Practical Non-Uniform Channelization for Multistandard Base Stations

A Multistandard software-defined radio base station must perform non-uniform channelization of multiplexed frequency bands. Non-uniform channelization accounts for a significant portion of the digital signal processing workload in the base station receiver and can be difficult to realize in a physical implementation. In non-uniform channelization methods based on generalized DFT filter banks, large prototype filter orders are a significant issue for implementation. In this paper, a multistage filter design is applied to two different non-uniform generalized DFT-based channelizers in order to reduce their filter orders. To evaluate the approach, a TETRA and TEDS base station is used. Experimental results show that the new multistage design reduces both the number of coefficients and operations and leads to a more feasible design and practical physical implementation

Practical Non-Uniform Channelization for Multistandard Base Stations

A Multistandard software-defined radio base station must perform non-uniform channelization of multiplexed frequency bands. Non-uniform channelization accounts for a significant portion of the digital signal processing workload in the base station receiver and can be difficult to realize in a physical implementation. In non-uniform channelization methods based on generalized DFT filter banks, large prototype filter orders are a significant issue for implementation. In this paper, a multistage filter design is applied to two different non-uniform generalized DFT-based channelizers in order to reduce their filter orders. To evaluate the approach, a TETRA and TEDS base station is used. Experimental results show that the new multistage design reduces both the number of coefficients and operations and leads to a more feasible design and practical physical implementation

Channelization for Multi-Standard Software-Defined Radio Base Stations

As the number of radio standards increase and spectrum resources come under more pressure, it becomes ever less efficient to reserve bands of spectrum for exclusive use by a single radio standard. Therefore, this work focuses on channelization structures compatible with spectrum sharing among multiple wireless standards and dynamic spectrum allocation in particular. A channelizer extracts independent communication channels from a wideband signal, and is one of the most computationally expensive components in a communications receiver. This work specifically focuses on non-uniform channelizers suitable for multi-standard Software-Defined Radio (SDR) base stations in general and public mobile radio base stations in particular. A comprehensive evaluation of non-uniform channelizers (existing and developed during the course of this work) shows that parallel and recombined variants of the Generalised Discrete Fourier Transform Modulated Filter Bank (GDFT-FB) represent the best trade-off between computational load and flexibility for dynamic spectrum allocation. Nevertheless, for base station applications (with many channels) very high filter orders may be required, making the channelizers difficult to physically implement. To mitigate this problem, multi-stage filtering techniques are applied to the GDFT-FB. It is shown that these multi-stage designs can significantly reduce the filter orders and number of operations required by the GDFT-FB. An alternative approach, applying frequency response masking techniques to the GDFT-FB prototype filter design, leads to even bigger reductions in the number of coefficients, but computational load is only reduced for oversampled configurations and then not as much as for the multi-stage designs. Both techniques render the implementation of GDFT-FB based non-uniform channelizers more practical. Finally, channelization solutions for some real-world spectrum sharing use cases are developed before some final physical implementation issues are considered

Non-Uniform Channelization Methods for Next Generation SDR PMR Base Stations

Channelization in multi-standard Software-Defined Radio base stations presents a significant challenge. In this paper, two different channelization structures designed for a multi-standard SDR base station are studied. As a basis for comparing their computational efficiency and reconfigurability, both are applied to a specific case study of a TETRA and TEDS standards base station. Uniform narrow band spectrum division followed by channel recombination demonstrates greater flexibility than a non-uniform parallel spectrum division alternative. However, computational advantages between both structures depend on the channel allocation patterns considered

Real-Time Localization Using Software Defined Radio

Service providers make use of cost-effective wireless solutions to identify, localize, and possibly track users using their carried MDs to support added services, such as geo-advertisement, security, and management. Indoor and outdoor hotspot areas play a significant role for such services. However, GPS does not work in many of these areas. To solve this problem, service providers leverage available indoor radio technologies, such as WiFi, GSM, and LTE, to identify and localize users. We focus our research on passive services provided by third parties, which are responsible for (i) data acquisition and (ii) processing, and network-based services, where (i) and (ii) are done inside the serving network. For better understanding of parameters that affect indoor localization, we investigate several factors that affect indoor signal propagation for both Bluetooth and WiFi technologies. For GSM-based passive services, we developed first a data acquisition module: a GSM receiver that can overhear GSM uplink messages transmitted by MDs while being invisible. A set of optimizations were made for the receiver components to support wideband capturing of the GSM spectrum while operating in real-time. Processing the wide-spectrum of the GSM is possible using a proposed distributed processing approach over an IP network. Then, to overcome the lack of information about tracked devices’ radio settings, we developed two novel localization algorithms that rely on proximity-based solutions to estimate in real environments devices’ locations. Given the challenging indoor environment on radio signals, such as NLOS reception and multipath propagation, we developed an original algorithm to detect and remove contaminated radio signals before being fed to the localization algorithm. To improve the localization algorithm, we extended our work with a hybrid based approach that uses both WiFi and GSM interfaces to localize users. For network-based services, we used a software implementation of a LTE base station to develop our algorithms, which characterize the indoor environment before applying the localization algorithm. Experiments were conducted without any special hardware, any prior knowledge of the indoor layout or any offline calibration of the system

Runtime Adaptation in Embedded Computing Systems using Markov Decision Processes

During the design and implementation of embedded computing systems (ECSs), engineers must make assumptions on how the system will be used after being built and deployed. Traditionally, these important decisions were made at design time for a fleet of ECSs prior to deployment. In contrast to this approach, this research explores and develops techniques to enable adaptation of ECSs at runtime to the environments and applications in which they operate. Adaptation is enabled such that the usage assumptions and performance optimization decisions can be made autonomously at runtime in the deployed system. This thesis utilizes Markov Decision Processes (MDPs), a powerful and well established mathematical framework used for decision making under uncertainty, to control computing systems at runtime. The resulting control is performed in ways that are more dynamic, robust and adaptable than alternatives in many scenarios. The techniques developed in this thesis are first applied to a reconfigurable embedded digital signal processing system. In this effort, several challenges are encountered and resolved using novel approaches. Through extensive simulations and a prototype implementation, the robustness of the adaptation is demonstrated in comparison with the prior state-of-the-art. The thesis continues by developing an efficient algorithm for conversion of MDP models to actionable control policies - a required step known as solving the MDP. The solver algorithm is developed in the context of ECSs that contain general purpose embedded GPUs (graphics processing units). The novel solver algorithm, Sparse Parallel Value Iteration (SPVI), makes use of the parallel processing capabilities provided by such GPUs, and also exploits the sparsity that typically exists in MDPs when used to model and control ECSs. To extend the applicability of the runtime adaptation techniques to smaller and more strictly resource constrained ECSs, another solver - Sparse Value Iteration (SVI) is developed for use on microcontrollers. The method is explored in a detailed case study involving a cellular (LTE-M) connected sensor that adapts to varying communications profiles. The case study reveals that the proposed adaptation framework outperforms a competing approach based on Reinforcement Learning (RL) in terms of robustness and adaptation, while consuming comparable resource requirements. Finally, the thesis concludes by analyzing the various logistical challenges that exist when deploying MDPs on ECSs. In response to these challenges, the thesis contributes an open source software package to the engineering community. The package contains libraries of MDP solvers, parsers, datasets and reference solutions, which provide a comprehensive infrastructure for exploring the trade-offs among existing embedded MDP techniques, and experimenting with novel approaches

Efficient Wideband Channelizer for Software Radio Systems Using Modulated PR Filterbanks

An efficient method is proposed for channelizing frequency division multiplexed (FDM) channels in wideband software radio (SWR) received signals that do not satisfy the conditions required for polyphase decomposition of the discrete filterbank (DFB) channelizer. The proposed method, which uses modulated perfect reconstruction (PR) filterbanks, requires fewer computations than DFBs for channelizing wideband signals that are composed of FDM channels of nonequal bandwidths, especially when a large number of channels are extracted. The proposed channelizer, if applied in the reverse direction, can be used to synthesize a set of channels with nonequal bandwidths into a single wideband signal in SWR transmitters. A method is also proposed for efficiently designing the modulated PR filterbanks, which have a large number of subchannels and prototype filters with high stopband attenuations that are used in the proposed channelizer. The computational complexity of the proposed channelizer is compared with the complexity of the DFB channelizer for channelizing the wideband and high-dynamic-range signals that are typical of SWR systems, and simulation results of the proposed channelization method are discussed

Highly Multiplexed Superconducting Detectors and Readout Electronics for Balloon-Borne and Ground-Based Far-Infrared Imaging and Polarimetry

abstract: This dissertation details the development of an open source, frequency domain multiplexed (FDM) readout for large-format arrays of superconducting lumped-element kinetic inductance detectors (LEKIDs). The system architecture is designed to meet the requirements of current and next generation balloon-borne and ground-based submillimeter (sub-mm), far-infrared (FIR) and millimeter-wave (mm-wave) astronomical cameras, whose science goals will soon drive the pixel counts of sub-mm detector arrays from the kilopixel to the megapixel regime. The in-flight performance of the readout system was verified during the summer, 2018 flight of ASI's OLIMPO balloon-borne telescope, from Svalbard, Norway. This was the first flight for both LEKID detectors and their associated readout electronics. In winter 2019/2020, the system will fly on NASA's long-duration Balloon Borne Large Aperture Submillimeter Telescope (BLAST-TNG), a sub-mm polarimeter which will map the polarized thermal emission from cosmic dust at 250, 350 and 500 microns (spatial resolution of 30", 41" and 59"). It is also a core system in several upcoming ground based mm-wave instruments which will soon observe at the 50 m Large Millimeter Telescope (e.g., TolTEC, SuperSpec, MUSCAT), at Sierra Negra, Mexico. The design and verification of the FPGA firmware, software and electronics which make up the system are described in detail. Primary system requirements are derived from the science objectives of BLAST-TNG, and discussed in the context of relevant size, weight, power and cost (SWaP-C) considerations for balloon platforms. The system was used to characterize the instrumental performance of the BLAST-TNG receiver and detector arrays in the lead-up to the 2019/2020 flight attempt from McMurdo Station, Antarctica. The results of this characterization are interpreted by applying a parametric software model of a LEKID detector to the measured data in order to estimate important system parameters, including the optical efficiency, optical passbands and sensitivity. The role that magnetic fields (B-fields) play in shaping structures on various scales in the interstellar medium is one of the central areas of research which is carried out by sub-mm/FIR observatories. The Davis-Chandrasekhar-Fermi Method (DCFM) is applied to a BLASTPol 2012 map (smoothed to 5') of the inner ~1.25 deg2 of the Carina Nebula Complex (CNC, NGC 3372) in order to estimate the strength of the B-field in the plane-of-the-sky (B-pos). The resulting map contains estimates of B-pos along several thousand sightlines through the CNC. This data analysis pipeline will be used to process maps of the CNC and other science targets which will be produced during the upcoming BLAST-TNG flight. A target selection survey of five nearby external galaxies which will be mapped during the flight is also presented.Dissertation/ThesisDoctoral Dissertation Astrophysics 201

Biomimetic Based Applications

The interaction between cells, tissues and biomaterial surfaces are the highlights of the book "Biomimetic Based Applications". In this regard the effect of nanostructures and nanotopographies and their effect on the development of a new generation of biomaterials including advanced multifunctional scaffolds for tissue engineering are discussed. The 2 volumes contain articles that cover a wide spectrum of subject matter such as different aspects of the development of scaffolds and coatings with enhanced performance and bioactivity, including investigations of material surface-cell interactions