Access profile

Ideal applicants are holders of master’s degrees in Information and Communication Technologies, and preferably Telecommunications Engineering. However, the multidisciplinary nature of some of the Department’s research groups makes it desirable to consider admitting candidates with other degrees in the fields of physics, computing, biology and computational linguistics.

In addition to this academic profile, certain characteristics are considered important for applicants to have, including interest in the research projects being carried out in the Department, having critical and analytical abilities, having initiative, being consistent and persistent in their work and being able to work in a team.

Degree classifications:

• Direct admission: European Master of Science in Research on Information and Communication Technologies (MERIT) and Master of Science in Communication and Network Engineering (COMNET). This last programme has not been submitted for verification, but it is expected to be verified very soon.
• Preferential admission: other postgraduate programmes in the field of ICT engineering: telecommunications engineering, telematic engineering, computer sciences and photonic technologies.
• Others: depending upon the presence of other multidisciplinary research groups in the Department, applicants with degrees from other programmes that do not coincide with the aforementioned profiles will also be considered: informatics, physical sciences, chemistry, mathematics, biology and computational linguistics.

An appropriate level of English is required for this programme.

Output profile

Doctoral candidates who complete a doctoral degree will have acquired the following competencies, which are needed to carry out quality research (Royal Decree 99/2011, of 28 January, which regulates official doctoral studies):

a) A systematic understanding of the field of study and a mastery of the research skills and methods related to the field.
b) An ability to conceive, design or create, put into practice and adopt a substantial process of research or creation.
c) An ability to contribute to pushing back the frontiers of knowledge through original research.
d) A capacity for critical analysis and an ability to assess and summarise new and complex ideas.
e) An ability to communicate with the academic and scientific community and with society in general as regards their fields of knowledge in the manner and languages that are typical of the international scientific community to which they belong.
f) An ability to foster scientific, technological, social, artistic and cultural progress in academic and professional contexts within a knowledge-based society.

The award of a doctoral degree must equip the graduate for work in a variety of settings, especially those requiring creativity and innovation. Doctoral graduates must have at least acquired the personal skills needed to:

a) Develop in contexts in which there is little specific information.
b) Find the key questions that must be answered to solve a complex problem.
c) Design, create, develop and undertake original, innovative projects in their field.
d) Work as part of a team and independently in an international or multidisciplinary context.
e) Integrate knowledge, deal with complexity and make judgements with limited information.
f) Offer criticism on and intellectually defend solutions.

Finally, with respect to competencies, doctoral students must:
a) have acquired advanced knowledge at the frontier of their discipline and demonstrated, in the context of internationally recognised scientific research, a deep, detailed and well-grounded understanding of theoretical and practical issues and scientific methodology in one or more research fields;
b) have made an original and significant contribution to scientific research in their field of expertise that has been recognised as such by the international scientific community;
c) have demonstrated that they are capable of designing a research project that serves as a framework for carrying out a critical analysis and assessment of imprecise situations, in which they are able to apply their contributions, expertise and working method to synthesise new and complex ideas that yield a deeper knowledge of the research context in which they work;
d) have developed sufficient autonomy to set up, manage and lead innovative research teams and projects and scientific collaborations (both national and international) within their subject area, in multidisciplinary contexts and, where appropriate, with a substantial element of knowledge transfer;
e) have demonstrated that they are able to carry out their research activity in a socially responsible manner and with scientific integrity;
f) have demonstrated, within their specific scientific context, that they are able to make cultural, social or technological advances and promote innovation in all areas within a knowledge-based society;
g) have demonstrated that they are able to participate in scientific discussions at the international level in their field of expertise and disseminate the results of their research activity to audiences of all kinds.

Number of places

30

Duration of studies and dedication regime

Duration
The maximum period of study for full-time doctoral studies is three years, counted from the date of admission to the programme to the date of submission of the doctoral thesis. The academic committee of the doctoral programme may authorise a doctoral candidate to pursue doctoral studies on a part-time basis. In this case, the maximum period of study is five years, counting from the date of admission to the programme to the date of submission of the doctoral thesis. For calculating these periods, the date of admission is considered to be the date of the first enrolment for tutorials, and the date of submission the moment in which the Doctoral School officially deposits the doctoral thesis.

For full-time doctoral candidates, the minimum period of study is two years, counted from the date of an applicant's admission to the programme until the date on which the doctoral thesis is deposited; for part-time doctoral candidates it is four years. When there are justified grounds for doing so, and the thesis supervisor and academic tutor have given their authorisation, doctoral candidates may request that the academic committee of their doctoral programme exempt them from the minimum period of study requirement.

The calculation of periods of study will not include periods of absence due to illness, pregnancy or any other reason provided for in the regulations in force. Students who find themselves in any of these circumstances must notify the academic committee of the doctoral programme, which, where appropriate, must inform the Doctoral School. Doctoral candidates may also temporarily withdraw from the programme for up to one year, and this period may be extended for an additional year. Doctoral candidates who wish to interrupt their studies must submit a justified request to the academic committee of the doctoral programme, which will decide whether or not to approve the request. Each programme will establish conditions for readmission to doctoral studies.

Extension
If full-time doctoral candidates have not applied to deposit their thesis by the end of the three-year period of study, the academic committee of the programme may authorise an extension of up to one year. In exceptional circumstances, a further one-year extension may be granted, subject to the conditions established by the corresponding doctoral programme. In the case of part-time doctoral candidates, an extension of two years may be authorised. In both cases, in exceptional circumstances a further one-year extension may be granted by the Doctoral School's Standing Committee, upon the submission of a reasoned application by the academic committee of the doctoral programme.

Dismissal from the doctoral programme
A doctoral candidate may be dismissed from a doctoral programme for the following reasons:

• The doctoral candidate submitting a justified application to withdraw from the programme.
• The maximum period of study and of extensions thereof ending.
• The doctoral candidate not having enrolled every academic year (unless he or she has been authorised to temporarily withdraw).
• The doctoral candidate failing two consecutive assessments.
• The doctoral candidate having disciplinary proceedings filed against him or her that rule that he or she must be dismissed from the UPC.

Dismissal from the programme implies that doctoral candidates cannot continue studying at the UPC and the closing of their academic record. This notwithstanding, they may apply to the academic committee of the programme for readmission and the committee must reevaluate them in accordance with the criteria established in the regulations.

Organization

• Comellas Colome, Jaume

• Ferrus Ferre, Ramon
• Rey Micolau, Francesc
• Rodriguez Gomez, Alejandro
• Vall-Llossera Ferran, Mercè

• Department of Signal Theory and Communications (PROMOTORA)

Doctoral Unit - ICT North Campus Management and Support Unit (UTGCNTIC)

C. Jordi Girona, 1-3. Building B4-003 (North Campus)
Tel.: 934 017 233
E-mail: doctorat.tsc@upc.edu

Access profile

Ideal applicants are holders of master’s degrees in Information and Communication Technologies, and preferably Telecommunications Engineering. However, the multidisciplinary nature of some of the Department’s research groups makes it desirable to consider admitting candidates with other degrees in the fields of physics, computing, biology and computational linguistics.

In addition to this academic profile, certain characteristics are considered important for applicants to have, including interest in the research projects being carried out in the Department, having critical and analytical abilities, having initiative, being consistent and persistent in their work and being able to work in a team.

Degree classifications:

• Direct admission: European Master of Science in Research on Information and Communication Technologies (MERIT) and Master of Science in Communication and Network Engineering (COMNET). This last programme has not been submitted for verification, but it is expected to be verified very soon.
• Preferential admission: other postgraduate programmes in the field of ICT engineering: telecommunications engineering, telematic engineering, computer sciences and photonic technologies.
• Others: depending upon the presence of other multidisciplinary research groups in the Department, applicants with degrees from other programmes that do not coincide with the aforementioned profiles will also be considered: informatics, physical sciences, chemistry, mathematics, biology and computational linguistics.

An appropriate level of English is required for this programme.

Access requirements

Applicants must hold a Spanish bachelor’s degree or equivalent and a Spanish master’s degree or equivalent, provided they have completed a minimum of 300 ECTS credits on the two degrees (Royal Decree 43/2015, of 2 February)

In addition, the following may apply:

• Holders of an official degree awarded by a university in Spain or any other country in the European Higher Education Area, pursuant to the provisions of Article 16 of Royal Decree 1393/2007, of 29 October, which establishes official university course regulations, who have completed a minimum of 300 ECTS credits on official university degrees, of which at least 60 must be at the master's degree level.
• Holders of an official Spanish bachelor’s degree comprising at least 300 credits, as provided for by EU regulations. Holder of degrees of this kind must complete bridging courses unless the curriculum of the bachelor’s degree in question included research training credits equivalent in value to those which would be earned on a master's degree.
• Holders of an official university qualification who, having passed the entrance examination for specialised medical training, have completed at least two years of a training course leading to an official degree in a health-sciences specialisation.
• Holders of a degree issued under a foreign education system. In these cases, homologation is not required, but the UPC must verify that the degree certifies a level of training equivalent to an official Spanish master's degree and qualifies the holder for admission to doctoral studies in the country where it was issued. Admission on this basis does not imply homologation of the foreign degree or its recognition for any purpose other than admission to doctoral studies.
• Holders of a Spanish doctoral qualification issued under previous university regulations.

Note 1: Doctoral studies entrance regulations for holders of an undergraduate degree awarded before the introduction of the EHEA (CG 47/02 2014)

Note 2: Governing Council Decision 64/2014, which approves the procedure and criteria for assessing the fulfilment of academic admission requirements for doctoral studies by holders of non-homologated foreign degrees (CG 25/03 2014)

Admission criteria and merits assessment

• Appropriateness of academic background with the activities carried out in the proposed research group: 25%.
• Knowledge of the English language: 20%.
• Quality of university from which previous degree was awarded: 10%.
• Motivation letter/letters of recommendation: 10%.

An assessment will be considered positive is an applicant is given a score of 3 or more out of 5.

Based on the content of the motivation letter and the applicant’s preparedness, the Postgraduate Committee will assign a thesis supervisor.

If candidates do not have a degree in some kind of ICT engineering, they will have to take the bridging courses recommended by their supervisors and the programme, whether courses from the associated master’s programmes (MET, MATT) or other ones.

Training complements

The Postgraduate Committee of the Signal Theory and Communications Department may require candidates to complete specific bridging courses. In this case, the Committee will monitor the bridging courses and set up appropriate criteria to limit their length.

The courses shall involve training in research, but in no case will candidates be required to enrol in 60 or more ECTS credits (according to the academic regulations for doctoral studies, bridging courses could include transversal education, but there are plans to change to this so that these bridging courses exclusively provide research credits, especially in cases involving doctoral programmes with 300 ECTS credits).

Depending on the activities completed by the candidates, the Postgraduate Committee of the Signal Theory and Communications Department may propose measures, in addition to those established by current regulations, that would disassociate candidates who do not meet the established requisites.

The Postgraduate Committee may require candidates who are to be admitted to complete certain bridging courses in order to better adapt their profiles to the programme’s requirements regarding the knowledge necessary to properly complete the doctoral studies.

No bridging courses will be required for those who graduated from the MET, MASTEAM or MATT programmes, or any of the other previously mentioned ICT programmes.

For those who completed other programmes, the bridging coursework required will depend upon their backgrounds and the activities carried out by the research groups in which they will participate, and it could be up to 30 ECTS.

The courses to be taken are offered by the MET, MASTEAM or MATT programmes.

Also, depending on the characteristics of some of the Department’s research groups, courses from the following UPC programmes will also be considered:
• Master’s programme in Telecommunications Engineering
• Master’s programme in Electrical Engineering
• Master’s programme in Photonics
• Master’s programme in Innovation and Research in Informatics
• Master’s programme in Artificial Intelligence

After consulting with candidates’ supervisors, it will be the sole responsibility of the TSC Department’s Postgraduate Committee to determine which courses students will have to take to complete these bridging courses. In any case, the aim of the courses will always be to fill in the gaps that students are seen to have in their academic transcripts with regard to the activities carried out by the research group in which they will participate.

Enrolment period for new doctoral students

Students enrolling in the doctoral programme for the first time must do so by the deadline specified in the admission decision.
Unless otherwise expressly indicated, enrolments corresponding to admission decisions issued from the second half of April on must be completed within the ordinary enrolment period for the current academic year.

More information at the registration section for new doctoral students

Enrolment period

Ordinary period for second and successive enrolments: first half of October.

More information at the general registration section

Procedure for the preparation and defense of the research plan

Doctoral candidates must submit a research plan, which will be included in their doctoral student activity report, before the end of the first year. The plan may be improved over the course of the doctoral degree. It must be endorsed by the tutor and the supervisor, and it must include the method that is to be followed and the aims of the research.

At least one of these annual assessments will include a public presentation and defence of the research plan and work done before a committee composed of three doctoral degree holders, which will be conducted in the manner determined by each academic committee. The examination committee awards a Pass or Fail mark. A Pass mark is a prerequisite for continuing on the doctoral programme. Doctoral candidates awarded a Fail mark must submit a new research plan for assessment by the academic committee of the doctoral programme within six months.

The committee assesses the research plan every year, in addition to all of the other activities in the doctoral student activity report. Doctoral candidates who are awarded two consecutive Fail marks for the research plan will be obliged to definitely withdraw from the programme.

If they change the subject of their thesis, they must submit a new research plan.

Formation activities

Activity: Tutorial.
- Hours: 288.
- Type: compulsory.

Activity: Mobility.
- Hours: 480.
- Type: optional.

Activity: Assessment based on doctoral student activity report (DAD) and research plan.
- Hours: 4.
- Type: compulsory.

Activity: Training in information skills.
- Hours: 1,5.
- Type: compulsory.

Activity: Research methodology.
- Hours: 12.
- Type: compulsory.

Activity: Innovation and creativity.
- Hours: 8.
- Type: optional.

Activity: Language and communication skills.
- Hours: 18.
- Type: optional.

Activity: Courses and seminars.
- Hours: 50.
- Type: optional.

Activity: Workshops.
- Hours: 8.
- Type: optional.

Procedure for assignment of tutor and thesis director

The academic committee of the doctoral programme assigns a thesis supervisor to each doctoral candidate when they are admitted or enrol for the first time, taking account of the thesis supervision commitment referred to in the admission decision.

The thesis supervisor will ensure that training activities carried out by the doctoral candidate are coherent and suitable, and that the topic of the candidate’s doctoral thesis will have an impact and make a novel contribution to knowledge in the relevant field. The thesis supervisor will also guide the doctoral candidate in planning the thesis and, if necessary, tailoring it to any other projects or activities undertaken. The thesis supervisor will generally be a UPC professor or researcher who holds a doctoral degree and has documented research experience. This includes PhD-holding staff at associated schools (as determined by the Governing Council) and UPC-affiliated research institutes (in accordance with corresponding collaboration and affiliation agreements). When thesis supervisors are UPC staff members, they also act as the doctoral candidate’s tutor.

PhD holders who do not meet these criteria (as a result of their contractual relationship or the nature of the institution to which they are attached) must be approved by the UPC Doctoral School's Standing Committee in order to participate in a doctoral programme as researchers with documented research experience.

The academic committee of the doctoral programme may approve the appointment of a PhD-holding expert who is not a UPC staff member as a candidate’s thesis supervisor. In such cases, the prior authorisation of the UPC Doctoral School's Standing Committee is required. A UPC staff member who holds a doctoral degree and has documented research experience must also be proposed to act as a co-supervisor, or as the doctoral candidate’s tutor if one has not been assigned.

A thesis supervisor may step down from this role if there are justified reasons (recognised as valid by the committee) for doing so. If this occurs, the academic committee of the doctoral programme will assign the doctoral candidate a new thesis supervisor.

Provided there are justified reasons for doing so, and after hearing any relevant input from the doctoral candidate, the academic committee of the doctoral programme may assign a new thesis supervisor at any time during the period of doctoral study.

If there are academic reasons for doing so (an interdisciplinary topic, joint or international programmes, etc.) and the academic committee of the programme gives its approval, an additional thesis supervisor may be assigned. Supervisors and co-supervisors have the same responsibilities and academic recognition.

The maximum number of supervisors of a doctoral thesis is two: a supervisor and a co-supervisor.

For theses carried out under a cotutelle agreement or as part of an Industrial Doctorate, if necessary and if the agreement foresees it this maximum number of supervisors may not apply. This notwithstanding, the maximum number of supervisors belonging to the UPC is two.

More information at the PhD theses section

Permanence

The academic committee of the programme may authorise an extension of up to one year for full-time doctoral candidates who have not applied to deposit their thesis by the end of the three-year period of study, in the terms outlined in the Academic Regulations for Doctoral Studies of the Universitat Politècnica de Catalunya. In the case of part-time candidates, an extension of two years may be authorised. In both cases, in exceptional circumstances a further one-year extension may be granted by the Doctoral School's Standing Committee, upon the submission of a reasoned application by the academic committee of the doctoral programme.

A doctoral candidate may be dismissed from a doctoral programme for the following reasons:

• The doctoral candidate submitting a justified application to withdraw from the programme.
• The maximum period of study and of extensions thereof ending.
• The doctoral candidate not having enrolled every academic year (unless he or she has been authorised to temporarily withdraw).
• The doctoral candidate failing two consecutive assessments.
• The doctoral candidate having disciplinary proceedings filed against him or her that rule that he or she must be dismissed from the UPC.

Dismissal from the programme implies that doctoral candidates cannot continue studying at the UPC and the closing of their academic record. This notwithstanding, they may apply to the academic committee of the programme for readmission and the committee must reevaluate them in accordance with the criteria established in the regulations.

International Mention

The doctoral degree certificate may include International Doctorate mention. In this case, the doctoral candidate must meet the following requirements:

a) During the period of study leading to the award of the doctoral degree, the doctoral candidate must have spent at least three months at a respected higher education institution or research centre outside Spain to complete courses or do research work. The stays and activities carried out must be endorsed by the thesis supervisor and authorised by the academic committee of the programme. The candidate must provide a certifying document issued by the person responsible for the research group of the body or bodies where the stay or activity was completed. This information will be added to the doctoral student’s activity report.
b) Part of the thesis (at least the summary and conclusions) must be written and presented in one of the languages commonly used for science communication in the relevant field of knowledge, which must not be an official language of Spain. This rule does not apply to stays and reports in Spanish or to experts from Spanish-speaking countries.
c) At least two PhD-holding experts belonging to a higher education institution or research centre outside Spain must have issued officially certified reports on the thesis.
d) The thesis examination committee must have included at least one PhD-holding expert from a higher education or research institution outside Spain who was not responsible for the candidate’s stay abroad (point a) above).
e) The thesis defence must have taken place on UPC premises or, in the case of joint programmes, at the location specified in the collaboration agreement.

List of authorized thesis for defense

• GARCÍA PASTOR, DAVID: Nonlinear analysis of electro-acoustic frequency-selective devices for communications
  
  Author: GARCÍA PASTOR, DAVID
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS
  Department: Department of Signal Theory and Communications (TSC)
  Mode: Confidentiality
  Deposit date: 03/02/2021
  Reading date: 09/03/2021
  Reading time: 14:00
  Reading place: Aula Teleensenyament - B3 - ETSETB - Campus Nord - videoconferència: meet.google.com/frc-hbet-ydy
  Thesis director: MATEU MATEU, JORDI | COLLADO GOMEZ, JUAN CARLOS
  Committee:
       PRESIDENT: AIGNER, ROBERT
       SECRETARI: UBEDA FARRE, EDUARDO
       VOCAL NO PRESENCIAL: MIREA, TEONA
  Thesis abstract: Nowadays, mobile devices have become a key technology in our lives, making us become part of a connected world, in which millions of mobile handsets are sold every year. In order to satisfy the user demands, many mobile communication standards are working together in the same device (LTE-A, 5G-NR, IEEE Wireless LAN Standards, etc.). High data rates are demanded for different wireless services working on a very crowded frequency spectrum, where all the devices and systems need to operate at the same time without detrimental of mutual interference. Although this major objective has to be faced from different perspectives, such as new modulations and new networking protocols, the radio frequency (RF) and microwave components, forming the communication chain in a transceiver, play a significant role on the whole system performance. Passive devices, like filters, contribute to the signal degradation due to passive intermodulation (PIM). PIM can be generated by the lack of mismatch between metallic contacts, oxidation, or basically, by the inherent nonlinear material properties used on the fabrication of the devices. Although the impact of PIM is lower than the distortion introduced by active devices, for current wireless services and their demanding requirements, any type of nonlinear generation is certainly an issue.Acoustic wave (AW) devices have become a fundamental technology for portable handsets supporting current wireless communication networks. Bulk Acoustic Wave (BAW) has become the main technology nowadays for high frequency filters. This technology allows a high degree of miniaturization, easily making more than 40 filters per device, and also gives other advantages as low insertion losses and multiple frequency operation. Despite these major advantages, BAW resonators exhibit a nonlinear behavior, i.e., they may suffer of intermodulation and harmonic distortion, which might become a real bottle neck for the full expansion of the technology in the ever increasing stringent requirements.The aim of this thesis is focused on characterizing this nonlinear limitation, quite present in acoustic resonators, by defining the origin of different nonlinear manifestations in BAW resonators, and providing new nonlinear models to reduce the computational time required to simulate those undesired effects.The first part of this work explains the basic knowledge about acoustic propagation and piezoelectricity, presenting the linear and nonlinear constitutive equations, including the typical nonlinear manifestations appearing in those devices. Then, the typical circuit models for AW devices and, more specifically its applicability to BAW devices, is presented.The second part of this work is focused on the nonlinear analysis of BAW resonators, by measuring different nonlinear manifestation of 8 different BAW devices, identifying the origin of the nonlinear effects and demonstrating that this unique hypothesis is consistent with those manifestations for all the measured resonators.
  

Last update: 04/03/2021 06:04:23.

List of lodged theses

• GIRBAU XALABARDER, ANDREU: Sports broadcasting and multiple object tracking with deep learning methods
  
  Author: GIRBAU XALABARDER, ANDREU
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS
  Department: Department of Signal Theory and Communications (TSC)
  Mode: Confidentiality
  Deposit date: 19/02/2021
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: MARQUES ACOSTA, FERNANDO | GIRÓ NIETO, XAVIER | RIUS FERRER, IGNASI
  Committee:
       PRESIDENT: SALGADO ALVAREZ DE SOTOMAYOR, LUIS
       SECRETARI: SALEMBIER CLAIRON, PHILIPPE
       VOCAL: CALDERERO PATINO, FELIPE
  Thesis abstract: Since less than a decade ago, deep learning techniques started to dominate many different fields, revolutionizing the possibilities of artificial intelligence. Seeing their potential, industrial sectors started to invest in applying such technologies as key components of the company strategy. This thesis has been developed in an industrial context, in AutomaticTV. The main focus along this period has been the transfer of knowledge and know-how between academia and industry, development of tools to exploit this knowledge, the exploration of new techniques for future challenges, and, from an academic research perspective, contributions to the multiple object tracking problem.The first part of the thesis is devoted to the introduction of deep learning technologies to AutomaticTV, a company dedicated to automatic sports analysis and broadcasting, and the development of tools and tasks that surround the application.The second part of this thesis introduces the contributions to the multiple object tracking challenge. We present TrajE, a trajectory estimator based on mixture density networks and beam search, used to boost the performance of existing multiple object trackers, and introduce an occlusion reconstruction step using the estimated trajectory information. By adding TrajE to an existing multiple object tracker, we boost its performance by 6.3, 1.8 points in MOTA and IDF1 scores respectively, becoming the new state of the art in the MOTChallenge dataset.
  

Last update: 04/03/2021 06:03:35.

List of defended theses by year

• GIMÉNEZ FEBRER, PEDRO JUAN: Matrix completion with prior information in reproducing kernel Hilbert spaces
  
  Author: GIMÉNEZ FEBRER, PEDRO JUAN
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS
  Department: Department of Signal Theory and Communications (TSC)
  Mode: Normal
  Reading date: 11/02/2021
  Thesis director: PAGES ZAMORA, ALBA MARIA
  

  Committee:
       PRESIDENT: GARCÍA MARQUÉS, ANTONIO
       SECRETARI: RODRIGUEZ FONOLLOSA, JAVIER
       VOCAL NO PRESENCIAL: ROMERO GONZÁLEZ, DANIEL
  Thesis abstract: In matrix completion, the objective is to recover an unknown matrix from a small subset of observed entries. Most successful methods for recovering the unknown entries are based on the assumption that the unknown full matrix has low rank. By having low rank, each of its entries are obtained as a function of a small number of coefficients which can be accurately estimated provided that there are enough available observations. Hence, in low-rank matrix completion the estimate is given by the matrix of minimum rank that fits the observed entries.Besides low rankness, the unknown matrix might exhibit other structural properties which can be leveraged in the recovery process. In a smooth matrix, it can be expected that entries that are close in index distance will have similar values. Similarly, groups of rows or columns can be known to contain similarly valued entries according to certain relational structures. This relational information is conveyed through different means such as covariance matrices or graphs, with the inconvenient that these cannot be derived from the data matrix itself since it is incomplete. Hence, any knowledge on how the matrix entries are related among them must be derived from prior information. This thesis deals with matrix completion with prior information, and presents an outlook that generalizes to many situations. In the first part, the columns of the unknown matrix are cast as graph signals with a graph known beforehand. In this, the adjacency matrix of the graph is used to calculate an initial point for a proximal gradient algorithm in order to reduce the iterations needed to converge to a solution. Then, under the assumption that the graph signals are smooth, the graph Laplacian is incorporated into the problem formulation with the aim to enforce smoothness on the solution. This results in an effective denoising of the observed matrix and reduced error, which is shown through theoretical analysis of the proximal gradient coupled with Laplacian regularization, and numerical tests. The second part of the thesis introduces a framework to exploit prior information through reproducing kernel Hilbert spaces. Since a kernel measures similarity between two points in an input set, it enables the encoding of any prior information such as feature vectors, dictionaries or connectivity on a graph. By associating each column and row of the unknown matrix with an item in a set, and defining a pair of kernels measuring similarity between columns or rows, the missing entries can be extrapolated by means of the kernel functions. A method based on kernel regression is presented, with two additional variants aimed at reducing computational cost, and online implementation. These methods prove to be competitive with existing techniques, especially when the number of observations is very small. Furthermore, mean-square error and generalization error analyses are carried out, shedding light on the factors impacting algorithm performance. For the generalization error analysis, the focus is on the transductive case, which measures the ability of an algorithm to transfer knowledge from a set of labelled inputs to an unlabelled set. Here, bounds are derived for the proposed and existing algorithms by means of the transductive Rademacher complexity, and numerical tests confirming the theoretical findings are presented. Finally, the thesis explores the question of how to choose the observed entries of a matrix in order to minimize the recovery error of the full matrix. A passive sampling approach is presented, which entails that no labelled inputs are needed to design the sampling distribution; only the input set and kernel functions are required. The approach is based on building the best Nyström approximation to the kernel matrix by sampling the columns according to their leverage scores, a metric that arises naturally in the theoretical analysis to find an optimal sampling distribution.
  

• HUELTES ESCOBAR, ALBERTO: Synthesis of acoustic wave filters. Ladder and transversal topologies. Towards a practical implementation
  
  Author: HUELTES ESCOBAR, ALBERTO
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS
  Department: Department of Signal Theory and Communications (TSC)
  Mode: Confidentiality
  Reading date: 05/02/2021
  Thesis director: COLLADO GOMEZ, JUAN CARLOS | MATEU MATEU, JORDI
  

  Committee:
       PRESIDENT: AIGNER, ROBERT
       SECRETARI: GILABERT PINAL, PERE LLUIS
       VOCAL NO PRESENCIAL: VILLANUEVA TORRIJO, LUIS GUILLERMO
  Thesis abstract: The meteoric growth of the mobile communication market for the last three decades has been strongly related with the evolution of the electroacoustic (EA) filter technology. With way over 5 billion cell phone users worldwide in 2017 and 5G standard in the horizon, the radiofrequency spectrum is becoming increasingly crowded whereas demand for mobile data has no expected limits in the short to medium term.In this scenario, where a unique filter needs to be designed for each band of operation, requirements for advanced filtering solutions continue to grow as well as the average value of the RF solutions and the RF content per mobile device.RF and microwave devices based on EA resonators such as Bulk Acoustic Wave (BAW) and Surface Acoustic Wave (SAW) filters overcame the limitations of the existent technologies back in the 1980¿s thanks to its compatibility with the manufacturing process of standard Silicon Integrated Circuits (Si-IC).Nowadays sophisticated RF Front-End (RFFE) Modules based on System-in-Package (SiP) are the key solution to integrate the increasing number of electronic parts - Power Amplifiers (PAs), Low Noise Amplifiers (LNAs) and switches - that accompanies acoustic filtering devices like filters, duplexers and multiplexers.Even though the level of complexity and accuracy present on the current EA devices is extraordinary, the design procedures for acoustic filters are still based on the optimization of built-in performance parameters from behavior-based compact models of resonators and the success on this duty relies mostly on the expertise of the designers. However due to the stringent technological constrains and the increasing complexity of the RFFE module architectures devoted to satisfy demanding specifications of the current and forthcoming communications standards, the challenging work of the designers is never getting easier. The aim of this work is focused on providing valuable insights that might help to overcome some of the existent limitations in the design of EA filters. Wider bandwidths, prescribed inclusion of external elements or multiplexing features are taken into consideration. On one hand we show a synthesis formulation and an automated procedure to carry out the synthesis for current well-known topologies, i.e. ladder, taking into consideration realistic values and specifications. On the other hand, a synthesis formulation for novel topologies, named here transversal, is provided. Success of this novel topology will certainly help to guarantee the prevalence of EA filters in the future communication standards, along with the extension to other applications with more stringent requirements and different operating frequencies. The first part of the work is devoted to explain the basic theory related to filter synthesis and its applicability to filters based on EA resonators. Subsequent chapters elaborate the theory to explain the procedures followed to obtain both synthesis and their limitations. Finally, a Chapter devoted to study cases shows the results of applying the filter synthesis to real case scenarios.
  

• KHAN, UMAIR: Self-supervised Deep Learning Approaches To Speaker Recognition
  
  Author: KHAN, UMAIR
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS
  Department: Department of Signal Theory and Communications (TSC)
  Mode: Normal
  Reading date: 11/01/2021
  Thesis director: HERNANDO PERICAS, FRANCISCO JAVIER
  

  Committee:
       PRESIDENT: GONZÁLEZ RODRÍGUEZ, JOAQUÍN
       SECRETARI: LUQUE SERRANO, JORGE
       VOCAL NO PRESENCIAL: GHAHABI ESFAHANI, OMID
  Thesis abstract: In speaker recognition, i-vectors have been the state-of-the-art unsupervised technique over the last few years, whereas x-vectors is becoming the state-of-the-art supervised technique, these days. Recent advances in Deep Learning (DL) approaches to speaker recognition have improved the performance but are constrained to the need of labels for the background data. In practice, labeled background data is not easily accessible, especially when large training data is required. In i-vector based speaker recognition, cosine and Probabilistic Linear Discriminant Analysis (PLDA) are the two basic scoring techniques. Cosine scoring is unsupervised whereas PLDA parameters are typically trained using speaker-labeled background data. This makes a big performance gap between these two scoring techniques. The question is: how to fill this performance gap without using speaker labels for the background data? In this thesis, the above mentioned problem has been addressed using DL approaches without using and/or limiting the use of labeled background data. Three DL based proposals have been made.In the first proposal, a Restricted Boltzmann Machine (RBM) vector representation of speech is proposed for the tasks of speaker clustering and tracking in TV broadcast shows. This representation is referred to as RBM vector. The experiments on AGORA database show that in speaker clustering the RBM vectors gain a relative improvement of 12% in terms of Equal Impurity (EI). For speaker tracking task RBM vectors are used only in the speaker identification part, where the relative improvement in terms of Equal Error Rate (EER) is 11% and 7% using cosine and PLDA scoring, respectively.In the second proposal, DL approaches are proposed in order to increase the discriminative power of i-vectors in speaker verification. We have proposed the use of autoencoder in several ways. Firstly, an autoencoder will be used as a pre-training for a Deep Neural Network (DNN) using a large amount of unlabeled background data. Then, a DNN classifier will be trained using relatively small labeled data. Secondly, an autoencoder will be trained to transform i-vectors into a new representation to increase their discriminative power. The training will be carried out based on the nearest neighbor i-vectors which will be chosen in an unsupervised manner. The evaluation was performed on VoxCeleb-1 database. The results show that using the first system, we gain a relative improvement of 21% in terms of EER, over i-vector/PLDA. Whereas, using the second system, a relative improvement of 42% is gained. If we use the background data in the testing part, a relative improvement of 53% is gained.In the third proposal, we will train a self-supervised end-to-end speaker verification system. The idea is to utilize impostor samples along with the nearest neighbor samples to make client/impostor pairs in an unsupervised manner. The architecture will be based on a Convolutional Neural Network (CNN) encoder, trained as a siamese network with two branch networks. Another network with three branches will also be trained using triplet loss, in order to extract unsupervised speaker embeddings. The experimental results show that both the end-to-end system and the speaker embeddings, despite being unsupervised, show a comparable performance to the supervised baseline. Moreover, their score combination can further improve the performance.The proposed approaches for speaker verification have respective pros and cons. The best result was obtained using the nearest neighbor autoencoder with a disadvantage of relying on background i-vectors in the testing. On the contrary, the autoencoder pre-training for DNN is not bound by this factor but is a semi-supervised approach. The third proposal is free from both these constraints and performs pretty reasonably. It is a self-supervised approach and it does not require the background i-vectors in the testing phase.
  

Last update: 04/03/2021 06:03:00.

Research groups

• ANTENNALAB-Antennas and Wireless Systems Laboratory
• CommSensLab-UPC-Centre Especific de Recerca en Comunicacio i Deteccio UPC
• CSC-Components and Systems for Communications Research Group
• GCO-Optical Communications Group
• GPI-Image and Video Processing Group
• GRCM-Mobile Communication Reserach Group
• RF&MW-Laboratory of RF & microwave systems, devices and materials
• RSLAB-Remote Sensing Lab
• SPCOM-Signal Processing and Communications Group
• VEU-Speech Processing Group
• WiComTec-Wireless Communications and Technologies Research Group

Teachers

• Aguasca Sole, Alberto
• Agusti Comes, Ramon
• Alonso Zarate, Lluis
• Artigas Garcia, David
• Barlabe Dalmau, Antoni
• Belmonte Molina, Aniceto
• Bertran Alberti, Eduard
• Blanch Boris, Sebastián
• Broquetas Ibars, Antoni
• Cabrera Bean, Marga
• Camps Carmona, Adriano Jose
• Casadevall Palacio, Ferran
• Casas Pla, Josep Ramon
• Collado Gomez, J.Carlos
• Comellas Colome, Jaume
• Comeron Tejero, Adolfo
• Corbella Sanahuja, Ignasi
• Dios Otin, Victor Federico
• Duffo Ubeda, Nuria
• Fabregas Canovas, Francisco Javier
• Fernandez Rubio, Juan-Antonio
• Ferrus Ferre, Ramon
• Garcia Lozano, Mario
• Garcia Vizcaino, David
• Gasull Llampallas, Antoni
• Gelonch Bosch, Antoni
• Gene Bernaus, Joan M.
• Gilabert Pinal, Pere Lluis
• Giro Nieto, Xavier
• Gonzalez Arbesu, Jose Maria
• Heldring, Alexander
• Hernando Pericas, Francisco Javier
• Jofre Roca, Lluis
• Junyent Giralt, Gabriel
• Lagunas Hernandez, M. A.
• Lamarca Orozco, Meritxell
• Lazaro Villa, Jose Antonio
• Lopez Martinez, Carlos
• Mallorqui Franquet, Jordi Joan
• Marques Acosta, Ferran
• Mateu Mateu, Jordi
• Monte Moreno, Enric
• Montoro Lopez, Gabriel
• Moreno Bilbao, M. Asuncion
• Morros Rubio, Ramon
• Muñoz Medina, Olga
• Nadeu Camprubi, Climent
• Najar Marton, Montse
• O'callaghan Castella, Joan
• Olmos Bonafe, Juan Jose
• Pages Zamora, Alba
• Pardas Feliu, Montse
• Pascual Iserte, Antonio
• Perez Neira, Ana Isabel
• Perez Pueyo, Rosanna
• Perez Romero, Jordi
• Perez Torres, Juan
• Pradell Cara, Lluis
• Prat Goma, Josep
• Rey Micolau, Francesc
• Riba Sagarra, Jaume
• Rius Casals, Juan-Manuel
• Rocadenbosch Burillo, Francisco
• Rodriguez Fonollosa, Javier
• Rodriguez Fonollosa, Jose Adrian
• Rodriguez Gomez, Alejandro
• Romeu Robert, Jordi
• Ruiz Boque, Silvia
• Ruiz Costa-Jussa, Marta
• Ruiz Hidalgo, Javier
• Ruiz Moreno, Sergio
• Sala Alvarez, Josep
• Salembier Clairon, Philippe
• Sallent Roig, Jose Oriol
• Santos Blanco, María
• Sicard, Michaël
• Soneira Ferrando, M. Jose
• Spadaro, Salvatore
• Tarres Ruiz, Francisco
• Torner Sabata, Lluis
• Torres Torres, Francesc
• Torres Urgell, Luis
• Ubeda Farre, Eduard
• Valenzuela Gonzalez, Jose Luis
• Vall-Llossera Ferran, Mercè
• Vazquez Grau, Gregori
• Vidal Manzano, Josep
• Vilaplana Besler, Veronica
• Villares Piera, Nemesio Javier