Doctorat en Teoria del Senyal i Comunicacions
http://hdl.handle.net/2117/184549
20210728T15:14:28Z

Correcting the ADCS jitter induced blurring in small satellite imagery
http://hdl.handle.net/2117/350138
Correcting the ADCS jitter induced blurring in small satellite imagery
Llaveria Godoy, David; Camps Carmona, Adriano José; Hyuk, Park
Earth Observation missions have increasingly demanding requirements, i.e., higher spatial resolutions and SNR, and lower revisit times, etc. Highresolution images have to be captured with precise pointing accuracy which is achieved by the satellite's attitude determination and control system (ADCS). This subsystem embeds multiple sensors and actuators capable of changing the satellite attitude by changing the torque applied to the platform. In small satellites, magnetorquers, and more recently reaction wheels as well, are the most frequently used actuators. These components fulfill their main purpose, but exhibit some drawbacks, notably a nonconstant jitter that provokes nondesired oscillations of the spacecraft, which may result in blurred images. This work presents a deblurring methodology that uses data coming from the ADCS sensors to infer a spatially variant pointspread function. Moreover, the impact of having a lower temporal resolution than the ideal on the sensors is analyzed and a method is presented to improve it.
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20210727T09:26:36Z
Llaveria Godoy, David
Camps Carmona, Adriano José
Hyuk, Park
Earth Observation missions have increasingly demanding requirements, i.e., higher spatial resolutions and SNR, and lower revisit times, etc. Highresolution images have to be captured with precise pointing accuracy which is achieved by the satellite's attitude determination and control system (ADCS). This subsystem embeds multiple sensors and actuators capable of changing the satellite attitude by changing the torque applied to the platform. In small satellites, magnetorquers, and more recently reaction wheels as well, are the most frequently used actuators. These components fulfill their main purpose, but exhibit some drawbacks, notably a nonconstant jitter that provokes nondesired oscillations of the spacecraft, which may result in blurred images. This work presents a deblurring methodology that uses data coming from the ADCS sensors to infer a spatially variant pointspread function. Moreover, the impact of having a lower temporal resolution than the ideal on the sensors is analyzed and a method is presented to improve it.

Characterisation of copper and stainless steel surfaces treated with laser ablation surface engineering
http://hdl.handle.net/2117/350134
Characterisation of copper and stainless steel surfaces treated with laser ablation surface engineering
Hannah, Adrian N.; Krkotic, Patrick; Valizadeh, Reza; Malyshev, Oleg; Mutch, J.; Whitehead, David J.; Pont, Montse; O'Callaghan Castellà, Juan Manuel; Dhanak, Vinod R.
In the past few years, it has been established that Laser Ablation Surface Engineering (LASE) is a very effective way of producing surfaces which have Secondary Electron Yields (SEY)¿<¿1. This can be achieved with a variety of laser pulse durations from nanoto picoseconds. However, the features (i.e. moderately deep grooves and nanoparticulates) that help to reduce the SEY can produce undesirable effects such as an increase in the RF surface resistance. In this paper we discuss the methods employed utilising the dielectric resonator technique to quantify the surface resistance of laser treated copper and stainless steel samples. The quantification is based on a nondestructive measurement of highfrequency losses on the conducting surface. It has been demonstrated that the LASE surface can be produced with SEY<1 and an RF surface resistance of only ~6% higher than that on untreated surfaces. Furthermore, a comparative study of electron stimulated desorption (ESD) between the LASE treated and untreated samples of copper and stainless steel is reported for H2, CH4, CO and CO2. It has been shown that there are negligible differences in ESD between LASE treated and untreated stainless steel. It has been demonstrated that LASEtreated copper samples have a considerable reduction in ESD as compared with untreated sample.
20210727T08:30:54Z
Hannah, Adrian N.
Krkotic, Patrick
Valizadeh, Reza
Malyshev, Oleg
Mutch, J.
Whitehead, David J.
Pont, Montse
O'Callaghan Castellà, Juan Manuel
Dhanak, Vinod R.
In the past few years, it has been established that Laser Ablation Surface Engineering (LASE) is a very effective way of producing surfaces which have Secondary Electron Yields (SEY)¿<¿1. This can be achieved with a variety of laser pulse durations from nanoto picoseconds. However, the features (i.e. moderately deep grooves and nanoparticulates) that help to reduce the SEY can produce undesirable effects such as an increase in the RF surface resistance. In this paper we discuss the methods employed utilising the dielectric resonator technique to quantify the surface resistance of laser treated copper and stainless steel samples. The quantification is based on a nondestructive measurement of highfrequency losses on the conducting surface. It has been demonstrated that the LASE surface can be produced with SEY<1 and an RF surface resistance of only ~6% higher than that on untreated surfaces. Furthermore, a comparative study of electron stimulated desorption (ESD) between the LASE treated and untreated samples of copper and stainless steel is reported for H2, CH4, CO and CO2. It has been shown that there are negligible differences in ESD between LASE treated and untreated stainless steel. It has been demonstrated that LASEtreated copper samples have a considerable reduction in ESD as compared with untreated sample.

RandomWalk laplacian for frequency analysis in periodic graphs
http://hdl.handle.net/2117/350117
RandomWalk laplacian for frequency analysis in periodic graphs
Boukrab, Rachid; Pagès Zamora, Alba Maria
This paper presents the benefits of using the randomwalk normalized Laplacian matrix as a graphshift operator and defines the frequencies of a graph by the eigenvalues of this matrix. A criterion to order these frequencies is proposed based on the Euclidean distance between a graph signal and its shifted version with the transition matrix as shift operator. Further, the frequencies of a periodic graph built through the repeated concatenation of a basic graph are studied. We show that when a graph is replicated, the graph frequency domain is interpolated by an upsampling factor equal to the number of replicas of the basic graph, similarly to the effect of zeropadding in digital signal processing.
20210726T14:30:21Z
Boukrab, Rachid
Pagès Zamora, Alba Maria
This paper presents the benefits of using the randomwalk normalized Laplacian matrix as a graphshift operator and defines the frequencies of a graph by the eigenvalues of this matrix. A criterion to order these frequencies is proposed based on the Euclidean distance between a graph signal and its shifted version with the transition matrix as shift operator. Further, the frequencies of a periodic graph built through the repeated concatenation of a basic graph are studied. We show that when a graph is replicated, the graph frequency domain is interpolated by an upsampling factor equal to the number of replicas of the basic graph, similarly to the effect of zeropadding in digital signal processing.

Sea ice thickness estimation based on regression neural networks using Lband microwave radiometry data from the FSSCat mission
http://hdl.handle.net/2117/350116
Sea ice thickness estimation based on regression neural networks using Lband microwave radiometry data from the FSSCat mission
Herbert, Christoph Josef; Muñoz Martin, Joan Francesc; Llaveria Godoy, David; Pablos, Miriam; Camps Carmona, Adriano José
Several methods have been developed to provide polar maps of sea ice thickness (SIT) from Lband brightness temperature (TB) and altimetry data. Current processbased inversion methods to yield SIT fail to address the complex surface characteristics because sea ice is subject to strong seasonal dynamics and icephysical properties are often nonlinearly related. Neural networks can be trained to find hidden links among large datasets and often perform better on convoluted problems for which traditional approaches miss out important relationships between the observations. The FSSCat mission launched on 3 September 2020, carries the Flexible Microwave Payload2 (FMPL2), which contains the first Reflected Global Navigation Satellite System (GNSSR) and Lband radiometer on board a CubeSat—designed to provide TB data on global coverage for soil moisture retrieval, and sea ice applications. This work investigates a predictive regression neural network approach with the goal to infer SIT using FMPL2 TB and ancillary data (sea ice concentration, surface temperature, and sea ice freeboard). Two models—covering thin ice up to 0.6 m and fullrange thickness—were separately trained on Arctic data in a twomonth period from midOctober to the beginning of December 2020, while using ground truth data derived from the Soil Moisture and Ocean Salinity (SMOS) and Cryosat2 missions. The thin ice and the fullrange models resulted in a mean absolute error of 6.5 cm and 23 cm, respectively. Both of the models allowed for one to produce weekly composites of Arctic maps, and monthly composites of Antarctic SIT were predicted based on the Arctic fullrange model. This work presents the first results of the FSSCat mission over the polar regions. It reveals the benefits of neural networks for sea ice retrievals and demonstrates that moderatecost CubeSat missions can provide valuable data for applications in Earth observation.
20210726T13:42:59Z
Herbert, Christoph Josef
Muñoz Martin, Joan Francesc
Llaveria Godoy, David
Pablos, Miriam
Camps Carmona, Adriano José
Several methods have been developed to provide polar maps of sea ice thickness (SIT) from Lband brightness temperature (TB) and altimetry data. Current processbased inversion methods to yield SIT fail to address the complex surface characteristics because sea ice is subject to strong seasonal dynamics and icephysical properties are often nonlinearly related. Neural networks can be trained to find hidden links among large datasets and often perform better on convoluted problems for which traditional approaches miss out important relationships between the observations. The FSSCat mission launched on 3 September 2020, carries the Flexible Microwave Payload2 (FMPL2), which contains the first Reflected Global Navigation Satellite System (GNSSR) and Lband radiometer on board a CubeSat—designed to provide TB data on global coverage for soil moisture retrieval, and sea ice applications. This work investigates a predictive regression neural network approach with the goal to infer SIT using FMPL2 TB and ancillary data (sea ice concentration, surface temperature, and sea ice freeboard). Two models—covering thin ice up to 0.6 m and fullrange thickness—were separately trained on Arctic data in a twomonth period from midOctober to the beginning of December 2020, while using ground truth data derived from the Soil Moisture and Ocean Salinity (SMOS) and Cryosat2 missions. The thin ice and the fullrange models resulted in a mean absolute error of 6.5 cm and 23 cm, respectively. Both of the models allowed for one to produce weekly composites of Arctic maps, and monthly composites of Antarctic SIT were predicted based on the Arctic fullrange model. This work presents the first results of the FSSCat mission over the polar regions. It reveals the benefits of neural networks for sea ice retrievals and demonstrates that moderatecost CubeSat missions can provide valuable data for applications in Earth observation.

Asymmetrical clipping optical filter bank multicarrier modulation scheme
http://hdl.handle.net/2117/349586
Asymmetrical clipping optical filter bank multicarrier modulation scheme
Ibrahim Mohamed Badr, Asmaa; Prat Gomà, Josep Joan; Ismail, Tawfik
Filter bank multicarrier (FBMC) is considered a promising alternative to the Orthogonal Frequency Division Multiplexing (OFDM) scheme. It improves spectral efficiency by eliminating the need for cyclic prefix while attenuating interference due to the robustness of the outofband emission. In this work, we present a framework, and the performance evaluation of FBMC is a multicarrier modulation scheme for the direct detection of optical communications. As the proposed model has higher spectral efficiency than the classical ACOOFDM, as removing the guard interval enhances the spectral efficiency. Furthermore, the perfect rectangular pulse shaping and eliminating the out of band emission of the filter bank enhances the ACOFBMC the BER performance of the ACOOFDM. We propose a transceiver model for Asymmetrical Clipped Optical FBMC (ACOFBMC) based on Fast Fourier Transform (FFT) operations, analyze interframe interference, and offer an iterative receptive method to eliminate it. Finally, we compared the bit error rate (BER) performance of the ACOFBMC using different overlapping factors with the ACOOFDM.
20210719T06:38:34Z
Ibrahim Mohamed Badr, Asmaa
Prat Gomà, Josep Joan
Ismail, Tawfik
Filter bank multicarrier (FBMC) is considered a promising alternative to the Orthogonal Frequency Division Multiplexing (OFDM) scheme. It improves spectral efficiency by eliminating the need for cyclic prefix while attenuating interference due to the robustness of the outofband emission. In this work, we present a framework, and the performance evaluation of FBMC is a multicarrier modulation scheme for the direct detection of optical communications. As the proposed model has higher spectral efficiency than the classical ACOOFDM, as removing the guard interval enhances the spectral efficiency. Furthermore, the perfect rectangular pulse shaping and eliminating the out of band emission of the filter bank enhances the ACOFBMC the BER performance of the ACOOFDM. We propose a transceiver model for Asymmetrical Clipped Optical FBMC (ACOFBMC) based on Fast Fourier Transform (FFT) operations, analyze interframe interference, and offer an iterative receptive method to eliminate it. Finally, we compared the bit error rate (BER) performance of the ACOFBMC using different overlapping factors with the ACOOFDM.

Machine learning assisted EDFA gain ripple modelling for accurate QoT estimation
http://hdl.handle.net/2117/349161
Machine learning assisted EDFA gain ripple modelling for accurate QoT estimation
Mahajan, Ankush; Christodoulopoulos, Konstantinos; Martínez Rivera, Ricardo Victor; Spadaro, Salvatore; Muñoz González, Raül
Wavelength dependent EDFA gain ripple has an impact on connection's OSNR performance. We propose a machine learning regression model to estimate the end to end gain ripple penalty and to increase QoT estimation accuracy.
20210713T08:38:33Z
Mahajan, Ankush
Christodoulopoulos, Konstantinos
Martínez Rivera, Ricardo Victor
Spadaro, Salvatore
Muñoz González, Raül
Wavelength dependent EDFA gain ripple has an impact on connection's OSNR performance. We propose a machine learning regression model to estimate the end to end gain ripple penalty and to increase QoT estimation accuracy.

Quality of transmission estimator retraining for dynamic optimization in optical networks
http://hdl.handle.net/2117/349149
Quality of transmission estimator retraining for dynamic optimization in optical networks
Mahajan, Ankush; Christodoulopoulos, Konstantinos; Martínez Rivera, Ricardo Victor; Muñoz González, Raül; Spadaro, Salvatore
Optical network optimization involves an algorithm and a physical layer model (PLM) to estimate the quality of transmission of connections while examining candidate optimization operations. In particular, the algorithm typically calculates intermediate solutions until it reaches the optimum, which is then configured to the network. If it uses a PLM that was aligned once to reflect the starting network configuration, then the algorithm within its intermediate calculations can project the network into states where the PLM suffers from low accuracy, resulting in a suboptimal optimization. In this paper, we propose to solve dynamic multivariable optimization problems with an iterative closed control loop process, where after certain algorithm steps we configure the intermediate solution so that we monitor and realign/retrain the PLM to follow the projected network states. The PLM is used as a digital twin, a digital representation of the real system, which is realigned during the dynamic optimization process. Specifically, we study the dynamic launch power optimization problem, where we have a set of established connections, and we optimize their launch powers while the network operates. We observed substantial improvements in the sum and the lowest margin when optimizing the launch powers with the proposed approach over optimization using a onetime trained PLM. The proposed approach achieved neartooptimum solutions as found by optimizing and continuously probing and monitoring the network, but with a substantial lower optimization time.
20210713T07:50:41Z
Mahajan, Ankush
Christodoulopoulos, Konstantinos
Martínez Rivera, Ricardo Victor
Muñoz González, Raül
Spadaro, Salvatore
Optical network optimization involves an algorithm and a physical layer model (PLM) to estimate the quality of transmission of connections while examining candidate optimization operations. In particular, the algorithm typically calculates intermediate solutions until it reaches the optimum, which is then configured to the network. If it uses a PLM that was aligned once to reflect the starting network configuration, then the algorithm within its intermediate calculations can project the network into states where the PLM suffers from low accuracy, resulting in a suboptimal optimization. In this paper, we propose to solve dynamic multivariable optimization problems with an iterative closed control loop process, where after certain algorithm steps we configure the intermediate solution so that we monitor and realign/retrain the PLM to follow the projected network states. The PLM is used as a digital twin, a digital representation of the real system, which is realigned during the dynamic optimization process. Specifically, we study the dynamic launch power optimization problem, where we have a set of established connections, and we optimize their launch powers while the network operates. We observed substantial improvements in the sum and the lowest margin when optimizing the launch powers with the proposed approach over optimization using a onetime trained PLM. The proposed approach achieved neartooptimum solutions as found by optimizing and continuously probing and monitoring the network, but with a substantial lower optimization time.

Data plane elements for optical performance monitoring agnostic to the modulation format for disaggregated optical networks
http://hdl.handle.net/2117/349135
Data plane elements for optical performance monitoring agnostic to the modulation format for disaggregated optical networks
Fàbrega Sánchez, Josep Maria; Locatelli, Fabiano; Nadal Reixats, Laia; Christodoulopoulos, Konstantinos; Svaluto Moreolo, Michela; Spadaro, Salvatore
In this paper, data plane alternatives for optical performance monitoring are presented as enablers to address the key challenges in disaggregated optical networks. In fact, a key element of the disaggregated networks is optical performance monitoring that is expected to deliver the feedback needed by the control plane to guarantee endtoend quality of transmission and quality of service. Therefore, we will discuss data plane elements for nonintrusive monitoring agnostic to the modulation format, proposing and analyzing different schemes. Furthermore, we will also review the relevant figures of merit to be delivered to the /SDN/ control, orchestration and management planes and their potential impact on the network performance.
20210713T07:16:40Z
Fàbrega Sánchez, Josep Maria
Locatelli, Fabiano
Nadal Reixats, Laia
Christodoulopoulos, Konstantinos
Svaluto Moreolo, Michela
Spadaro, Salvatore
In this paper, data plane alternatives for optical performance monitoring are presented as enablers to address the key challenges in disaggregated optical networks. In fact, a key element of the disaggregated networks is optical performance monitoring that is expected to deliver the feedback needed by the control plane to guarantee endtoend quality of transmission and quality of service. Therefore, we will discuss data plane elements for nonintrusive monitoring agnostic to the modulation format, proposing and analyzing different schemes. Furthermore, we will also review the relevant figures of merit to be delivered to the /SDN/ control, orchestration and management planes and their potential impact on the network performance.

Spectral processing techniques for efficient monitoring in optical networks
http://hdl.handle.net/2117/348927
Spectral processing techniques for efficient monitoring in optical networks
Locatelli, Fabiano; Christodoulopoulos, Konstantinos; Svaluto Moreolo, Michela; Fàbrega Sánchez, Josep Maria; Nadal Reixats, Laia; Spadaro, Salvatore
Having ubiquitous optical monitors in dense wavelengthdivision multiplexing (DWDM) or flexgrid networks allows the estimation in real time of crucial parameters. Such monitoring would be even more important in disaggregated optical networks, to inspect performance issues related to intervendor interoperability. Several important parameters can be retrieved using optical spectrum analyzers (OSAs). However, omnipresent OSAs represent an infeasible solution. Nevertheless, the advent of new, relatively cheap, compact and mediumresolution optical channel monitors (OCMs) enable a more intensive deployment of these devices. In this paper, we identify two main scenarios for the placement of such monitors: at the ingress and at the egress of the optical nodes. In the ingress scenario, we can directly estimate the parameters related to the signals, but not those related to the filters. On the contrary, in the egress scenario, the filterrelated parameters can be easily detected, but not those related to amplified spontaneous emission. Therefore, we present two methods that, leveraging a curve fitting and a machine learning regression algorithm, allow detection of the missing parameters. We verify the proposed solutions with spectral data acquired in simulation and experimental setups. We obtained good estimation accuracy for both setups and for both studied placement scenarios. It is noteworthy that in the experimental assessment of the ingress scenario, we achieved a maximum absolute error (MAE) lower than 1 GHz in filter bandwidth estimation and a MAE lower than 0.5 GHz in filter frequency shift estimation. In addition, by comparing the relative errors of the considered parameters, we identified the ingress scenario as the more beneficial. In particular, we estimated the filter central frequency shift with 84% and the filter 6 dB bandwidth with 75% higher accuracy, with respect to datasheet/reference values. This translates into a total reduction of the estimated signaltonoise ratio (SNR) penalty, introduced by a single optical filter, of 0.24 dB.
20210712T07:01:04Z
Locatelli, Fabiano
Christodoulopoulos, Konstantinos
Svaluto Moreolo, Michela
Fàbrega Sánchez, Josep Maria
Nadal Reixats, Laia
Spadaro, Salvatore
Having ubiquitous optical monitors in dense wavelengthdivision multiplexing (DWDM) or flexgrid networks allows the estimation in real time of crucial parameters. Such monitoring would be even more important in disaggregated optical networks, to inspect performance issues related to intervendor interoperability. Several important parameters can be retrieved using optical spectrum analyzers (OSAs). However, omnipresent OSAs represent an infeasible solution. Nevertheless, the advent of new, relatively cheap, compact and mediumresolution optical channel monitors (OCMs) enable a more intensive deployment of these devices. In this paper, we identify two main scenarios for the placement of such monitors: at the ingress and at the egress of the optical nodes. In the ingress scenario, we can directly estimate the parameters related to the signals, but not those related to the filters. On the contrary, in the egress scenario, the filterrelated parameters can be easily detected, but not those related to amplified spontaneous emission. Therefore, we present two methods that, leveraging a curve fitting and a machine learning regression algorithm, allow detection of the missing parameters. We verify the proposed solutions with spectral data acquired in simulation and experimental setups. We obtained good estimation accuracy for both setups and for both studied placement scenarios. It is noteworthy that in the experimental assessment of the ingress scenario, we achieved a maximum absolute error (MAE) lower than 1 GHz in filter bandwidth estimation and a MAE lower than 0.5 GHz in filter frequency shift estimation. In addition, by comparing the relative errors of the considered parameters, we identified the ingress scenario as the more beneficial. In particular, we estimated the filter central frequency shift with 84% and the filter 6 dB bandwidth with 75% higher accuracy, with respect to datasheet/reference values. This translates into a total reduction of the estimated signaltonoise ratio (SNR) penalty, introduced by a single optical filter, of 0.24 dB.

Optical phase effects in reconfigurable microwave photonic filters with multiple wavelength input
http://hdl.handle.net/2117/348085
Optical phase effects in reconfigurable microwave photonic filters with multiple wavelength input
Nuño Gómez, DanielJuan; Santos Blanco, M. Concepción
Microwave photonic filters with a multiple wavelength input are analyzed. A comprehensive model assessing the impact of the phase characteristic of the optical stage is presented from which optimized design rules have been derived. Examples with one, 2 and 3 lasers are provided along with experimental results supporting our findings.
20210629T13:49:34Z
Nuño Gómez, DanielJuan
Santos Blanco, M. Concepción
Microwave photonic filters with a multiple wavelength input are analyzed. A comprehensive model assessing the impact of the phase characteristic of the optical stage is presented from which optimized design rules have been derived. Examples with one, 2 and 3 lasers are provided along with experimental results supporting our findings.