Contribution to dimensionality reduction of digital predistorter behavioral models for RF power amplifier linearization

The power efficiency and linearity of radio frequency (RF) power amplifiers (PAs) are critical in wireless communication systems. The main scope of PA designers is to build the RF PAs capable to maintain high efficiency and linearity figures simultaneously. However, these figures are inherently conflicted to each other and system-level solutions based on linearization techniques are required. Digital predistortion (DPD) linearization has become the most widely used solution to mitigate the efficiency versus linearity trade-off. The dimensionality of the DPD model depends on the complexity of the system. It increases significantly in high efficient amplification architectures when considering current wideband and spectrally efficient technologies. Overparametrization may lead to an ill-conditioned least squares (LS) estimation of the DPD coefficients, which is usually solved by employing regularization techniques. However, in order to both reduce the computational complexity and avoid ill-conditioning problems derived from overparametrization, several efforts have been dedicated to investigate dimensionality reduction techniques to reduce the order of the DPD model. This dissertation contributes to the dimensionality reduction of DPD linearizers for RF PAs with emphasis on the identification and adaptation subsystem. In particular, several dynamic model order reduction approaches based on feature extraction techniques are proposed. Thus, the minimum number of relevant DPD coefficients are dynamically selected and estimated in the DPD adaptation subsystem. The number of DPD coefficients is reduced, ensuring a well-conditioned LS estimation while demanding minimum hardware resources. The presented dynamic linearization approaches are evaluated and compared through experimental validation with an envelope tracking PA and a class-J PA The experimental results show similar linearization performance than the conventional LS solution but at lower computational cost.La eficiencia energetica y la linealidad de los amplificadores de potencia (PA) de radiofrecuencia (RF) son fundamentales en los sistemas de comunicacion inalambrica. El principal objetivo a alcanzar en el diserio de amplificadores de radiofrecuencia es lograr simultaneamente elevadas cifras de eficiencia y de linealidad. Sin embargo, estas cifras estan inherentemente en conflicto entre si, y se requieren soluciones a nivel de sistema basadas en tecnicas de linealizacion. La linealizacion mediante predistorsion digital (DPD) se ha convertido en la solucion mas utilizada para mitigar el compromise entre eficiencia y linealidad. La dimension del modelo del predistorsionador DPD depende de la complejidad del sistema, y aumenta significativamente en las arquitecturas de amplificacion de alta eficiencia cuando se consideran los actuales anchos de banda y las tecnologfas espectralmente eficientes. El exceso de parametrizacion puede conducir a una estimacion de los coeficientes DPD, mediante minimos cuadrados (LS), mal condicionada, lo cual generalmente se resuelve empleando tecnicas de regularizacion. Sin embargo, con el fin de reducir la complejidad computacional y evitar dichos problemas de mal acondicionamiento derivados de la sobreparametrizacion, se han dedicado varies esfuerzos para investigar tecnicas de reduccion de dimensionalidad que permitan reducir el orden del modelo del DPD. Esta tesis doctoral contribuye a aportar soluciones para la reduccion de la dimension de los linealizadores DPD para RF PA, centrandose en el subsistema de identificacion y adaptacion. En concrete, se proponen varies enfoques de reduccion de orden del modelo dinamico, basados en tecnicas de extraccion de caracteristicas. El numero minimo de coeficientes DPD relevantes se seleccionan y estiman dinamicamente en el subsistema de adaptacion del DPD, y de este modo la cantidad de coeficientes DPD se reduce, lo cual ademas garantiza una estimacion de LS bien condicionada al tiempo que exige menos recursos de hardware. Las propuestas de linealizacion dinamica presentados en esta tesis se evaluan y comparan mediante validacion experimental con un PA de seguimiento de envolvente y un PA tipo clase J. Los resultados experimentales muestran unos resultados de linealizacion de los PA similares a los obtenidos cuando se em plea la solucion LS convencional, pero con un coste computacional mas reducido.Postprint (published version

コトナル ショクセイ ヒフクチ ニオケル ドジョウ シンショク ト エイヨウエン チクセキリョウ ノ ソウゴ サヨウ ノ ヒョウカ

博士（農学）東京農工大

Dynamic selection and estimation of the digital predistorter parameters for power amplifier linearization

© © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This paper presents a new technique that dynamically estimates and updates the coefficients of a digital predistorter (DPD) for power amplifier (PA) linearization. The proposed technique is dynamic in the sense of estimating, at every iteration of the coefficient's update, only the minimum necessary parameters according to a criterion based on the residual estimation error. At the first step, the original basis functions defining the DPD in the forward path are orthonormalized for DPD adaptation in the feedback path by means of a precalculated principal component analysis (PCA) transformation. The robustness and reliability of the precalculated PCA transformation (i.e., PCA transformation matrix obtained off line and only once) is tested and verified. Then, at the second step, a properly modified partial least squares (PLS) method, named dynamic partial least squares (DPLS), is applied to obtain the minimum and most relevant transformed components required for updating the coefficients of the DPD linearizer. The combination of the PCA transformation with the DPLS extraction of components is equivalent to a canonical correlation analysis (CCA) updating solution, which is optimum in the sense of generating components with maximum correlation (instead of maximum covariance as in the case of the DPLS extraction alone). The proposed dynamic extraction technique is evaluated and compared in terms of computational cost and performance with the commonly used QR decomposition approach for solving the least squares (LS) problem. Experimental results show that the proposed method (i.e., combining PCA with DPLS) drastically reduces the amount of DPD coefficients to be estimated while maintaining the same linearization performance.Peer ReviewedPostprint (author's final draft

Challenges And Opportunities For The Development Of Infrastructure After ‘Oda Graduation’ - Moving Towards Sustainable Development: Case Study Of Vietnam

The research on ODA will be focused on its relation to Goal 17, the Partnership, considered a major issue by the researchers, especially in the case of Vietnam as a developing economy. ODA was mainly used for investing in economic infrastructure when Vietnam witnessed a downfall in receiving financial aid due to its significant economic growth. ODA helped Vietnam transform from one of the world’s poorest nations into a lower middle-income country and soon, this is going to lead to the ‘ODA Graduation’. However, the process has just begun. The country is still in a process of industrialization and modernization and its socio-economic situation has not been stable or solid. By all means, ODA is not only a financial resource, it also helps the country to accomplish Sustainable Development Goals (SDGs) of the UN. ‘ODA Graduation’ means that the economy of Vietnam has faced certain challenges such as increasing pressure of outbound debts; raising impact on social development or imbalance between high capital recovery investments and public-services investments. However, ‘ODA Graduation’ has brought certain opportunities such as increasing Vietnam’s independence in capital mobilization, preventing the removal of tariffs barrier, reducing losses and waste of funds. This research gives recommendations for improving Vietnam’s economic situation and can help overcome the difficulties in the period of ‘ODA Graduation’

Challenges And Opportunities For The Development Of Infrastructure After ‘Oda Graduation’ - Moving Towards Sustainable Development: Case Study Of Vietnam

The research on ODA will be focused on its relation to Goal 17, the Partnership, considered a major issue by the researchers, especially in the case of Vietnam as a developing economy. ODA was mainly used for investing in economic infrastructure when Vietnam witnessed a downfall in receiving financial aid due to its significant economic growth. ODA helped Vietnam transform from one of the world’s poorest nations into a lower middle-income country and soon, this is going to lead to the ‘ODA Graduation’. However, the process has just begun. The country is still in a process of industrialization and modernization and its socio-economic situation has not been stable or solid. By all means, ODA is not only a financial resource, it also helps the country to accomplish Sustainable Development Goals (SDGs) of the UN. ‘ODA Graduation’ means that the economy of Vietnam has faced certain challenges such as increasing pressure of outbound debts; raising impact on social development or imbalance between high capital recovery investments and public-services investments. However, ‘ODA Graduation’ has brought certain opportunities such as increasing Vietnam’s independence in capital mobilization, preventing the removal of tariffs barrier, reducing losses and waste of funds. This research gives recommendations for improving Vietnam’s economic situation and can help overcome the difficulties in the period of ‘ODA Graduation’

Online teaching during the COVID-19 pandemic: Vietnamese language teachers’ emotions, regulation strategies and institutional policy and management

Teaching is often described as one of the most emotion-laden professions. In times of the COVID-19 pandemic, the conversion to online teaching has triggered new emotional experiences of teachers that not many studies have taken into account. Studying emotion from a poststructuralist lens, this study examines the emotional experiences of 10 language teachers in a university in Vietnam and their responses to the new teaching platforms. Analysis of the in-depth semi-structured interviews shows that the pedagogically and technologically distinctive features of online teaching aroused unique challenges for and emotions of the teachers, both positive and negative. Also, the teachers reported a number of strategies to cope with the new situation which we term as in-the-moment and out-of-class emotion regulation. The study highlights the need for acknowledgment and support for teachers in terms of resources, policy and management of institutions in the “new normal situation,” while displaying teachers’ self-reliance and emotional self-regulation. The article calls for attention to teachers emotion as an integral dimension of the profession, regardless of the physical or virtual setting of the classroom

The Status of Educational Sciences In Vietnam: A Bibliometric Analysis From Clarivate Web Of Science Database Between 1991 And 2018

Since 2013, Vietnam has implemented a plan to reform the whole education sector. However, there is little understanding on the status of educational research in Vietnam, which may lay the foundation for such plan. Thus, this research aims to analyze the whole picture of educational research from Vietnam, as seen from the Clarivate Web of Science (WOS) database: 215 publications were recorded, ranging from 1991 to 2018. These 215 publications were further analyzed from five perspectives: 1) number of publications by year; 2) research fields and levels of education; 3) top institutions with the highest number of publications; 4) international collaboration; and 5) quality. Some of the most notable results are: 1) the educational sciences in Vietnam have been still under-developed until recently; 2) among different research topics research among educational sciences, some (e.g., Vocational Education and Training or Early Childhood Education) seemed to be overlooked whereas others (e.g., Higher Education and Teaching and Learning) seemed to receive more attention from educational scholars; 3) all the most major education – specialized universities did not appear among the top five institutions with highest number of publications; 4) Australia, Thailand, the USA, New Zealand and China were the countries with the highest number of co-publications with Vietnamese researchers; and 5) The majority of publications belonged to low-ranked journals. Implications would be withdrawn for Vietnamese policymakers, education leaders, educational researchers and teachers in order to adjust their policies and/or action plans; thus, enhancing the performance and impacts of educational research in the future

Independent digital predistortion parameters estimation using adaptive principal component analysis

©2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This paper presents an estimation/adaptation method based on the adaptive principal component analysis (APCA) technique to guarantee the identification of the minimum necessary parameters of a digital predistorter. The proposed estimation/adaptation technique is suitable for online field-programmable gate array or system on chip implementation. By exploiting the orthogonality of the resulting transformed matrix obtained with the APCA technique, it is possible to reduce the number of coefficients to be estimated which, at the same time, has a beneficial regularization effect by preventing ill-conditioning or overfitting problems. Therefore, this identification/adaptation method enhances the robustness of the parameter estimation and simplifies the adaptation by reducing the number of estimated coefficients. Due to the orthogonality of the new basis, these parameters can be estimated independently, thus allowing for scalability. Experimental results will show that it is possible to determine the minimum number of parameters to be estimated in order to meet the targeted linearity levels while ensuring a robust well-conditioned identification. Moreover, the results will show how thanks to the orthogonality property of the new basis functions, the coefficients of the digital predistorter can be estimated independently. This allows to tradeoff the digital predistorter adaptation time versus performance and hardware complexity.Peer ReviewedPostprint (author's final draft

Countering stuckness: international doctoral students' experiences of disrupted mobility amidst COVID-19

The paper, through the lens of positioning and agency theories, examines the experiences of being stranded in the home country due to the restricted mobility caused by the COVID-19 pandemic of 10 international doctoral students of different nationalities (Chinese, Vietnamese, Malaysian, and Indian), majoring in different disciplines (Education, Linguistics, Applied linguistics, Economics, Public health, and Civil engineering), and studying in different countries (New Zealand, Australia, and the United States). With an aim to explore the abrupt immobility and its subsequent impacts on the students’ learning, the article highlights the challenges that the students had to tackle including the feelings of being in limbo, nostalgia, and detachment, and faced with academic challenges due to the physical distance from the study destination. Accordingly, they had to self-position and reposition themselves and enact different forms of agency to confront the difficulties, including agency for becoming, needs-response agency, and agency as struggle and resistance. The findings highlight how the international PhD students mobilized resources to develop their independence as future researchers, as well as their connection with the academic communities in their home countries in various ways

Survey on Vietnamese teachers’ perspectives and perceived support during COVID-19

The COVID-19 pandemic has caused unprecedented damage to the educational system worldwide. Besides the measurable economic impacts in the short-term and long-term, there is intangible destruction within educational institutions. In particular, teachers – the most critical intellectual resources of any schools – have to face various types of financial, physical, and mental struggles due to COVID-19. To capture the current context of more than one million Vietnamese teachers during COVID-19, we distributed an e- survey to more than 2,500 randomly selected teachers from two major teacher communities on Facebook from 6th to 11th April 2020. From over 373 responses, we excluded the observations which violated our cross-check questions and retained 294 observations for further analysis. This dataset includes: (i) Demographics of participants; (ii) Teachers' perspectives regarding the operation of teaching activities during the pandemic; (iii) Teachers' received support from their schools, government bodies, other stakeholders such as teacher unions, and parents' associations; and (iv) teachers' evaluation of school readiness toward digital transformation. Further, the dataset was supplemented with an additional question on the teachers' primary source of professional development activities during the pandemic