316 research outputs found
Hardware Precoding Demonstration in Multi-Beam UHTS Communications under Realistic Payload Characteristics
In this paper, we present a new hardware test-bed to demonstrate closed-loop precoded communications for interference mitigation in multi-beam ultra high throughput satellite systems under realistic payload and channel impairments. We build the test-bed to demonstrate a real-time channel aided precoded transmission under realistic conditions such as the power constraints and satellite-payload non-linearities. We develop a scalable architecture of an SDR platform with the DVB-S2X piloting. The SDR platform consists of two parts: analog-to-digital (ADC) and digital-to-analog (DAC) converters preceded by radio frequency (RF) front-end and Field-Programmable Gate Array (FPGA) backend. The former introduces realistic impairments in the transmission chain such as carrier frequency and phase misalignments, quantization noise of multichannel ADC and DAC and non-linearities of RF components. It allows evaluating the performance of the precoded transmission in a more realistic environment rather than using only numerical simulations. We benchmark the performance of the communication standard in realistic channel scenarios, evaluate received signal
SNR, and measure the actual channel throughput using LDPC codes
Wireless technology: current status and future directions
Wireless Technology is expected to be the dominant
mode of access technology in the future. Besides voice, a
new data range of services such as multimedia and high
speed data are being offered for delivery over wireless
network. Mobility will be seamless, realizing the concept
of persons' being in contact anywhere, at any time.
Throughout this paper, we review the long, interesting
development of wireless communication in the past,
examine the current progress in standards and
technologies, and finally discuss possible trends for
wireless communication solutions
Spectrum Occupancy Estimation and Analysis
The goal of Cognitive Radio (CR) is to facilitate efficient utilization of the electromagnetic spectrum. CR applies spectrum sensing techniques to detect unused channels and then allows opportunistic usage of such channels by secondary users, i.e., un-licensed users, without interfering with primary users, i.e., licensed users. In order to implement a complete TV White Spaces (TVWS) based CR system, at first a model is needed that can be used for identifying TVWS, which can then be exploited for dynamic spectrum access. This work is focused on proposing a sensing method and building a probabilistic model for identifying the occupancy of the electromagnetic spectrum within the UHF TV bands. It also develops a hardware prototype for demonstrating the performance of the proposed technique. It proposes simultaneous sensing both noise and noise-contaminated user\u27s signal (composite signal) for detecting spectrum occupancy minimizing errors. The proposed sensing technique combines energy detection, pilot detection, and information obtained from an external source in order to reduce missed-detection probability. In addition to pre-defined threshold levels, the proposed probabilistic model considers parameters like probability of false alarm and probability of detection for measuring detection accuracy. Finally, a mobile sensing station is designed and implemented using off-the-shelf components to verify the developed technique for TVWS spectrum sensing. Using this mobile station, the UHF TV channels within the spectrum band of 500MHz-698MHz (Channel #19 to Channel 51) are scanned. Covering the total bandwidth of 198MHz, over 8 million data samples are collected through repeated scanning, ensuring possible spatio-temporal variations are taken into account. Results show that the availability of TVWS changes quite significantly with spatial variations. But, even in the most crowded spectrum locations, 28% of UHF channels were identified as TVWS. The model demonstrates about 10% improvement in detecting accuracy compared to other existing models
Interference charecterisation, location and bandwidth estimation in emerging WiFi networks
Wireless LAN technology based on the IEEE 802.11 standard, commonly referred
to as WiFi, has been hugely successful not only for the last hop access to the Internet
in home, office and hotspot scenarios but also for realising wireless backhaul in mesh
networks and for point -to -point long- distance wireless communication. This success
can be mainly attributed to two reasons: low cost of 802.11 hardware from reaching
economies of scale, and operation in the unlicensed bands of wireless spectrum.The popularity of WiFi, in particular for indoor wireless access at homes and offices,
has led to significant amount of research effort looking at the performance issues
arising from various factors, including interference, CSMA/CA based MAC protocol
used by 802.11 devices, the impact of link and physical layer overheads on application
performance, and spatio-temporal channel variations. These factors affect the performance
of applications and services that run over WiFi networks. In this thesis, we
experimentally investigate the effects of some of the above mentioned factors in the
context of emerging WiFi network scenarios such as multi- interface indoor mesh networks,
802.11n -based WiFi networks and WiFi networks with virtual access points
(VAPs). More specifically, this thesis comprises of four experimental characterisation
studies: (i) measure prevalence and severity of co- channel interference in urban WiFi
deployments; (ii) characterise interference in multi- interface indoor mesh networks;
(iii) study the effect of spatio-temporal channel variations, VAPs and multi -band operation
on WiFi fingerprinting based location estimation; and (iv) study the effects of
newly introduced features in 802.11n like frame aggregation (FA) on available bandwidth
estimation.With growing density of WiFi deployments especially in urban areas, co- channel
interference becomes a major factor that adversely affects network performance. To
characterise the nature of this phenomena at a city scale, we propose using a new measurement
methodology called mobile crowdsensing. The idea is to leverage commodity
smartphones and the natural mobility of people to characterise urban WiFi co- channel
interference. Specifically, we report measurement results obtained for Edinburgh, a
representative European city, on detecting the presence of deployed WiFi APs via the
mobile crowdsensing approach. These show that few channels in 2.4GHz are heavily
used and there is hardly any activity in the 5GHz band even though relatively it
has a greater number of available channels. Spatial analysis of spectrum usage reveals
that co- channel interference among nearby APs operating in the same channel
can be a serious problem with around 10 APs contending with each other in many locations. We find that the characteristics of WiFi deployments at city -scale are similar
to those of WiFi deployments in public spaces of different indoor environments. We
validate our approach in comparison with wardriving, and also show that our findings
generally match with previous studies based on other measurement approaches. As
an application of the mobile crowdsensing based urban WiFi monitoring, we outline a
cloud based WiFi router configuration service for better interference management with
global awareness in urban areas.For mesh networks, the use of multiple radio interfaces is widely seen as a practical
way to achieve high end -to -end network performance and better utilisation of
available spectrum. However this gives rise to another type of interference (referred to
as coexistence interference) due to co- location of multiple radio interfaces. We show
that such interference can be so severe that it prevents concurrent successful operation
of collocated interfaces even when they use channels from widely different frequency
bands. We propose the use of antenna polarisation to mitigate such interference and
experimentally study its benefits in both multi -band and single -band configurations. In
particular, we show that using differently polarised antennas on a multi -radio platform
can be a helpful counteracting mechanism for alleviating receiver blocking and adjacent
channel interference phenomena that underlie multi -radio coexistence interference.
We also validate observations about adjacent channel interference from previous
studies via direct and microscopic observation of MAC behaviour.Location is an indispensable information for navigation and sensing applications.
The rapidly growing adoption of smartphones has resulted in a plethora of mobile
applications that rely on position information (e.g., shopping apps that use user position
information to recommend products to users and help them to find what they want
in the store). WiFi fingerprinting is a popular and well studied approach for indoor
location estimation that leverages the existing WiFi infrastructure and works based on
the difference in strengths of the received AP signals at different locations. However,
understanding the impact of WiFi network deployment aspects such as multi -band
APs and VAPs has not received much attention in the literature. We first examine the
impact of various aspects underlying a WiFi fingerprinting system. Specifically, we
investigate different definitions for fingerprinting and location estimation algorithms
across different indoor environments ranging from a multi- storey office building to
shopping centres of different sizes. Our results show that the fingerprint definition
is as important as the choice of location estimation algorithm and there is no single
combination of these two that works across all environments or even all floors of a given environment. We then consider the effect of WiFi frequency bands (e.g., 2.4GHz
and 5GHz) and the presence of virtual access points (VAPs) on location accuracy with
WiFi fingerprinting. Our results demonstrate that lower co- channel interference in the
5GHz band yields more accurate location estimation. We show that the inclusion of
VAPs has a significant impact on the location accuracy of WiFi fingerprinting systems;
we analyse the potential reasons to explain the findings.End -to -end available bandwidth estimation (ABE) has a wide range of uses, from
adaptive application content delivery, transport-level transmission rate adaptation and
admission control to traffic engineering and peer node selection in peer -to- peer /overlay
networks [ 1, 2]. Given its importance, it has been received much research attention in
both wired data networks and legacy WiFi networks (based on 802.11 a/b /g standards),
resulting in different ABE techniques and tools proposed to optimise different criteria
and suit different scenarios. However, effects of new MAC/PHY layer enhancements
in new and next generation WiFi networks (based on 802.11n and 802.11ac
standards) have not been studied yet. We experimentally find that among different
new features like frame aggregation, channel bonding and MIMO modes (spacial division
multiplexing), frame aggregation has the most harmful effect as it has direct
effect on ABE by distorting the measurement probing traffic pattern commonly used
to estimate available bandwidth. Frame aggregation is also specified in both 802.11n
and 802.1 lac standards as a mandatory feature to be supported. We study the effect of
enabling frame aggregation, for the first time, on the performance of the ABE using an
indoor 802.11n wireless testbed. The analysis of results obtained using three tools -
representing two main Probe Rate Model (PRM) and Probe Gap Model (PGM) based
approaches for ABE - led us to come up with the two key principles of jumbo probes
and having longer measurement probe train sizes to counter the effects of aggregating
frames on the performance of ABE tools. Then, we develop a new tool, WBest+ that
is aware of the underlying frame aggregation by incorporating these principles. The
experimental evaluation of WBest+ shows more accurate ABE in the presence of frame
aggregation.Overall, the contributions of this thesis fall in three categories - experimental
characterisation, measurement techniques and mitigation/solution approaches for performance
problems in emerging WiFi network scenarios. The influence of various factors
mentioned above are all studied via experimental evaluation in a testbed or real - world setting. Specifically, co- existence interference characterisation and evaluation
of available bandwidth techniques are done using indoor testbeds, whereas characterisation of urban WiFi networks and WiFi fingerprinting based location estimation are
carried out in real environments. New measurement approaches are also introduced
to aid better experimental evaluation or proposed as new measurement tools. These
include mobile crowdsensing based WiFi monitoring; MAC/PHY layer monitoring of
co- existence interference; and WBest+ tool for available bandwidth estimation. Finally,
new mitigation approaches are proposed to address challenges and problems
identified throughout the characterisation studies. These include: a proposal for crowd - based interference management in large scale uncoordinated WiFi networks; exploiting
antenna polarisation diversity to remedy the effects of co- existence interference
in multi -interface platforms; taking advantage of VAPs and multi -band operation for
better location estimation; and introducing the jumbo frame concept and longer probe
train sizes to improve performance of ABE tools in next generation WiFi networks
On the use of smartphones as novel photogrammetric water gauging instruments: Developing tools for crowdsourcing water levels
The term global climate change is omnipresent since the beginning of the last decade. Changes in the global climate are associated with an increase in heavy rainfalls that can cause nearly unpredictable flash floods. Consequently, spatio-temporally high-resolution monitoring of rivers becomes increasingly important.
Water gauging stations continuously and precisely measure water levels. However, they are rather expensive in purchase and maintenance and are preferably installed at water bodies relevant for water management. Small-scale catchments remain often ungauged. In order to increase the data density of hydrometric monitoring networks and thus to improve the prediction quality of flood events, new, flexible and cost-effective water level measurement technologies are required. They should be oriented towards the accuracy requirements of conventional measurement systems and facilitate the observation of water levels at virtually any time, even at the smallest rivers.
A possible solution is the development of a photogrammetric smartphone application (app) for crowdsourcing water levels, which merely requires voluntary users to take pictures of a river section to determine the water level. Today’s smartphones integrate high-resolution cameras, a variety of sensors, powerful processors, and mass storage. However, they are designed for the mass market and use low-cost hardware that cannot comply with the quality of geodetic measurement technology.
In order to investigate the potential for mobile measurement applications, research was conducted on the smartphone as a photogrammetric measurement instrument as part of the doctoral project. The studies deal with the geometric stability of smartphone cameras regarding device-internal temperature changes and with the accuracy potential of rotation parameters measured with smartphone sensors.
The results show a high, temperature-related variability of the interior orientation parameters, which is why the calibration of the camera should be carried out during the immediate measurement. The results of the sensor investigations show considerable inaccuracies when measuring rotation parameters, especially the compass angle (errors up to 90° were observed). The same applies to position parameters measured by global navigation satellite system (GNSS) receivers built into smartphones. According to the literature, positional accuracies of about 5 m are possible in best conditions. Otherwise, errors of several 10 m are to be expected. As a result, direct georeferencing of image measurements using current smartphone technology should be discouraged.
In consideration of the results, the water gauging app Open Water Levels (OWL) was developed, whose methodological development and implementation constituted the core of the thesis project. OWL enables the flexible measurement of water levels via crowdsourcing without requiring additional equipment or being limited to specific river sections. Data acquisition and processing take place directly in the field, so that the water level information is immediately available.
In practice, the user captures a short time-lapse sequence of a river bank with OWL, which is used to calculate a spatio-temporal texture that enables the detection of the water line. In order to translate the image measurement into 3D object space, a synthetic, photo-realistic image of the situation is created from existing 3D data of the river section to be investigated. Necessary approximations of the image orientation parameters are measured by smartphone sensors and GNSS. The assignment of camera image and synthetic image allows for the determination of the interior and exterior orientation parameters by means of space resection and finally the transfer of the image-measured 2D water line into the 3D object space to derive the prevalent water level in the reference system of the 3D data.
In comparison with conventionally measured water levels, OWL reveals an accuracy potential of 2 cm on average, provided that synthetic image and camera image exhibit consistent image contents and that the water line can be reliably detected. In the present dissertation, related geometric and radiometric problems are comprehensively discussed. Furthermore, possible solutions, based on advancing developments in smartphone technology and image processing as well as the increasing availability of 3D reference data, are presented in the synthesis of the work.
The app Open Water Levels, which is currently available as a beta version and has been tested on selected devices, provides a basis, which, with continuous further development, aims to achieve a final release for crowdsourcing water levels towards the establishment of new and the expansion of existing monitoring networks.Der Begriff des globalen Klimawandels ist seit Beginn des letzten Jahrzehnts allgegenwärtig. Die Veränderung des Weltklimas ist mit einer Zunahme von Starkregenereignissen verbunden, die nahezu unvorhersehbare Sturzfluten verursachen können. Folglich gewinnt die raumzeitlich hochaufgelöste Überwachung von Fließgewässern zunehmend an Bedeutung.
Pegelmessstationen erfassen kontinuierlich und präzise Wasserstände, sind jedoch in Anschaffung und Wartung sehr teuer und werden vorzugsweise an wasserwirtschaftlich-relevanten Gewässern installiert. Kleinere Gewässer bleiben häufig unbeobachtet. Um die Datendichte hydrometrischer Messnetze zu erhöhen und somit die Vorhersagequalität von Hochwasserereignissen zu verbessern, sind neue, kostengünstige und flexibel einsetzbare Wasserstandsmesstechnologien erforderlich. Diese sollten sich an den Genauigkeitsanforderungen konventioneller Messsysteme orientieren und die Beobachtung von Wasserständen zu praktisch jedem Zeitpunkt, selbst an den kleinsten Flüssen, ermöglichen.
Ein Lösungsvorschlag ist die Entwicklung einer photogrammetrischen Smartphone-Anwendung (App) zum Crowdsourcing von Wasserständen mit welcher freiwillige Nutzer lediglich Bilder eines Flussabschnitts aufnehmen müssen, um daraus den Wasserstand zu bestimmen. Heutige Smartphones integrieren hochauflösende Kameras, eine Vielzahl von Sensoren, leistungsfähige Prozessoren und Massenspeicher. Sie sind jedoch für den Massenmarkt konzipiert und verwenden kostengünstige Hardware, die nicht der Qualität geodätischer Messtechnik entsprechen kann.
Um das Einsatzpotential in mobilen Messanwendungen zu eruieren, sind Untersuchungen zum Smartphone als photogrammetrisches Messinstrument im Rahmen des Promotionsprojekts durchgeführt worden. Die Studien befassen sich mit der geometrischen Stabilität von Smartphone-Kameras bezüglich geräteinterner Temperaturänderungen und mit dem Genauigkeitspotential von mit Smartphone-Sensoren gemessenen Rotationsparametern.
Die Ergebnisse zeigen eine starke, temperaturbedingte Variabilität der inneren Orientierungsparameter, weshalb die Kalibrierung der Kamera zum unmittelbaren Messzeitpunkt erfolgen sollte. Die Ergebnisse der Sensoruntersuchungen zeigen große Ungenauigkeiten bei der Messung der Rotationsparameter, insbesondere des Kompasswinkels (Fehler von bis zu 90° festgestellt). Selbiges gilt auch für Positionsparameter, gemessen durch in Smartphones eingebaute Empfänger für Signale globaler Navigationssatellitensysteme (GNSS). Wie aus der Literatur zu entnehmen ist, lassen sich unter besten Bedingungen Lagegenauigkeiten von etwa 5 m erreichen. Abseits davon sind Fehler von mehreren 10 m zu erwarten. Infolgedessen ist von einer direkten Georeferenzierung von Bildmessungen mittels aktueller Smartphone-Technologie abzusehen.
Unter Berücksichtigung der gewonnenen Erkenntnisse wurde die Pegel-App Open Water Levels (OWL) entwickelt, deren methodische Entwicklung und Implementierung den Kern der Arbeit bildete. OWL ermöglicht die flexible Messung von Wasserständen via Crowdsourcing, ohne dabei zusätzliche Ausrüstung zu verlangen oder auf spezifische Flussabschnitte beschränkt zu sein. Datenaufnahme und Verarbeitung erfolgen direkt im Feld, so dass die Pegelinformationen sofort verfügbar sind.
Praktisch nimmt der Anwender mit OWL eine kurze Zeitraffersequenz eines Flussufers auf, die zur Berechnung einer Raum-Zeit-Textur dient und die Erkennung der Wasserlinie ermöglicht. Zur Übersetzung der Bildmessung in den 3D-Objektraum wird aus vorhandenen 3D-Daten des zu untersuchenden Flussabschnittes ein synthetisches, photorealistisches Abbild der Aufnahmesituation erstellt. Erforderliche Näherungen der Bildorientierungsparameter werden von Smartphone-Sensoren und GNSS gemessen. Die Zuordnung von Kamerabild und synthetischem Bild erlaubt die Bestimmung der inneren und äußeren Orientierungsparameter mittels räumlichen Rückwärtsschnitt. Nach Rekonstruktion der Aufnahmesituation lässt sich die im Bild gemessene 2D-Wasserlinie in den 3D-Objektraum projizieren und der vorherrschende Wasserstand im Referenzsystem der 3D-Daten ableiten.
Im Soll-Ist-Vergleich mit konventionell gemessenen Pegeldaten zeigt OWL ein erreichbares Genauigkeitspotential von durchschnittlich 2 cm, insofern synthetisches und reales Kamerabild einen möglichst konsistenten Bildinhalt aufweisen und die Wasserlinie zuverlässig detektiert werden kann. In der vorliegenden Dissertation werden damit verbundene geometrische und radiometrische Probleme ausführlich diskutiert sowie Lösungsansätze, auf der Basis fortschreitender Entwicklungen von Smartphone-Technologie und Bildverarbeitung sowie der zunehmenden Verfügbarkeit von 3D-Referenzdaten, in der Synthese der Arbeit vorgestellt.
Mit der gegenwärtig als Betaversion vorliegenden und auf ausgewählten Geräten getesteten App Open Water Levels wurde eine Basis geschaffen, die mit kontinuierlicher Weiterentwicklung eine finale Freigabe für das Crowdsourcing von Wasserständen und damit den Aufbau neuer und die Erweiterung bestehender Monitoring-Netzwerke anstrebt
Semi-empirical modelling of subtropical rain attenuation on earth-satellite microwave links.
Doctoral Degree. University of KwaZulu-Natal, Durban.The exponential rise in demand for high fidelity content on multiple platforms has in recent years made increased use of the higher echelons of radio communication frequency inevitable. At these high frequencies, wavelength becomes small enough to compare with the size of rain drops and in some cases smaller than drop size. This implies that the impairment due to rain, which already usually forms the most severe form of impairment at higher radio frequency bands, will become even more acute and require rigorous parameterization.
This thesis investigates both by rigorous measurements and by theoretical approaches, the attenuation effect of rainfall in a subtropical climate (Durban, South Africa) on a microwave earth-satellite link operating at 12.6 GHz. The link was set up and the received signal level monitored via spectrum analyser sweeps conducted every minute. A Joss-Waldvogel impact disdrometer was installed such that its diaphragm is located a few meters away from the link’s receive antenna. From such a location, all precipitation recorded by the disdrometer are assumed to have some effect on the link. The monthly variation in the received signal during clear air was investigated by taking into consideration the average monthly values of temperature, relative humidity and atmospheric pressure. By employing multiple regression, a linear expression was obtained that can be used to predict the change in received signal level in clear air over the link given the values of these three atmospheric parameters. The attenuation due to the rain events was extracted from the data by carrying out an even-by-event matching of rain rate spikes with the corresponding drop observed in the received signal level at and around the time of the precipitation. The average monthly received signal level during clear air was extracted from the spectrum analyser data and used as the base channel power to which the received signal during rain in the particular month is compared. The difference between the two is stored as the attenuation due to rain in that instant of measurement time. The attenuation data thus accumulated were entered into a computer algorithm and a regression fitting procedure carried out to deduce an empirical set of logarithmic and power law models that relate the total path attenuation to rain rate. The models were then validated by a largely favourable comparison with four existing models, one of which is the in-force ITU-recommended model for slant path attenuation estimations.
Random number properties of rain attenuation statistics obtained from the measurement model were exploited to develop a Markov chain approach by which seasonal and annual slant path rain attenuation time series can be generated. By investigating the nature of the probability distributions of the seasonal and annual measured path attenuation statistics, which was found to be lognormal, the state probability matrix necessary for implementing a Markov chain prediction model for future patterns of rain attenuation on a similar link was obtained as the lognormal probability density function. The state transition probability vector for each time period was developed by extracting the fade slope statistics of the measured attenuation. The discrete-time Gaussian distributed fade slope PDF forms the basis for the state transition probability matrix. With these, Markov-generated time series of seasonal and annual slant path attenuation for up to five iterations were obtained. The results make useful data that can be used for long-term planning for rain fade mitigation in a subtropical climate easier to generate without the expense of measurements.
The theoretical approach called the Synthetic Storm Technique was also applied to investigate the nature of slant path rain attenuation in Durban. Based on the rainfall pattern captured by the disdrometer, SST approximations for the four seasons of the subtropical year and for years of rain data collection were carried out. The results were compared with the values generated from the measurement model. It reveals that the two models exhibit significant agreement because in a majority of the cases, the A0.01 values obtained are very close. Comparison of the performance of SST as a theoretical model with that of the ITU-recommended method also reveals that the ITU performs slightly better as an alternative to measurement than the SST model.
It was observed that during certain precipitation events, the satellite link registers significant attenuation levels several minutes before the disdrometer records any precipitation on the ground. This anomaly was investigated in this work and a few conclusions drawn. By proceeding on the assumption that the observed delay was due to the migrating rain cell interacting with the satellite beam several minutes before reaching the receive antenna, it was demonstrated that the time of delay between precipitation and attenuation is related to the rain height during that particular rain event. A simple mathematical analysis is presented that enables the rain height to be estimated from the delay time. The results obtained range between 1.4 km to 6.7 km which is similarity to rain height values obtained by the ITU model which range from 1.36 km to 6.36 km
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