiconductor Technologies for RFIC Design . . . . . . . . . . . . 48
2.7.1 Silicon Germanium BiCMOS . . . . . . . . . . . . . . . . . 48
2.7.2 Silicon-on-Insulator . . . . . . . . . . . . . . . . . . . . . . . 48
3 24GHz Superregenerative Transponder based Identification and Rang-
ing System 51
3.1 System Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
3.1.1 SRT Identification and Ranging . . . . . . . . . . . . . . . . 51
3.1.2 Power Link Analysis . . . . . . . . . . . . . . . . . . . . . . 55
3.1.3 Non-idealities . . . . . . . . . . . . . . . . . . . . . . . . . . 59
3.1.4 SRA Quench Frequency Shift Keying for data transfer . . . 61
3.1.5 Knowledge Gained . . . . . . . . . . . . . . . . . . . . . . . 63
3.2 RFIC Designs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
3.2.1 Low Power Direct Antenna Drive CMOS SRA IC . . . . . . 66
3.2.1.1 Circuit analysis and design . . . . . . . . . . . . . 66
3.2.1.2 Characterization . . . . . . . . . . . . . . . . . . . 69
3.2.2 Direct Antenna Drive SiGe SRA ICs . . . . . . . . . . . . . 71
3.2.2.1 Stacked Transistor Cross-coupled Quenchable Oscillator
. . . . . . . . . . . . . . . . . . . . . . . . 72
3.2.2.1.1 Resonator . . . . . . . . . . . . . . . . . . 72
3.2.2.1.2 Output Network . . . . . . . . . . . . . . 75
3.2.2.1.3 Stacked Transistor Cross-coupled Pair and
Loop Gain . . . . . . . . . . . . . . . . . 77
3.2.2.2 Quench Waveform Design . . . . . . . . . . . . . . 85
3.2.2.3 Characterization . . . . . . . . . . . . . . . . . . . 89
3.2.3 Antenna Diversity SiGe SRA IC with Integrated Quench
Pulse Shaping . . . . . . . . . . . . . . . . . . . . . . . . . . 91
3.2.3.1 Circuit Analysis and Design . . . . . . . . . . . . 91
3.2.3.1.1 Crosscoupled Pair and Sampling Current 94
3.2.3.1.2 Common Base Input Stage . . . . . . . . 95
3.2.3.1.3 Cascode Output Stage . . . . . . . . . . . 96
3.2.3.1.4 Quench Pulse Shaping Circuit . . . . . . 96
3.2.3.1.5 Power Gain . . . . . . . . . . . . . . . . . 99
3.2.3.2 Characterization . . . . . . . . . . . . . . . . . . . 102
3.2.4 Knowledge Gained . . . . . . . . . . . . . . . . . . . . . . . 103
3.3 Proof of Principle System Implementation . . . . . . . . . . . . . . 106
3.3.1 Superregenerative Transponders . . . . . . . . . . . . . . . 106
3.3.1.1 Bandwidth Enhanced Microstrip Patch Antennas 108
3.3.2 FMCW Radar Interrogator . . . . . . . . . . . . . . . . . . 114
3.3.3 Chirp Z-transform Based Data Analysis . . . . . . . . . . . 116
4 60GHz Single Antenna RFID Interrogator based Identification System 121
4.1 System Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
4.2 RFIC Designs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
4.2.1 Quasi-circulator ICs . . . . . . . . . . . . . . . . . . . . . . 125
4.2.1.1 Transmission Lines based Quasi-Circulator IC . . 126
4.2.1.2 Lumped Elements WPD based Quasi-Circulator . 130
4.2.1.3 Characterization . . . . . . . . . . . . . . . . . . . 134
4.2.1.4 Knowledge Gained . . . . . . . . . . . . . . . . . . 135
4.2.2 Folded Switching Stage Downconversion Mixer IC . . . . . 138
4.2.2.1 FSSDM Circuit Design . . . . . . . . . . . . . . . 138
4.2.2.2 Cascode Transconductance Stage . . . . . . . . . . 138
4.2.2.3 Folded Switching Stage with LC DC Feed . . . . . 142
4.2.2.4 LO Balun . . . . . . . . . . . . . . . . . . . . . . . 145
4.2.2.5 Backgate Tunable IF Stage and Offset Correction 146
4.2.2.6 Voltage Conversion Gain . . . . . . . . . . . . . . 147
4.2.2.7 Characterization . . . . . . . . . . . . . . . . . . . 150
4.2.2.8 Knowledge Gained . . . . . . . . . . . . . . . . . . 151
4.3 Proof of Principle System Implementation . . . . . . . . . . . . . . 154
5 Experimental Tests 157
5.1 24GHz System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157
5.1.1 Ranging Experiments . . . . . . . . . . . . . . . . . . . . . 157
5.1.2 Roll Invariance Experiments . . . . . . . . . . . . . . . . . . 158
5.1.3 Joint Ranging and Data Transfer Experiments . . . . . . . 158
5.2 60GHz System Detection Experiments . . . . . . . . . . . . . . . . 165
6 Summary and Future Work 167
Appendices 171
A Derivation of Parameters for CB Amplifier with Base Feedback Capac-
itance 173
B Definitions 177
C 24GHz Experiment Setups 179
D 60 GHz Experiment Setups 183
References 185
List of Original Publications 203
List of Abbreviations 207
List of Symbols 213
List of Figures 215
List of Tables 223
Curriculum Vitae 22
Direct communication radio Iinterface for new radio multicasting and cooperative positioning
Cotutela: Universidad de defensa UNIVERSITAâ MEDITERRANEA DI REGGIO CALABRIARecently, the popularity of Millimeter Wave (mmWave) wireless networks has increased due to their capability to cope with the escalation of mobile data demands caused by the unprecedented proliferation of smart devices in the fifth-generation (5G). Extremely high frequency or mmWave band is a fundamental pillar in the provision of the expected gigabit data rates. Hence, according to both academic and industrial communities, mmWave technology, e.g., 5G New Radio (NR) and WiGig (60 GHz), is considered as one of the main components of 5G and beyond networks. Particularly, the 3rd Generation Partnership Project (3GPP) provides for the use of licensed mmWave sub-bands for the 5G mmWave cellular networks, whereas IEEE actively explores the unlicensed band at 60 GHz for the next-generation wireless local area networks. In this regard, mmWave has been envisaged as a new technology
layout for real-time heavy-traffic and wearable applications.
This very work is devoted to solving the problem of mmWave band communication system while enhancing its advantages through utilizing the direct communication radio interface for NR multicasting, cooperative positioning, and mission-critical applications. The main contributions presented in this work include: (i) a set of mathematical frameworks and simulation tools to characterize multicast traffic delivery in mmWave directional systems; (ii) sidelink
relaying concept exploitation to deal with the channel condition deterioration of dynamic multicast systems and to ensure mission-critical and ultra-reliable low-latency communications; (iii) cooperative positioning techniques analysis for enhancing cellular positioning accuracy for 5G+ emerging applications that require not only improved communication characteristics but also precise localization.
Our study indicates the need for additional mechanisms/research that can be utilized: (i) to further improve multicasting performance in 5G/6G systems; (ii) to investigate sideline aspects, including, but not limited to, standardization perspective and the next relay selection strategies; and (iii) to design cooperative positioning systems based on Device-to-Device (D2D) technology
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