225 research outputs found

    Spectral estimation using nonuniform sampling

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    Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.Includes bibliographical references (leaves 98-99).by James Martin Nohrden.M.S

    Channel estimation techniques for filter bank multicarrier based transceivers for next generation of wireless networks

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    A dissertation submitted to Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfillment of the requirements for the degree of Master of Science in Engineering (Electrical and Information Engineering), August 2017The fourth generation (4G) of wireless communication system is designed based on the principles of cyclic prefix orthogonal frequency division multiplexing (CP-OFDM) where the cyclic prefix (CP) is used to combat inter-symbol interference (ISI) and inter-carrier interference (ICI) in order to achieve higher data rates in comparison to the previous generations of wireless networks. Various filter bank multicarrier systems have been considered as potential waveforms for the fast emerging next generation (xG) of wireless networks (especially the fifth generation (5G) networks). Some examples of the considered waveforms are orthogonal frequency division multiplexing with offset quadrature amplitude modulation based filter bank, universal filtered multicarrier (UFMC), bi-orthogonal frequency division multiplexing (BFDM) and generalized frequency division multiplexing (GFDM). In perfect reconstruction (PR) or near perfect reconstruction (NPR) filter bank designs, these aforementioned FBMC waveforms adopt the use of well-designed prototype filters (which are used for designing the synthesis and analysis filter banks) so as to either replace or minimize the CP usage of the 4G networks in order to provide higher spectral efficiencies for the overall increment in data rates. The accurate designing of the FIR low-pass prototype filter in NPR filter banks results in minimal signal distortions thus, making the analysis filter bank a time-reversed version of the corresponding synthesis filter bank. However, in non-perfect reconstruction (Non-PR) the analysis filter bank is not directly a time-reversed version of the corresponding synthesis filter bank as the prototype filter impulse response for this system is formulated (in this dissertation) by the introduction of randomly generated errors. Hence, aliasing and amplitude distortions are more prominent for Non-PR. Channel estimation (CE) is used to predict the behaviour of the frequency selective channel and is usually adopted to ensure excellent reconstruction of the transmitted symbols. These techniques can be broadly classified as pilot based, semi-blind and blind channel estimation schemes. In this dissertation, two linear pilot based CE techniques namely the least square (LS) and linear minimum mean square error (LMMSE), and three adaptive channel estimation schemes namely least mean square (LMS), normalized least mean square (NLMS) and recursive least square (RLS) are presented, analyzed and documented. These are implemented while exploiting the near orthogonality properties of offset quadrature amplitude modulation (OQAM) to mitigate the effects of interference for two filter bank waveforms (i.e. OFDM/OQAM and GFDM/OQAM) for the next generation of wireless networks assuming conditions of both NPR and Non-PR in slow and fast frequency selective Rayleigh fading channel. Results obtained from the computer simulations carried out showed that the channel estimation schemes performed better in an NPR filter bank system as compared with Non-PR filter banks. The low performance of Non-PR system is due to the amplitude distortion and aliasing introduced from the random errors generated in the system that is used to design its prototype filters. It can be concluded that RLS, NLMS, LMS, LMMSE and LS channel estimation schemes offered the best normalized mean square error (NMSE) and bit error rate (BER) performances (in decreasing order) for both waveforms assuming both NPR and Non-PR filter banks. Keywords: Channel estimation, Filter bank, OFDM/OQAM, GFDM/OQAM, NPR, Non-PR, 5G, Frequency selective channel.CK201

    Frequency diversity wideband digital receiver and signal processor for solid-state dual-polarimetric weather radars

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    2012 Summer.Includes bibliographical references.The recent spate in the use of solid-state transmitters for weather radar systems has unexceptionably revolutionized the research in meteorology. The solid-state transmitters allow transmission of low peak powers without losing the radar range resolution by allowing the use of pulse compression waveforms. In this research, a novel frequency-diversity wideband waveform is proposed and realized to extenuate the low sensitivity of solid-state radars and mitigate the blind range problem tied with the longer pulse compression waveforms. The latest developments in the computing landscape have permitted the design of wideband digital receivers which can process this novel waveform on Field Programmable Gate Array (FPGA) chips. In terms of signal processing, wideband systems are generally characterized by the fact that the bandwidth of the signal of interest is comparable to the sampled bandwidth; that is, a band of frequencies must be selected and filtered out from a comparable spectral window in which the signal might occur. The development of such a wideband digital receiver opens a window for exciting research opportunities for improved estimation of precipitation measurements for higher frequency systems such as X, Ku and Ka bands, satellite-borne radars and other solid-state ground-based radars. This research describes various unique challenges associated with the design of a multi-channel wideband receiver. The receiver consists of twelve channels which simultaneously downconvert and filter the digitized intermediate-frequency (IF) signal for radar data processing. The product processing for the multi-channel digital receiver mandates a software and network architecture which provides for generating and archiving a single meteorological product profile culled from multi-pulse profiles at an increased data date. The multi-channel digital receiver also continuously samples the transmit pulse for calibration of radar receiver gain and transmit power. The multi-channel digital receiver has been successfully deployed as a key component in the recently developed National Aeronautical and Space Administration (NASA) Global Precipitation Measurement (GPM) Dual-Frequency Dual-Polarization Doppler Radar (D3R). The D3R is the principal ground validation instrument for the precipitation measurements of the Dual Precipitation Radar (DPR) onboard the GPM Core Observatory satellite scheduled for launch in 2014. The D3R system employs two broadly separated frequencies at Ku- and Ka-bands that together make measurements for precipitation types which need higher sensitivity such as light rain, drizzle and snow. This research describes unique design space to configure the digital receiver for D3R at several processing levels. At length, this research presents analysis and results obtained by employing the multi-carrier waveforms for D3R during the 2012 GPM Cold-Season Precipitation Experiment (GCPEx) campaign in Canada

    Lossless and low-cost integer-based lifting wavelet transform

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    Discrete wavelet transform (DWT) is a powerful tool for analyzing real-time signals, including aperiodic, irregular, noisy, and transient data, because of its capability to explore signals in both the frequency- and time-domain in different resolutions. For this reason, they are used extensively in a wide number of applications in image and signal processing. Despite the wide usage, the implementation of the wavelet transform is usually lossy or computationally complex, and it requires expensive hardware. However, in many applications, such as medical diagnosis, reversible data-hiding, and critical satellite data, lossless implementation of the wavelet transform is desirable. It is also important to have more hardware-friendly implementations due to its recent inclusion in signal processing modules in system-on-chips (SoCs). To address the need, this research work provides a generalized implementation of a wavelet transform using an integer-based lifting method to produce lossless and low-cost architecture while maintaining the performance close to the original wavelets. In order to achieve a general implementation method for all orthogonal and biorthogonal wavelets, the Daubechies wavelet family has been utilized at first since it is one of the most widely used wavelets and based on a systematic method of construction of compact support orthogonal wavelets. Though the first two phases of this work are for Daubechies wavelets, they can be generalized in order to apply to other wavelets as well. Subsequently, some techniques used in the primary works have been adopted and the critical issues for achieving general lossless implementation have solved to propose a general lossless method. The research work presented here can be divided into several phases. In the first phase, low-cost architectures of the Daubechies-4 (D4) and Daubechies-6 (D6) wavelets have been derived by applying the integer-polynomial mapping. A lifting architecture has been used which reduces the cost by a half compared to the conventional convolution-based approach. The application of integer-polynomial mapping (IPM) of the polynomial filter coefficient with a floating-point value further decreases the complexity and reduces the loss in signal reconstruction. Also, the “resource sharing” between lifting steps results in a further reduction in implementation costs and near-lossless data reconstruction. In the second phase, a completely lossless or error-free architecture has been proposed for the Daubechies-8 (D8) wavelet. Several lifting variants have been derived for the same wavelet, the integer mapping has been applied, and the best variant is determined in terms of performance, using entropy and transform coding gain. Then a theory has been derived regarding the impact of scaling steps on the transform coding gain (GT). The approach results in the lowest cost lossless architecture of the D8 in the literature, to the best of our knowledge. The proposed approach may be applied to other orthogonal wavelets, including biorthogonal ones to achieve higher performance. In the final phase, a general algorithm has been proposed to implement the original filter coefficients expressed by a polyphase matrix into a more efficient lifting structure. This is done by using modified factorization, so that the factorized polyphase matrix does not include the lossy scaling step like the conventional lifting method. This general technique has been applied on some widely used orthogonal and biorthogonal wavelets and its advantages have been discussed. Since the discrete wavelet transform is used in a vast number of applications, the proposed algorithms can be utilized in those cases to achieve lossless, low-cost, and hardware-friendly architectures

    Deteção espetral de banda larga para rádio cógnitivo

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    Doutoramento em TelecomunicaçõesEsta tese tem como objetivo o desenvolvimento de uma unidade autónoma de deteção espetral em tempo real. Para tal são analisadas várias implementações para a estimação do nível de ruído de fundo de forma a se poder criar um limiar adaptativo para um detetor com uma taxa constante de falso alarme. Além da identificação binária da utilização do espetro, pretende-se também obter a classificação individual de cada transmissor e a sua ocupação ao longo do tempo. Para tal são exploradas duas soluções baseadas no algoritmo, de agrupamento de dados, conhecido como maximização de expectativas que permite identificar os sinais analisados pela potência recebida e relação de fase entre dois recetores. Um algoritmo de deteção de sinal baseado também na relação de fase de dois recetores e sem necessidade de estimação do ruído de fundo é também demonstrado. Este algoritmo foi otimizado para permitir uma implementação eficiente num arranjo de portas programáveis em campo a funcionar em tempo real para uma elevada largura de banda, permitindo também estimar a direção da transmissão detetada.The purpose of this thesis is to develop an autonomous unit for real time spectrum sensing. For this purpose, several implementations for the estimation of the background noise level are analysed to create an adaptive threshold and ensure a constant false alarm rate detector. In addition to the binary identification of the spectrum usage, it is also intended to obtain an individual classification of each transmitter occupation and its spectrum usage over time. To do so, two solutions based on the expectation maximization data clustering, that allow to identify the analyzed signals by the received power and phase relation between two receivers, were explored. A signal detection algorithm, also based on the phase relationship between two receivers and with no need for noise estimation is also demonstrated. This algorithm has been optimized to allow an efficient implementation in a FPGA operating in real time for a high bandwidth and it also allows the estimation of the direction of arrival of the detected transmission

    The Telecommunications and Data Acquisition Report

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    This quarterly publication provides archival reports on developments in programs in space communications, radio navigation, radio science, and ground-based radio and radar astronomy. It reports on activities of the Deep Space Network (DSN) in planning, supporting research and technology, implementation, and operations. Also included are standardization activities at the Jet Propulsion Laboratory for space data and information systems

    Digital Predistortion of Pseudo-Orthogonal Wideband Waveforms for Dual-Polarimetric Phased Array Radars

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    Many new and interesting radar operational modes and techniques are being explored to maximize the efficiency and utility of next-generation radar systems while complying with increasingly stringent operational and budgeting requirements. This dissertation's aim is to analyze and present possible techniques to help maximize the scientific value of measurements while complying with operational requirements through methods of physical transmission and exciting the target area, methods of processing the received waveforms, and methods of designing waveforms for a given system. In regard to methods of physical transmission and exciting the target area, this dissertation addresses unique problems that will be faced by next-generation radar systems utilizing simultaneous transmit and simultaneous receive operational modes in polarimetric active phased array architectures. This is accomplished through establishing mathematical representations of the received complex baseband waveforms for dual-polarimetric radar operation and analyzing the predicted behavior versus traditional polarimetric radar alternating transmit and simultaneous receive operation. In regard to methods of processing the received waveforms, pulse compression will undoubtedly be widely utilized in future radar systems due to the increase in range resolution that it provides for a given pulse length. Additionally, matched filtering allows the realization of simultaneously transmitted pseudo-orthogonal waveforms occupying the same spectral region that would be otherwise impossible. As a result, the mathematical basis of pulse compression is provided, and pulse compression effects are taken into account in all relevant system analyses in this manuscript. This dissertation arguably provides the most attention in regard to methods for designing and modifying waveforms for application in a given system. An analysis of common pulse compression waveforms for suitability in pseudo-orthogonal waveform sets is provided in addition to a novel method for designing polyphase coded waveform and non-linear frequency modulated waveform based pseudo-orthogonal waveform sets utilizing particle swarm optimization. Additionally, for the first time, research is presented on the full design and application methods for digital predistortion of wideband solid state radar amplifiers. Digital predistortion methods and results are presented for both the impedance matched high power amplifier case and for the varying load impedance case that can be expected to be encountered in radar systems utilizing electronic beamsteering in active phased array architectures. Overall, this dissertation's aim is to provide relevant results from conducted research in the form of analysis and novel design methods that can be applied in both the design and operation of next-generation radar systems to maximize utility and scientific data quality while operating within given system and environmental specifications

    Gigahertz Bandwidth and Nanosecond Timescales: New Frontiers in Radio Astronomy Through Peak Performance Signal Processing

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    Abstract In the past decade, there has been a revolution in radio-astronomy signal processing. High bandwidth receivers coupled with fast ADCs have enabled the collection of tremendous instantaneous bandwidth, but streaming computational resources are struggling to catch up and serve these new capabilities. As a consequence, there is a need for novel signal processing algorithms capable of maximizing these resources. This thesis responds to the demand by presenting FPGA implementations of a Polyphase Filter Bank which are an order of magnitude more efficient than previous algorithms while exhibiting similar noise performance. These algorithms are showcased together alongside a broadband RF front-end in Starburst: a 5 GHz instantaneous bandwidth two-element interferometer, the first broadband digital sideband separating astronomical interferometer.  Starburst technology has been applied to three instruments to date. Abstract Wielding tremendous computational power and precisely calibrated hardware, low frequency radio telescope arrays have potential greatly exceeding their current applications.  This thesis presents new modes for low frequency radio-telescopes, dramatically extending their original capabilities.  A microsecond-scale time/frequency mode empowered the Owens Valley Long Wavelength Array to inspect not just the radio sky by enabling the testing of novel imaging techniques and detecting overhead beacon satellites, but also the terrestrial neighborhood, allowing for the characterization and mitigation of nearby sources of radio frequency interference (RFI).  This characterization led to insights prompting a nanosecond-scale observing mode to be developed, opening new avenues in high energy astrophysics, specifically related to the radio frequency detection of ultra-high energy cosmic rays and neutrinos. Abstract Measurement of the flux spectrum, composition, and origin of the highest energy cosmic ray events is a lofty goal in high energy astrophysics. One of the most powerful new windows has been the detection of associated extensive air showers at radio frequencies. However, all current ground-based systems must trigger off an expensive and insensitive external source such as particle detectors - making detection of the rare, high energy events uneconomical.  Attempts to make a direct detection in radio-only data have been unsuccessful despite numerous efforts. The problem is even more severe in the case of radio detection of ultra-high energy neutrino events, which cannot rely on in-situ particle detectors as a triggering mechanism. This thesis combines the aforementioned nanosecond-scale observing mode with real-time, on-FPGA RFI mitigation and sophisticated offline post-processing.  The resulting system has produced the first successful ground based detection of cosmic rays using only radio instruments. Design and measurements of cosmic ray detections are discussed, as well as recommendations for future cosmic ray experiments.  The presented future designs allow for another order of magnitude improvement in both sensitivity and output data-rate, paving the way for the economical ground-based detection of the highest energy neutrinos.</p

    The Telecommunications and Data Acquisition

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    This quarterly publication provides archival reports on developments in programs managed by JPL's Office of Telecommunications and Data Acquisition (TDA). In space communications, radio navigation, radio science, and ground-based radio and radar astronomy, it reports on activities of the Deep Space Network (DSN) in planning, supporting research and technology, implementation, and operations. Also included are standards activity at JPL for space data and information systems and reimbursable DSN work performed for other space agencies through NASA. The preceding work is all performed for NASA's Office of Space Communications (OSC)
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