68 research outputs found
Supervised Machine Learning for Signals Having RRC Shaped Pulses
Classification performances of the supervised machine learning techniques
such as support vector machines, neural networks and logistic regression are
compared for modulation recognition purposes. The simple and robust features
are used to distinguish continuous-phase FSK from QAM-PSK signals. Signals
having root-raised-cosine shaped pulses are simulated in extreme noisy
conditions having joint impurities of block fading, lack of symbol and sampling
synchronization, carrier offset, and additive white Gaussian noise. The
features are based on sample mean and sample variance of the imaginary part of
the product of two consecutive complex signal values.Comment: 5 page
Collision resolution in wireless networks
In a wireless uplink, collisions occur when two or more wireless users transmit signals at the same time over the same channel. Traditionally, when this happens, the received packets are discarded and retransmissions are required, which is a waste of power and bandwidth. The main contributions of this dissertation include a studyof approaches for collision resolution, i.e., recovery of collided packets, the design of pulse-shape functions that facilitate collision resolution and also the analysis ofpacket delays in a cellular wireless network whose base station has collision resolution capability.In the first part of this dissertation a new scheme, namely ALOHA with Collision Resolution (ALOHA-CR), is proposed, which is a cross-layer approach for highthroughput wireless communications in a cellular uplink scenario. Transmissions occur in a time-slotted ALOHA-type fashion but with an important difference: simultaneous transmissions of two users can be successful. When two users transmit, the collision is resolved by oversampling the collision signal and exploiting independent information about the users that is contained in the signal polyphase components. The performance of ALOHA-CR is demonstrated on the Wireless Open Access Research Platform (WARP) testbed containing five software defined radio (SDR) nodes. The testbed results indicate that ALOHA-CR leads to significant increase in throughput and reduction of service delays as compared to ALOHA. The second part of this dissertation focuses on optimal pulse-shape design for collision resolution. As mentioned above, the collided packets are separated by oversampling the collision signal. Because of oversampling, high correlations can occur between the columns of the virtual multiple-input multiple-output(MIMO) system matrix, which can be detrimental to user separation. A novel pulse-shape waveform design is proposed, which results in low correlation between the columns of the system matrix, while it exploits all available bandwidth as dictated by a spectral mask. In the third part, we study the delay properties of random scheduling (RS) in a cellular wireless network, under the assumption that the base station (BS) has multi-packet reception (MPR) capability. We minimize the expected delay of RS by determining the scheduling probabilities of nodes that will transmit simultaneously. For the perfect reception case, (i.e., when the success probability of transmissions is 1), a lower bound of the delay performance for an arbitrary scheduling policy is provided. The imperfect reception case is also studied and a convex optimization formulation is proposed, which can minimize theupper bound on the expected delay of RS. An approximation and a lower bound on the expected delay of RS are also developed under the assumption that the basestation can support simultaneous transmission of two users.Ph.D., Electrical Engineering -- Drexel University, 201
An Analysis of the Unmanned Aerial Systems-to-Ground Channel and Joint Sensing and Communications Systems Using Software Defined Radio
abstract: Software-defined radio provides users with a low-cost and flexible platform for implementing and studying advanced communications and remote sensing applications. Two such applications include unmanned aerial system-to-ground communications channel and joint sensing and communication systems. In this work, these applications are studied.
In the first part, unmanned aerial system-to-ground communications channel models are derived from empirical data collected from software-defined radio transceivers in residential and mountainous desert environments using a small (< 20 kg) unmanned aerial system during low-altitude flight (< 130 m). The Kullback-Leibler divergence measure was employed to characterize model mismatch from the empirical data. Using this measure the derived models accurately describe the underlying data.
In the second part, an experimental joint sensing and communications system is implemented using a network of software-defined radio transceivers. A novel co-design receiver architecture is presented and demonstrated within a three-node joint multiple access system topology consisting of an independent radar and communications transmitter along with a joint radar and communications receiver. The receiver tracks an emulated target moving along a predefined path and simultaneously decodes a communications message. Experimental system performance bounds are characterized jointly using the communications channel capacity and novel estimation information rate.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201
Ultra Wideband Communications: from Analog to Digital
ï»żUltrabreitband-Signale (Ultra Wideband [UWB]) können einen
signifikanten Nutzen im Bereich drahtloser Kommunikationssysteme haben. Es
sind jedoch noch einige Probleme offen, die durch Systemdesigner und
Wissenschaftler gelöst werden mĂŒssen. Ein Funknetzsystem mit einer derart
groĂen Bandbreite ist normalerweise auch durch eine groĂe Anzahl an
Mehrwegekomponenten mit jeweils verschiedenen Pfadamplituden
gekennzeichnet. Daher ist es schwierig, die zeitlich verteilte Energie
effektiv zu erfassen. AuĂerdem ist in vielen FĂ€llen der naheliegende
Ansatz, ein kohÀrenter EmpfÀnger im Sinne eines signalangepassten Filters
oder eines Korrelators, nicht unbedingt die beste Wahl. In der vorliegenden
Arbeit wird dabei auf die bestehende Problematik und weitere
Lösungsmöglichkeiten eingegangen.
Im ersten Abschnitt geht es um âImpulse Radio UWBâ-Systeme mit
niedriger Datenrate. Bei diesen Systemen kommt ein inkohÀrenter EmpfÀnger
zum Einsatz. InkohÀrente Signaldetektion stellt insofern einen
vielversprechenden Ansatz dar, als das damit aufwandsgĂŒnstige und robuste
Implementierungen möglich sind. Dies trifft vor allem in AnwendungsfÀllen
wie den von drahtlosen Sensornetzen zu, wo preiswerte GerÀte mit langer
Batterielaufzeit nötigsind. Dies verringert den fĂŒr die KanalschĂ€tzung
und die Synchronisation nötigen Aufwand, was jedoch auf Kosten der
Leistungseffizienz geht und eine erhöhte Störempfindlichkeit gegenĂŒber
Interferenz (z.B. Interferenz durch mehrere Nutzer oder schmalbandige
Interferenz) zur Folge hat.
Um die Bitfehlerrate der oben genannten Verfahren zu bestimmen, wurde
zunÀchst ein inkohÀrenter Combining-Verlust spezifiziert, welcher
auftritt im Gegensatz zu kohÀrenter Detektion mit Maximum Ratio Multipath
Combining. Dieser Verlust hÀngt von dem Produkt aus der LÀnge des
Integrationsfensters und der Signalbandbreite ab.
Um den Verlust durch inkohÀrentes Combining zu reduzieren und somit die
Leistungseffizienz des EmpfÀngers zu steigern, werden verbesserte
Combining-Methoden fĂŒr Mehrwegeempfang vorgeschlagen. Ein analoger
EmpfÀnger, bei dem der Hauptteil des Mehrwege-Combinings durch einen
âIntegrate and Dumpâ-Filter implementiert ist, wird fĂŒr UWB-Systeme
mit Zeit-Hopping gezeigt. Dabei wurde die Einsatzmöglichkeit von dĂŒnn
besetzten Codes in solchen System diskutiert und bewertet. Des Weiteren
wird eine Regel fĂŒr die Code-Auswahl vorgestellt, welche die StabilitĂ€t
des Systems gegen Mehrnutzer-Störungen sicherstellt und gleichzeitig den
Verlust durch inkohÀrentes Combining verringert.
Danach liegt der Fokus auf digitalen Lösungen bei inkohÀrenter
Demodulation. Im Vergleich zum AnalogempfÀnger besitzt ein
DigitalempfÀnger einen Analog-Digital-Wandler im Zeitbereich gefolgt von
einem digitalen Optimalfilter. Der digitale Optimalfilter dekodiert den
Mehrfachzugriffscode kohÀrent und beschrÀnkt das inkohÀrente Combining
auf die empfangenen Mehrwegekomponenten im Digitalbereich. Es kommt ein
schneller Analog-Digital-Wandler mit geringer Auflösung zum Einsatz, um
einen vertretbaren Energieverbrauch zu gewÀhrleisten. Diese Digitaltechnik
macht den Einsatz langer Analogverzögerungen bei differentieller
Demodulation unnötig und ermöglicht viele Arten der digitalen
Signalverarbeitung. Im Vergleich zur Analogtechnik reduziert sie nicht nur
den inkohÀrenten Combining-Verlust, sonder zeigt auch eine stÀrkere
Resistenz gegenĂŒber Störungen. Dabei werden die Auswirkungen der
Auflösung und der Abtastrate der Analog-Digital-Umsetzung analysiert. Die
Resultate zeigen, dass die verminderte Effizienz solcher
Analog-Digital-Wandler gering ausfÀllt. Weiterhin zeigt sich, dass im
Falle starker Mehrnutzerinterferenz sogar eine Verbesserung der Ergebnisse
zu beobachten ist. Die vorgeschlagenen Design-Regeln spezifizieren die
Anwendung der Analog-Digital-Wandler und die Auswahl der Systemparameter in
AbhÀngigkeit der verwendeten Mehrfachzugriffscodes und der Modulationsart.
Wir zeigen, wie unter Anwendung erweiterter Modulationsverfahren die
Leistungseffizienz verbessert werden kann und schlagen ein Verfahren zur
UnterdrĂŒckung schmalbandiger Störer vor, welches auf Soft Limiting
aufbaut. Durch die Untersuchungen und Ergebnissen zeigt sich, dass
inkohÀrente EmpfÀnger in UWB-Kommunikationssystemen mit niedriger
Datenrate ein groĂes Potential aufweisen.
AuĂerdem wird die Auswahl der benutzbaren Bandbreite untersucht, um einen
Kompromiss zwischen inkohÀrentem Combining-Verlust und StabilitÀt
gegenĂŒber langsamen Schwund zu erreichen. Dadurch wurde ein neues Konzept
fĂŒr UWB-Systeme erarbeitet: wahlweise kohĂ€rente oder inkohĂ€rente
EmpfÀnger, welche als UWB-Systeme Frequenz-Hopping nutzen. Der wesentliche
Vorteil hiervon liegt darin, dass die Bandbreite im Basisband sich deutlich
verringert. Mithin ermöglicht dies einfach zu realisierende digitale
Signalverarbeitungstechnik mit kostengĂŒnstigen Analog-Digital-Wandlern.
Dies stellt eine neue Epoche in der Forschung im Bereich drahtloser
Sensorfunknetze dar.
Der Schwerpunkt des zweiten Abschnitts stellt adaptiven Signalverarbeitung
fĂŒr hohe Datenraten mit âDirect Sequenceâ-UWB-Systemen in den
Vordergrund. In solchen Systemen entstehen, wegen der groĂen Anzahl der
empfangenen Mehrwegekomponenten, starke Inter- bzw.
Intrasymbolinterferenzen. AuĂerdem kann die FunktionalitĂ€t des Systems
durch Mehrnutzerinterferenz und Schmalbandstörungen deutlich beeinflusst
werden. Um sie zu eliminieren, wird die âWidely Linearâ-Rangreduzierung
benutzt. Dabei verbessert die Rangreduzierungsmethode das
Konvergenzverhalten, besonders wenn der gegebene Vektor eine sehr groĂe
Anzahl an Abtastwerten beinhaltet (in Folge hoher einer Abtastrate).
ZusÀtzlich kann das System durch die Anwendung der R-linearen Verarbeitung
die Statistik zweiter Ordnung des nicht-zirkularen Signals vollstÀndig
ausnutzen, was sich in verbesserten SchÀtzergebnissen widerspiegelt.
Allgemeine kann die Methode der âWidely Linearâ-Rangreduzierung auch in
andern Bereichen angewendet werden, z.B. in âDirect
Sequenceâ-Codemultiplexverfahren (DS-CDMA), im MIMO-Bereich, im Global
System for Mobile Communications (GSM) und beim Beamforming.The aim of this thesis is to investigate key issues encountered in the
design of transmission schemes and receiving techniques for Ultra Wideband
(UWB) communication systems. Based on different data rate applications,
this work is divided into two parts, where energy efficient and robust
physical layer solutions are proposed, respectively.
Due to a huge bandwidth of UWB signals, a considerable amount of multipath
arrivals with various path gains is resolvable at the receiver. For low
data rate impulse radio UWB systems, suboptimal non-coherent detection is a
simple way to effectively capture the multipath energy. Feasible techniques
that increase the power efficiency and the interference robustness of
non-coherent detection need to be investigated. For high data rate direct
sequence UWB systems, a large number of multipath arrivals results in
severe inter-/intra-symbol interference. Additionally, the system
performance may also be deteriorated by multi-user interference and
narrowband interference. It is necessary to develop advanced signal
processing techniques at the receiver to suppress these interferences.
Part I of this thesis deals with the co-design of signaling schemes and
receiver architectures in low data rate impulse radio UWB systems based on
non-coherent detection.â We analyze the bit error rate performance of
non-coherent detection and characterize a non-coherent combining loss,
i.e., a performance penalty with respect to coherent detection with maximum
ratio multipath combining. The thorough analysis of this loss is very
helpful for the design of transmission schemes and receive techniques
innon-coherent UWB communication systems.â We propose to use optical
orthogonal codes in a time hopping impulse radio UWB system based on an
analog non-coherent receiver. The âanalogâ means that the major part of
the multipath combining is implemented by an integrate and dump filter. The
introduced semi-analytical method can help us to easily select the time
hopping codes to ensure the robustness against the multi-user interference
and meanwhile to alleviate the non-coherent combining loss.â The main
contribution of Part I is the proposal of applying fully digital solutions
in non-coherent detection. The proposed digital non-coherent receiver is
based on a time domain analog-to-digital converter, which has a high speed
but a very low resolution to maintain a reasonable power consumption.
Compared to its analog counterpart, itnot only significantly reduces the
non-coherent combining loss but also offers a higher interference
robustness. In particular, the one-bit receiver can effectively suppress
strong multi-user interference and is thus advantageous in separating
simultaneously operating piconets.The fully digital solutions overcome the
difficulty of implementing long analog delay lines and make differential
UWB detection possible. They also facilitate the development of various
digital signal processing techniques such as multi-user detection and
non-coherent multipath combining methods as well as the use of advanced
modulationschemes (e.g., M-ary Walsh modulation).â Furthermore, we
present a novel impulse radio UWB system based on frequency hopping, where
both coherent and non-coherent receivers can be adopted. The key advantage
is that the baseband bandwidth can be considerably reduced (e.g., lower
than 500 MHz), which enables low-complexity implementation of the fully
digital solutions. It opens up various research activities in the
application field of wireless sensor networks.
Part II of this thesis proposes adaptive widely linear reduced-rank
techniques to suppress interferences for high data rate direct sequence UWB
systems, where second-order non-circular signals are used. The reduced-rank
techniques are designed to improve the convergence performance and the
interference robustness especially when the received vector contains a
large number of samples (due to a high sampling rate in UWB systems). The
widely linear processing takes full advantage of the second-order
statistics of the non-circular signals and enhances the estimation
performance. The generic widely linear reduced-rank concept also has a
great potential in the applications of other systems such as Direct
Sequence Code Division Multiple Access (DS-CDMA), Multiple Input Multiple
Output (MIMO) system, and Global System for Mobile Communications (GSM), or
in other areas such as beamforming
Anwendung von maschinellem Lernen in der optischen NachrichtenĂŒbertragungstechnik
Aufgrund des zunehmenden Datenverkehrs wird erwartet, dass die optischen Netze zukĂŒnftig mit höheren SystemkapazitĂ€ten betrieben werden. Dazu wird bspw. die kohĂ€rente Ăbertragung eingesetzt, bei der das Modulationsformat erhöht werden kann, erforder jedoch ein gröĂeres SNR. Um dies zu erreichen, wird die optische Signalleistung erhöht, wodurch die DatenĂŒbertragung durch die nichtlinearen BeeintrĂ€chtigungen gestört wird. Der Schwerpunkt dieser Arbeit liegt auf der Entwicklung von Modellen des maschinellen Lernens, die auf diese nichtlineare Signalverschlechterung reagieren. Es wird die Support-Vector-Machine (SVM) implementiert und als klassifizierende Entscheidungsmaschine verwendet. Die Ergebnisse zeigen, dass die SVM eine verbesserte Kompensation sowohl der nichtlinearen Fasereffekte als auch der Verzerrungen der optischen Systemkomponenten ermöglicht. Das Prinzip von EONs bietet eine Technologie zur effizienten Nutzung der verfĂŒgbaren Ressourcen, die von der optischen Faser bereitgestellt werden. Ein SchlĂŒsselelement der Technologie ist der bandbreitenvariable Transponder, der bspw. die Anpassung des Modulationsformats oder des Codierungsschemas an die aktuellen Verbindungsbedingungen ermöglicht. Um eine optimale Ressourcenauslastung zu gewĂ€hrleisten wird der Einsatz von Algorithmen des Reinforcement Learnings untersucht. Die Ergebnisse zeigen, dass der RL-Algorithmus in der Lage ist, sich an unbekannte Link-Bedingungen anzupassen, wĂ€hrend vergleichbare heuristische AnsĂ€tze wie der genetische Algorithmus fĂŒr jedes Szenario neu trainiert werden mĂŒssen
Advanced signal processing solutions for ATR and spectrum sharing in distributed radar systems
Previously held under moratorium from 11 September 2017 until 16 February 2022This Thesis presents advanced signal processing solutions for Automatic
Target Recognition (ATR) operations and for spectrum sharing in distributed radar systems.
Two Synthetic Aperture Radar (SAR) ATR algorithms are described for
full- and single-polarimetric images, and tested on the GOTCHA and the
MSTAR datasets. The first one exploits the Krogager polarimetric decomposition in order to enhance peculiar scattering mechanisms from manmade targets, used in combination with the pseudo-Zernike image moments. The second algorithm employs the Krawtchouk image moments,
that, being discrete defined, provide better representations of targetsâ details. The proposed image moments based framework can be extended to
the availability of several images from multiple sensors through the implementation of a simple fusion rule.
A model-based micro-Doppler algorithm is developed for the identification of helicopters. The approach relies on the proposed sparse representation of the signal scattered from the helicopterâs rotor and received by
the radar. Such a sparse representation is obtained through the application of a greedy sparse recovery framework, with the goal of estimating
the number, the length and the rotation speed of the blades, parameters
that are peculiar for each helicopterâs model. The algorithm is extended to
deal with the identification of multiple helicopters flying in formation that
cannot be resolved in another domain. Moreover, a fusion rule is presented
to integrate the results of the identification performed from several sensors
in a distributed radar system. Tests performed both on simulated signals
and on real signals acquired from a scale model of a helicopter, confirm
the validity of the algorithm.
Finally, a waveform design framework for joint radar-communication systems is presented. The waveform is composed by quasi-orthogonal chirp
sub-carriers generated through the Fractional Fourier Transform (FrFT),
with the aim of preserving the radar performance of a typical Linear Frequency Modulated (LFM) pulse while embedding data to be sent to a
cooperative system. Techniques aimed at optimise the design parameters and mitigate the Inter-Carrier Interference (ICI) caused by the quasiorthogonality of the chirp sub-carriers are also described. The FrFT based
waveform is extensively tested and compared with Orthogonal Frequency
Division Multiplexing (OFDM) and LFM waveforms, in order to assess
both its radar and communication performance.This Thesis presents advanced signal processing solutions for Automatic
Target Recognition (ATR) operations and for spectrum sharing in distributed radar systems.
Two Synthetic Aperture Radar (SAR) ATR algorithms are described for
full- and single-polarimetric images, and tested on the GOTCHA and the
MSTAR datasets. The first one exploits the Krogager polarimetric decomposition in order to enhance peculiar scattering mechanisms from manmade targets, used in combination with the pseudo-Zernike image moments. The second algorithm employs the Krawtchouk image moments,
that, being discrete defined, provide better representations of targetsâ details. The proposed image moments based framework can be extended to
the availability of several images from multiple sensors through the implementation of a simple fusion rule.
A model-based micro-Doppler algorithm is developed for the identification of helicopters. The approach relies on the proposed sparse representation of the signal scattered from the helicopterâs rotor and received by
the radar. Such a sparse representation is obtained through the application of a greedy sparse recovery framework, with the goal of estimating
the number, the length and the rotation speed of the blades, parameters
that are peculiar for each helicopterâs model. The algorithm is extended to
deal with the identification of multiple helicopters flying in formation that
cannot be resolved in another domain. Moreover, a fusion rule is presented
to integrate the results of the identification performed from several sensors
in a distributed radar system. Tests performed both on simulated signals
and on real signals acquired from a scale model of a helicopter, confirm
the validity of the algorithm.
Finally, a waveform design framework for joint radar-communication systems is presented. The waveform is composed by quasi-orthogonal chirp
sub-carriers generated through the Fractional Fourier Transform (FrFT),
with the aim of preserving the radar performance of a typical Linear Frequency Modulated (LFM) pulse while embedding data to be sent to a
cooperative system. Techniques aimed at optimise the design parameters and mitigate the Inter-Carrier Interference (ICI) caused by the quasiorthogonality of the chirp sub-carriers are also described. The FrFT based
waveform is extensively tested and compared with Orthogonal Frequency
Division Multiplexing (OFDM) and LFM waveforms, in order to assess
both its radar and communication performance
Adaptive equalisation for fading digital communication channels
This thesis considers the design of new adaptive equalisers for fading digital communication channels. The role of equalisation is discussed in the context of the functions of a digital radio communication system and both conventional and more recent novel equaliser designs are described. The application of recurrent neural networks to the problem of equalisation is developed from a theoretical study of a single node structure to the design of multinode structures. These neural networks are shown to cancel intersymbol interference in a manner mimicking conventional techniques and simulations demonstrate their sensitivity to symbol estimation errors. In addition the error mechanisms of conventional maximum likelihood equalisers operating on rapidly time-varying channels are investigated and highlight the problems of channel estimation using delayed and often incorrect symbol estimates. The relative sensitivity of Bayesian equalisation techniques to errors in the channel estimate is studied and demonstrates that the structure's equalisation capability is also susceptible to such errors. Applications of multiple channel estimator methods are developed, leading to reduced complexity structures which trade performance for a smaller computational load. These novel structures are shown to provide an improvement over the conventional techniques, especially for rapidly time-varying channels, by reducing the time delay in the channel estimation process. Finally, the use of confidence measures of the equaliser's symbol estimates in order to improve channel estimation is studied and isolates the critical areas in the development of the technique â the production of reliable confidence measures by the equalisers and the statistics of symbol estimation error bursts
Radio Communications
In the last decades the restless evolution of information and communication technologies (ICT) brought to a deep transformation of our habits. The growth of the Internet and the advances in hardware and software implementations modiïŹed our way to communicate and to share information. In this book, an overview of the major issues faced today by researchers in the ïŹeld of radio communications is given through 35 high quality chapters written by specialists working in universities and research centers all over the world. Various aspects will be deeply discussed: channel modeling, beamforming, multiple antennas, cooperative networks, opportunistic scheduling, advanced admission control, handover management, systems performance assessment, routing issues in mobility conditions, localization, web security. Advanced techniques for the radio resource management will be discussed both in single and multiple radio technologies; either in infrastructure, mesh or ad hoc networks
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