10 research outputs found
Efficient parallelization of polyphase arbitrary resampling FIR filters for high-speed applications
This article describes a method for increasing the sampling rate of efficient polyphase arbitrary resampling FIR filters. An FPGA proof of concept prototype of this architecture has been implemented in a Xilinx Kintex-7 FPGA which is able to convert the sampling rate of a signal from 500 MHz to 600 MHz. This article compares this new architecture with other best known efficient resampling architectures implemented on the same FPGA. The area usage on the FPGA shows that our proposed implementation is very proficient in high bandwidth applications without requiring significantly more resources on the FPGA. A theoretical calculation of the resampling error introduced on a modulated data stream is provided to evaluate the new architecture against other existing resampling architectures
BASEBAND RADIO MODEM DESIGN USING GRAPHICS PROCESSING UNITS
A modern radio or wireless communications transceiver is programmed via
software and firmware to change its functionalities at the baseband. However, the
actual implementation of the radio circuits relies on dedicated hardware, and the
design and implementation of such devices are time consuming and challenging. Due
to the need for real-time operation, dedicated hardware is preferred in order to meet
stringent requirements on throughput and latency. With increasing need for higher
throughput and shorter latency, while supporting increasing bandwidth across a
fragmented spectrum, dedicated subsystems are developed in order to service individual
frequency bands and specifications. Such a dedicated-hardware-intensive
approach leads to high resource costs, including costs due to multiple instantiations
of mixers, filters, and samplers. Such increases in hardware requirements in turn
increases device size, power consumption, weight, and financial cost.
If it can meet the required real-time constraints, a more flexible and reconfigurable
design approach, such as a software-based solution, is often more desirable
over a dedicated hardware solution. However, significant challenges must be
overcome in order to meet constraints on throughput and latency while servicing
different frequency bands and bandwidths. Graphics processing unit (GPU) technology
provides a promising class of platforms for addressing these challenges. GPUs,
which were originally designed for rendering images and video sequences, have been
adapted as general purpose high-throughput computation engines for a wide variety
of application areas beyond their original target domains. Linear algebra and signal
processing acceleration are examples of such application areas.
In this thesis, we apply GPUs as software-based, baseband radios and demonstrate
novel, software-based implementations of key subsystems in modern wireless
transceivers. In our work, we develop novel implementation techniques that allow
communication system designers to use GPUs as accelerators for baseband processing
functions, including real-time filtering and signal transformations. More
specifically, we apply GPUs to accelerate several computationally-intensive, frontend
radio subsystems, including filtering, signal mixing, sample rate conversion,
and synchronization. These are critical subsystems that must operate in real-time
to reliably receive waveforms.
The contributions of this thesis can be broadly organized into 3 major areas:
(1) channelization, (2) arbitrary resampling, and (3) synchronization.
1. Channelization: a wideband signal is shared between different users and
channels, and a channelizer is used to separate the components of the shared signal
in the different channels. A channelizer is often used as a pre-processing step in
selecting a specific channel-of-interest. A typical channelization process involves signal
conversion, resampling, and filtering to reject adjacent channels. We investigate
GPU acceleration for a particularly efficient form of channelizer called a polyphase
filterbank channelizer, and demonstrate a real-time implementation of our novel
channelizer design.
2. Arbitrary resampling: following a channelization process, a signal is often
resampled to at least twice the data rate in order to further condition the signal.
Since different communication standards require different resampling ratios, it is
desirable for a resampling subsystem to support a variety of different ratios. We
investigate optimized, GPU-based methods for resampling using polyphase filter
structures that are mapped efficiently into GPU hardware. We investigate these
GPU implementation techniques in the context of interpolation (integer-factor increases
in sampling rate), decimation (integer-factor decreases in sampling rate),
and rational resampling. Finally, we demonstrate an efficient implementation of arbitrary
resampling using GPUs. This implementation exploits specialized hardware
units within the GPU to enable efficient and accurate resampling processes involving
arbitrary changes in sample rate.
3. Synchronization: incoming signals in a wireless communications transceiver
must be synchronized in order to recover the transmitted data properly from complex
channel effects such as thermal noise, fading, and multipath propagation. We investigate
timing recovery in GPUs to accelerate the most computationally intensive
part of the synchronization process, and correctly align the incoming data symbols
in the receiver. Furthermore, we implement fully-parallel timing error detection to
accelerate maximum likelihood estimation
Portable Waveform Development for Software Defined Radios
This work focuses on the question: "How can we build waveforms that can be moved from one platform to another?\u27\u27 Therefore an approach based on the Model Driven Architecture was evaluated. Furthermore, a proof of concept is given with the port of a TETRA waveform from a USRP platform to an SFF SDR platform
Applications in Electronics Pervading Industry, Environment and Society
This book features the manuscripts accepted for the Special Issue “Applications in Electronics Pervading Industry, Environment and Society—Sensing Systems and Pervasive Intelligence” of the MDPI journal Sensors. Most of the papers come from a selection of the best papers of the 2019 edition of the “Applications in Electronics Pervading Industry, Environment and Society” (APPLEPIES) Conference, which was held in November 2019. All these papers have been significantly enhanced with novel experimental results. The papers give an overview of the trends in research and development activities concerning the pervasive application of electronics in industry, the environment, and society. The focus of these papers is on cyber physical systems (CPS), with research proposals for new sensor acquisition and ADC (analog to digital converter) methods, high-speed communication systems, cybersecurity, big data management, and data processing including emerging machine learning techniques. Physical implementation aspects are discussed as well as the trade-off found between functional performance and hardware/system costs
Mismatched Processing for Radar Interference Cancellation
Matched processing is a fundamental filtering operation within radar signal processing to estimate scattering in the radar scene based on the transmit signal. Although matched processing maximizes the signal-to-noise ratio (SNR), the filtering operation is ineffective when interference is captured in the receive measurement. Adaptive interference mitigation combined with matched processing has proven to mitigate interference and estimate the radar scene. A known caveat of matched processing is the resulting sidelobes that may mask other scatterers. The sidelobes can be efficiently addressed by windowing but this approach also comes with limited suppression capabilities, loss in resolution, and loss in SNR. The recent emergence of mismatch processing has shown to optimally reduce sidelobes while maintaining nominal resolution and signal estimation performance. Throughout this work, re-iterative minimum-mean square error (RMMSE) adaptive and least-squares (LS) optimal mismatch processing are proposed for enhanced signal estimation in unison with adaptive interference mitigation for various radar applications including random pulse repetition interval (PRI) staggering pulse-Doppler radar, airborne ground moving target indication, and radar & communication spectrum sharing. Mismatch processing and adaptive interference cancellation each can be computationally complex for practical implementation. Sub-optimal RMMSE and LS approaches are also introduced to address computational limitations. The efficacy of these algorithms is presented using various high-fidelity Monte Carlo simulations and open-air experimental datasets
Abstracts on Radio Direction Finding (1899 - 1995)
The files on this record represent the various databases that originally composed the CD-ROM issue of "Abstracts on Radio Direction Finding" database, which is now part of the Dudley Knox Library's Abstracts and Selected Full Text Documents on Radio Direction Finding (1899 - 1995) Collection. (See Calhoun record https://calhoun.nps.edu/handle/10945/57364 for further information on this collection and the bibliography).
Due to issues of technological obsolescence preventing current and future audiences from accessing the bibliography, DKL exported and converted into the three files on this record the various databases contained in the CD-ROM.
The contents of these files are:
1) RDFA_CompleteBibliography_xls.zip [RDFA_CompleteBibliography.xls: Metadata for the complete bibliography, in Excel 97-2003 Workbook format; RDFA_Glossary.xls: Glossary of terms, in Excel 97-2003 Workbookformat; RDFA_Biographies.xls: Biographies of leading figures, in Excel 97-2003 Workbook format];
2) RDFA_CompleteBibliography_csv.zip [RDFA_CompleteBibliography.TXT: Metadata for the complete bibliography, in CSV format; RDFA_Glossary.TXT: Glossary of terms, in CSV format; RDFA_Biographies.TXT: Biographies of leading figures, in CSV format];
3) RDFA_CompleteBibliography.pdf: A human readable display of the bibliographic data, as a means of double-checking any possible deviations due to conversion