85 research outputs found

    Linking Real Time and Location in Scheduling Demand-Responsive Transit

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    The role of rural demand-responsive transit is changing, and with that change is coming an increasing need for technology. As long as rural transit was limited to a type of social service transportation for a specific set of clients who primarily traveled in groups to common meal sites, work centers for the disabled, or clinics in larger communities, a preset calendar augmented by notes on a yellow legal pad was sufficient to develop schedules. Any individual trips were arranged at least 24 to 48 hours ahead of time and were carefully scheduled the night before in half-hour or twenty-minute windows by a dispatcher who knew every lane in the service area. Since it took hours to build the schedule, any last-minute changes could wreak havoc with the plans and raise the stress level in the dispatch office. Nevertheless, given these parameters, a manual scheduling system worked for a small demand-responsive operation

    Design and implementation of an SDR-based multi-frequency ground-based SAR system

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    Synthetic Aperture Radar (SAR) has proven a valuable tool in the monitoring of the Earth, either at a global or local scales. SAR is a coherent radar system able to image extended areas with high resolution, and finds applications in many areas such as forestry, agriculture, mining, structure inspection or security operations. Although space-borne SAR systems can image extended areas, their main limitation is the long revisit times, which are not suitable for applications where the target experiments rapid changes, in the scale of minutes to few days. GBSAR systems have proven useful to fill this revisit time gap by imaging relatively small areas continuously, with extensions usually smaller than a few square kilometers. Ground Based SAR (GBSAR) systems have been used extensively for the monitoring of slope instability, and are a common tool in the mining sector. The development of the GBSAR is relatively recent, and various developments have taken place since the 2000s, transitioning from the usage of Vector Network Analyzers (VNAs) to custom radar cores tailored for this application. This transition is accompanied by a reduction in cost, but at the same time is accompanied by a loss of operational flexibility. Specifically, most GBSAR sensors now operate at a single frequency, losing the value of the multi-band operation that VNAs provided. This work is motivated by the idea that it is worth to use the value of multi-frequency GBSAR measurements, while maintaining a limited system cost. In order to implement a GBSAR with these characteristics, it is realized that Software Defined Radio (SDR) devices are a good option for fast and flexible implementation of broadband transceivers. This thesis details the design and implementation process of an SDR-based Frequency Modulated Continuous Wave (FMCW) GBSAR system from the ground up, presenting the main issues related with the usage of the most common SDR analog architecture, the Zero-IF transceiver. The main problem is determined to be the behavior of spurs related to IQ imbalances of the analog transceiver with the FMCW demodulation process. Two effective techniques to overcome these issues, the Super Spatial Variant Apodization (SSVA) and the Short Time Fourier Transform (STFT) signal reconstruction techniques, are implemented and tested. The thesis also deals with the digital implementation of the signal generator and digital receiver, which are implemented on top of an RF Network-on-Chip (RFNoC) architecture in the SDR Field Programmable Gate Array (FPGA). Another important aspect of this work is the development of an radiofrequency front-end that extends the capabilities of the SDR, implementing filtering, amplification, leakage mitigation and up-conversion to X-band. Finally, a set of test campaigns is described, in which the operation of the system is verified and the value of multi-frequency GBSAR observations is shown.El radar d'obertura sintètica (SAR) ha demostrat ser una eina valuosa en el monitoratge de la Terra, sigui a escala global o local. El SAR és un sistema de radar coherent capaç d’obtenir imatges de zones extenses amb alta resolució i té aplicacions en moltes àrees com la silvicultura, l’agricultura, la mineria, la inspecció d’estructures o les operacions de seguretat. Tot i que els sistemes SAR embarcats en plataformes orbitals poden obtenir imatges d'àrees extenses, la seva principal limitació és el temps de revisita, que no són adequats per a aplicacions on l'objectiu experimenta canvis ràpids, en una escala de minuts a pocs dies. Els sistemes GBSAR han demostrat ser útils per omplir aquesta bretxa de temps, obtenint imatges d'àrees relativament petites de manera contínua, amb extensions generalment inferiors a uns pocs quilòmetres quadrats. Els sistemes SAR terrestres (GBSAR) s’han utilitzat àmpliament per al control de la inestabilitat de talussos i esllavissades i són una eina comuna al sector miner. El desenvolupament del GBSAR és relativament recent i s’han produït diversos desenvolupaments des de la dècada de 2000, passant de l’ús d’analitzadors de xarxes vectorials (VNA) a nuclis de radar personalitzats i adaptats a aquesta aplicació. Aquesta transició s’acompanya d’una reducció del cost, però al mateix temps d’una pèrdua de flexibilitat operativa. Concretament, la majoria dels sensors GBSAR funcionen a una única freqüència, perdent el valor de l’operació en múltiples bandes que proporcionaven els VNA. Aquesta tesi està motivada per la idea de recuperar el valor de les mesures GBSAR multifreqüència, mantenint un cost del sistema limitat. Per tal d’implementar un GBSAR amb aquestes característiques, s’adona que els dispositius de ràdio definida per software (SDR) són una bona opció per a la implementació ràpida i flexible dels transceptors de banda ampla. Aquesta tesi detalla el procés de disseny i implementació d’un sistema GBSAR d’ona contínua modulada en freqüència (FMCW) basat en la tecnologia SDR, presentant els principals problemes relacionats amb l’ús de l’arquitectura analògica de SDR més comuna, el transceptor Zero-IF. Es determina que el problema principal és el comportament dels espuris relacionats amb el balanç de les cadenes de fase i quadratura del transceptor analògic amb el procés de desmodulació FMCW. S’implementen i comproven dues tècniques efectives per minimitzar aquests problemes basades en la reconstrucció de la senyal contaminada per espuris: la tècnica anomenada Super Spatial Variant Apodization (SSVA) i una tècnica basada en la transformada de Fourier amb finestra (STFT). La tesi també tracta la implementació digital del generador de senyal i del receptor digital, que s’implementen sobre una arquitectura RF Network-on-Chip (RFNoC). Un altre aspecte important d’aquesta tesi és el desenvolupament d’un front-end de radiofreqüència que amplia les capacitats de la SDR, implementant filtratge, amplificació, millora de l'aïllament entre transmissió i recepció i conversió a banda X. Finalment, es descriu un conjunt de campanyes de prova en què es verifica el funcionament del sistema i es mostra el valor de les observacions GBSAR multifreqüència

    Reconfigurable Receiver Front-Ends for Advanced Telecommunication Technologies

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    The exponential growth of converging technologies, including augmented reality, autonomous vehicles, machine-to-machine and machine-to-human interactions, biomedical and environmental sensory systems, and artificial intelligence, is driving the need for robust infrastructural systems capable of handling vast data volumes between end users and service providers. This demand has prompted a significant evolution in wireless communication, with 5G and subsequent generations requiring exponentially improved spectral and energy efficiency compared to their predecessors. Achieving this entails intricate strategies such as advanced digital modulations, broader channel bandwidths, complex spectrum sharing, and carrier aggregation scenarios. A particularly challenging aspect arises in the form of non-contiguous aggregation of up to six carrier components across the frequency range 1 (FR1). This necessitates receiver front-ends to effectively reject out-of-band (OOB) interferences while maintaining high-performance in-band (IB) operation. Reconfigurability becomes pivotal in such dynamic environments, where frequency resource allocation, signal strength, and interference levels continuously change. Software-defined radios (SDRs) and cognitive radios (CRs) emerge as solutions, with direct RF-sampling receivers offering a suitable architecture in which the frequency translation is entirely performed in digital domain to avoid analog mixing issues. Moreover, direct RF- sampling receivers facilitate spectrum observation, which is crucial to identify free zones, and detect interferences. Acoustic and distributed filters offer impressive dynamic range and sharp roll off characteristics, but their bulkiness and lack of electronic adjustment capabilities limit their practicality. Active filters, on the other hand, present opportunities for integration in advanced CMOS technology, addressing size constraints and providing versatile programmability. However, concerns about power consumption, noise generation, and linearity in active filters require careful consideration.This thesis primarily focuses on the design and implementation of a low-voltage, low-power RFFE tailored for direct sampling receivers in 5G FR1 applications. The RFFE consists of a balun low-noise amplifier (LNA), a Q-enhanced filter, and a programmable gain amplifier (PGA). The balun-LNA employs noise cancellation, current reuse, and gm boosting for wideband gain and input impedance matching. Leveraging FD-SOI technology allows for programmable gain and linearity via body biasing. The LNA's operational state ranges between high-performance and high-tolerance modes, which are apt for sensitivityand blocking tests, respectively. The Q-enhanced filter adopts noise-cancelling, current-reuse, and programmable Gm-cells to realize a fourth-order response using two resonators. The fourth-order filter response is achieved by subtracting the individual response of these resonators. Compared to cascaded and magnetically coupled fourth-order filters, this technique maintains the large dynamic range of second-order resonators. Fabricated in 22-nm FD-SOI technology, the RFFE achieves 1%-40% fractional bandwidth (FBW) adjustability from 1.7 GHz to 6.4 GHz, 4.6 dB noise figure (NF) and an OOB third-order intermodulation intercept point (IIP3) of 22 dBm. Furthermore, concerning the implementation uncertainties and potential variations of temperature and supply voltage, design margins have been considered and a hybrid calibration scheme is introduced. A combination of on-chip and off-chip calibration based on noise response is employed to effectively adjust the quality factors, Gm-cells, and resonance frequencies, ensuring desired bandpass response. To optimize and accelerate the calibration process, a reinforcement learning (RL) agent is used.Anticipating future trends, the concept of the Q-enhanced filter extends to a multiple-mode filter for 6G upper mid-band applications. Covering the frequency range from 8 to 20 GHz, this RFFE can be configured as a fourth-order dual-band filter, two bandpass filters (BPFs) with an OOB notch, or a BPF with an IB notch. In cognitive radios, the filter’s transmission zeros can be positioned with respect to the carrier frequencies of interfering signals to yield over 50 dB blocker rejection

    Low-frequency Antennas, Transparent Ground Planes, and Transponders for Communication Enhancement in Unfavorable Environments

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    The communication environment has a major influence on the performance of wireless networks. Unlike antennas, receivers, processors, and other components of a typical wireless system, the designer has almost no control over the communication channel. Therefore, it is imminent that the adverse effects of the communication channel such as path-loss, multi-path, lack of a clear line of sight, and interference are among the most limiting factors in designing and operating wireless networks. Recent investments in infrastructures such as cell-phone towers, communication satellites, routers, and networking devices have been aimed at reducing the aforementioned adverse effects. However, wireless ad hoc networks (WANET) cannot rely on pre-existing infrastructures such as access points or routers. In this thesis, a number of solutions are presented to enhance communication and navigation in harsh environments. 1) At lower frequencies, the defects of the communication channel are less prominent, which has led militaries to use UHF and VHF frequency bands for communication. A number of optically transparent UHF antennas are developed and embedded in the windows of military vehicles to reduce their visual signature. 2) Direction finding at low frequencies using baseline method results in an exorbitantly large array of sensors. However, a vector sensor consisting of three orthogonal two-port loop antennas can be used. A simple and accurate circuit model for the two-port loop antenna is developed for the first time that can be used for direction of arrival estimation over a wide range of frequencies and angles. 3) Using a conventional radio repeater with ad-hoc systems requires a communication protocol and decreases the throughput by a factor of two for every repeater in the chain. A full-duplex repeater, capable of simultaneously transmitting and receiving at the same frequency, is developed for the 2.4 GHz ISM band.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/143898/1/manikafa_1.pd

    Learning and identification of wireless network internode dynamics using software defined radio

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    The recently developed paradigm of cognitive radio wireless devices has been developed with the goal of achieving more customizable and efficient spectrum utilization of commonly used wireless frequency bands. The primary focus of such spectrum utilization approaches has been to discern occupancies and vacancies over portions of the wireless spectrum without necessarily identifying how specific radio frequency (RF) devices contribute to the temporal dynamics of these occupancy patterns within the spectrum. The aim of this thesis is to utilize a hidden semi-Markov model (HSMM) statistical analysis to infer the individual occupancy patterns of specific users from wireless RF observation traces. It is proposed that the HSMM approach for RF device characterization over time may act as a first step towards performing a more complete characterization of the RF spectrum in which the inferred traffic patterns may demonstrate the coexistence of multiple networks, the specific devices comprising each distinct network, and the level of mutual interference between the component networks resultant from such coexistence. The first main portion of this thesis is the development of a Bayesian learning framework for HSMM characterization of the wireless RF observations, with occupancy periods and each individual RF device being classified as distinct states in the HSMM. The traditional HSMM approach is supplemented with the concept of the hierarchical Dirichlet random process to achieve a minimal number of states needed to effectively capture each distinct device, without the need for strong a priori assumptions regarding the number of devices seen in the RF trace prior to computational analysis. The second portion of the thesis utilizes user-programmed cognitive radios to construct a real-time software-defined RF network environment emulation testbed to assess the accuracy of the HSMM characterization. Finally, the HSMM algorithm is tested on wireless devices operating under an actual implementation of the ubiquitous IEEE 802.11 wireless standard

    Suitability of a commercial software defined radio system for passive coherent location

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    Includes abstract. Includes bibliographical references (leaves 98-99)

    Conceptual design study: Forest Fire Advanced System Technology (FFAST)

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    An integrated forest fire detection and mapping system that will be based upon technology available in the 1990s was defined. Uncertainties in emerging and advanced technologies related to the conceptual design were identified and recommended for inclusion as preferred system components. System component technologies identified for an end-to-end system include thermal infrared, linear array detectors, automatic georeferencing and signal processing, geosynchronous satellite communication links, and advanced data integration and display. Potential system configuration options were developed and examined for possible inclusion in the preferred system configuration. The preferred system configuration will provide increased performance and be cost effective over the system currently in use. Forest fire management user requirements and the system component emerging technologies were the basis for the system configuration design. A preferred system configuration was defined that warrants continued refinement and development, examined economic aspects of the current and preferred system, and provided preliminary cost estimates for follow-on system prototype development

    Sub-sampling Receivers for Wireless Communications

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    Nonlinear Distortion in Wideband Radio Receivers and Analog-to-Digital Converters: Modeling and Digital Suppression

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    Emerging wireless communications systems aim to flexible and efficient usage of radio spectrum in order to increase data rates. The ultimate goal in this field is a cognitive radio. It employs spectrum sensing in order to locate spatially and temporally vacant spectrum chunks that can be used for communications. In order to achieve that, flexible and reconfigurable transceivers are needed. A software-defined radio can provide these features by having a highly-integrated wideband transceiver with minimum analog components and mostly relying on digital signal processing. This is also desired from size, cost, and power consumption point of view. However, several challenges arise, from which dynamic range is one of the most important. This is especially true on receiver side where several signals can be received simultaneously through a single receiver chain. In extreme cases the weakest signal can be almost 100 dB weaker than the strongest one. Due to the limited dynamic range of the receiver, the strongest signals may cause nonlinear distortion which deteriorates spectrum sensing capabilities and also reception of the weakest signals. The nonlinearities are stemming from the analog receiver components and also from analog-to-digital converters (ADCs). This is a performance bottleneck in many wideband communications and also radar receivers. The dynamic range challenges are already encountered in current devices, such as in wideband multi-operator receiver scenarios in mobile networks, and the challenges will have even more essential role in the future.This thesis focuses on aforementioned receiver scenarios and contributes to modeling and digital suppression of nonlinear distortion. A behavioral model for direct-conversion receiver nonlinearities is derived and it jointly takes into account RF, mixer, and baseband nonlinearities together with I/Q imbalance. The model is then exploited in suppression of receiver nonlinearities. The considered method is based on adaptive digital post-processing and does not require any analog hardware modification. It is able to extract all the necessary information directly from the received waveform in order to suppress the nonlinear distortion caused by the strongest blocker signals inside the reception band.In addition, the nonlinearities of ADCs are considered. Even if the dynamic range of the analog receiver components is not limiting the performance, ADCs may cause considerable amount of nonlinear distortion. It can originate, e.g., from undeliberate variations of quantization levels. Furthermore, the received waveform may exceed the nominal voltage range of the ADC due to signal power variations. This causes unintentional signal clipping which creates severe nonlinear distortion. In this thesis, a Fourier series based model is derived for the signal clipping caused by ADCs. Furthermore, four different methods are considered for suppressing ADC nonlinearities, especially unintentional signal clipping. The methods exploit polynomial modeling, interpolation, or symbol decisions for suppressing the distortion. The common factor is that all the methods are based on digital post-processing and are able to continuously adapt to variations in the received waveform and in the receiver itself. This is a very important aspect in wideband receivers, especially in cognitive radios, when the flexibility and state-of-the-art performance is required
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