Compressed sensing and approximate message passing for the single-pixel camera

Measuring the phase of optical waves (electromagnetic fields oscillating at 1015 Hz and higher) involves additional complexity, typically by requiring interference with another known field, in the process of holography. Interestingly, electromagnetic fields do have some other features that make them amenable for algorithmic phase retrieval: their far field corresponds to the Fourier transform of their near field. More specifically, given a mask that superimposes an image on a quasi-monochromatic coherent field at some plane in space, the electromagnetic field distribution aThis thesis is based on the technology of Compressed Sensing and the study of the algorithms of Approximate Message Passing for the single-pixel camera. This thesis has been developed in the institute of telecommunication in the Technische Universität Wien (TU Wien) led by the research group of the professor Norbert Görtz. In the beginning of the thesis it is explained what a single-pixel camera is and it also talks about what compressed sensing is, later on, two necessarily iterative schemes (Iterative Hard Thresgolding i Iterative Soft Thresholding) are defined to understand the algorithms of Approximate Message Passing (AMP) and its Bayesian derivation (Bayesian Approximate Message Passing, BAMP). The theoretical explanation of the operation of these algorithms is implicit in the thesis, moreover, AMP and BAMP are implemented in Matlab coding. This implementation allows to see the behaviour of these algorithms in different scenarios to fully understand the differences between them.Este trabajo se basa en la tecnología del Compressed Sensing y en el estudio de los algoritmos de Approximate Message Passing para la cámara de un solo pixel. Es un trabajo desarrollado en el instituto de telecomunicaciones de la Technische Universität Wien (TU Wien) liderado por el grupo de investigación del profesor Norbert Görtz. En el principio del trabajo se explica que es la cámara de un solo pixel y también se habla de que es el Compressed Sensing, más adelante se explican dos esquemas iterativos (Iterative Hard Thresgolding i Iterative Soft Thresholding) necesarios para entender los algoritmos de Approximate Message Passing (AMP) y su derivada bayesiana (Bayesian Approximate Message Passing, BAMP). La explicación teórica del funcionamiento de estos algoritmos es implícita en el proyecto, además, estos dos últimos están implementados en código Matlab. Dicha implementación permite ver cuál es el comportamiento de estos algoritmos en diferentes escenarios y permite entender el algoritmo de AMP y su derivada bayesiana, BAMP.Aquest treball es basa en la tecnologia del compressed sensing i l'estudi dels algoritmes d'Approximate Message Passing per la càmera d'un sol píxel. És un treball desenvolupat a l'intitus de telecomunicacion de la Technische Universität Wien (TU Wien) liderat pel grup de recerca del professor Norbert Görtz, el qual ve liderant la recerca en aquest sector des de fa diversos anys. En l'inici del treball s'explica que és la càmera d'un sol píxel i també es parla de què és el compressed sensing, més endavant s¡expliquen dos esquemes iteratius (Iterative Hard Thresgolding i Iterative Soft Thresholding) necessaris per entendre els algoritmes de Approximate Message Passing (AMP) i la seva derivant bayesiana (Bayesian Approximate Message Passing, BAMP). L'explicació teòrica del funcionament d'aquests algoritmes està implícit en el projecte, a més a més, aquests dos algoritmes estan implementats en codi Matlab. Aquesta implementació permet veure quin és el comportament d'aquests algoritmes per diferents escenaris i permet entendre l'algoritme de AMP i la seva derivant bayesiana (BAMP)

5G-SMART D1.5 Evaluation of radio network deployment options

This deliverable results from the work on the radio network performance analysis of the identified use cases and deployment options. Covered topics include latency reduction and mobility features of the 5G NR itself, as well as detailed analysis of the radio network KPIs, such as latency, reliability, throughput, spectral efficiency and capacity. Corresponding trade-offs for the identified deployment options and industrial use cases are quantified with an extensive set of technical results. Also, this deliverable is looking into co-channel coexistence performance analyzed through a real-life measurement campaign and considers performance optimization in presence of a special micro-exclusion zone within a factory.Comment: Deliverable D1.5 of the project 5G For Smart Manufacturing (5G-SMART

Compressed sensing and approximate message passing for the single-pixel camera

Measuring the phase of optical waves (electromagnetic fields oscillating at 1015 Hz and higher) involves additional complexity, typically by requiring interference with another known field, in the process of holography. Interestingly, electromagnetic fields do have some other features that make them amenable for algorithmic phase retrieval: their far field corresponds to the Fourier transform of their near field. More specifically, given a mask that superimposes an image on a quasi-monochromatic coherent field at some plane in space, the electromagnetic field distribution aThis thesis is based on the technology of Compressed Sensing and the study of the algorithms of Approximate Message Passing for the single-pixel camera. This thesis has been developed in the institute of telecommunication in the Technische Universität Wien (TU Wien) led by the research group of the professor Norbert Görtz. In the beginning of the thesis it is explained what a single-pixel camera is and it also talks about what compressed sensing is, later on, two necessarily iterative schemes (Iterative Hard Thresgolding i Iterative Soft Thresholding) are defined to understand the algorithms of Approximate Message Passing (AMP) and its Bayesian derivation (Bayesian Approximate Message Passing, BAMP). The theoretical explanation of the operation of these algorithms is implicit in the thesis, moreover, AMP and BAMP are implemented in Matlab coding. This implementation allows to see the behaviour of these algorithms in different scenarios to fully understand the differences between them.Este trabajo se basa en la tecnología del Compressed Sensing y en el estudio de los algoritmos de Approximate Message Passing para la cámara de un solo pixel. Es un trabajo desarrollado en el instituto de telecomunicaciones de la Technische Universität Wien (TU Wien) liderado por el grupo de investigación del profesor Norbert Görtz. En el principio del trabajo se explica que es la cámara de un solo pixel y también se habla de que es el Compressed Sensing, más adelante se explican dos esquemas iterativos (Iterative Hard Thresgolding i Iterative Soft Thresholding) necesarios para entender los algoritmos de Approximate Message Passing (AMP) y su derivada bayesiana (Bayesian Approximate Message Passing, BAMP). La explicación teórica del funcionamiento de estos algoritmos es implícita en el proyecto, además, estos dos últimos están implementados en código Matlab. Dicha implementación permite ver cuál es el comportamiento de estos algoritmos en diferentes escenarios y permite entender el algoritmo de AMP y su derivada bayesiana, BAMP.Aquest treball es basa en la tecnologia del compressed sensing i l'estudi dels algoritmes d'Approximate Message Passing per la càmera d'un sol píxel. És un treball desenvolupat a l'intitus de telecomunicacion de la Technische Universität Wien (TU Wien) liderat pel grup de recerca del professor Norbert Görtz, el qual ve liderant la recerca en aquest sector des de fa diversos anys. En l'inici del treball s'explica que és la càmera d'un sol píxel i també es parla de què és el compressed sensing, més endavant s¡expliquen dos esquemes iteratius (Iterative Hard Thresgolding i Iterative Soft Thresholding) necessaris per entendre els algoritmes de Approximate Message Passing (AMP) i la seva derivant bayesiana (Bayesian Approximate Message Passing, BAMP). L'explicació teòrica del funcionament d'aquests algoritmes està implícit en el projecte, a més a més, aquests dos algoritmes estan implementats en codi Matlab. Aquesta implementació permet veure quin és el comportament d'aquests algoritmes per diferents escenaris i permet entendre l'algoritme de AMP i la seva derivant bayesiana (BAMP)

A deep reinforcement learning approach for optimization and task-offloading of mobile edge computing in virtual radio access networks

Mobile systems are increasing in number and, in the future, exponential growth is expected with the deployment of new technologies like 5G and Internet of Things. Requirements from those technologies lead to an improvement from the existent techniques to new sophisticated ones. A key role in future developments, which are already applied in research and industry, are Software Defined Networks (SDN) and Network Function Virtualization (NFV). Therefore, we present a solution for mobile edge computing (MEC) using a deep reinforcement learning (DRL) algorithm to optimize and offload tasks in a scenario of a virtual radio access network (VRANs). Final chapters show results obtained from experiments where the learning agent improves its reward through time benefiting the amount of bandwidth used in the network. Finally, a chapter discussing about the conclusions arise with interesting future work which could potentially lead to better results

Compressed sensing and approximate message passing for the single-pixel camera

Measuring the phase of optical waves (electromagnetic fields oscillating at 1015 Hz and higher) involves additional complexity, typically by requiring interference with another known field, in the process of holography. Interestingly, electromagnetic fields do have some other features that make them amenable for algorithmic phase retrieval: their far field corresponds to the Fourier transform of their near field. More specifically, given a mask that superimposes an image on a quasi-monochromatic coherent field at some plane in space, the electromagnetic field distribution aThis thesis is based on the technology of Compressed Sensing and the study of the algorithms of Approximate Message Passing for the single-pixel camera. This thesis has been developed in the institute of telecommunication in the Technische Universität Wien (TU Wien) led by the research group of the professor Norbert Görtz. In the beginning of the thesis it is explained what a single-pixel camera is and it also talks about what compressed sensing is, later on, two necessarily iterative schemes (Iterative Hard Thresgolding i Iterative Soft Thresholding) are defined to understand the algorithms of Approximate Message Passing (AMP) and its Bayesian derivation (Bayesian Approximate Message Passing, BAMP). The theoretical explanation of the operation of these algorithms is implicit in the thesis, moreover, AMP and BAMP are implemented in Matlab coding. This implementation allows to see the behaviour of these algorithms in different scenarios to fully understand the differences between them.Este trabajo se basa en la tecnología del Compressed Sensing y en el estudio de los algoritmos de Approximate Message Passing para la cámara de un solo pixel. Es un trabajo desarrollado en el instituto de telecomunicaciones de la Technische Universität Wien (TU Wien) liderado por el grupo de investigación del profesor Norbert Görtz. En el principio del trabajo se explica que es la cámara de un solo pixel y también se habla de que es el Compressed Sensing, más adelante se explican dos esquemas iterativos (Iterative Hard Thresgolding i Iterative Soft Thresholding) necesarios para entender los algoritmos de Approximate Message Passing (AMP) y su derivada bayesiana (Bayesian Approximate Message Passing, BAMP). La explicación teórica del funcionamiento de estos algoritmos es implícita en el proyecto, además, estos dos últimos están implementados en código Matlab. Dicha implementación permite ver cuál es el comportamiento de estos algoritmos en diferentes escenarios y permite entender el algoritmo de AMP y su derivada bayesiana, BAMP.Aquest treball es basa en la tecnologia del compressed sensing i l'estudi dels algoritmes d'Approximate Message Passing per la càmera d'un sol píxel. És un treball desenvolupat a l'intitus de telecomunicacion de la Technische Universität Wien (TU Wien) liderat pel grup de recerca del professor Norbert Görtz, el qual ve liderant la recerca en aquest sector des de fa diversos anys. En l'inici del treball s'explica que és la càmera d'un sol píxel i també es parla de què és el compressed sensing, més endavant s¡expliquen dos esquemes iteratius (Iterative Hard Thresgolding i Iterative Soft Thresholding) necessaris per entendre els algoritmes de Approximate Message Passing (AMP) i la seva derivant bayesiana (Bayesian Approximate Message Passing, BAMP). L'explicació teòrica del funcionament d'aquests algoritmes està implícit en el projecte, a més a més, aquests dos algoritmes estan implementats en codi Matlab. Aquesta implementació permet veure quin és el comportament d'aquests algoritmes per diferents escenaris i permet entendre l'algoritme de AMP i la seva derivant bayesiana (BAMP)

Enabling service provisioning and quality maintenance in sliceable optical networks

Future 5G and beyond services rely on the network slicing concept, in which underlying network elements are split and/or aggregated to compose a synthetic network infrastructure (the slice) to satisfy the requirements of services that will be executed on top. Generally speaking, end-to-end network slices comprise multiple network segments, including optical and data centers networks. Therefore, the provisioning of end-to-end network slices is a challenging task that has to consider the characteristics of the different technologies to satisfactorily map the requirements coming/imposed from the services to be deployed. This requires that offers towards the fulfillment of the services to be supported are properly parametrized, enabling the possibility to translate them into specific slice and network services characteristics to be finally materialized in concrete infrastructure resources. On the other hand, there is a rising trend of quality assurance at all levels to satisfy the requirements of services deployed, requiring the runtime maintenance of quality of service/experience of the deployed slices. Due to the dynamic nature of services, it becomes essential to monitor the associated Key Performance Indicators (KPIs), derive from them current quality levels and implement the necessary mechanisms to steer the behavior of the slices towards the maintenance of optimal quality levels. Given such scenarios, in this paper we present a framework that enables the provisioning and orchestration of network slices in multi-domain/segment optical networks as well as an approach to proactively manage the maintenance of the required slices quality. The presented framework is validated through several experimental results.This work has been supported by the Spanish Government through project ALLIANCE-B (TEC2017-90034-C2-2-R) with FEDER contribution.Peer ReviewedPostprint (published version

Autonomous resource assignment for optimal utilization in optical data centre infrastructures

We present an architectural solution based on data analytics for self-organizing optical data centers. Thanks to a reinforcement learning-based cognitive layer, an adaptive and autonomous resource assignment to deployed services is achieved.This work has been supported by the Spanish Government through project TRAINER-B (PID2020‐118011GB‐C22) with FEDER contribution.Peer ReviewedPostprint (author's final draft

Empirical Study on 5G NR Cochannel Coexistence

The 5G non-public network deployments for industrial applications are becoming highly interesting for industries and enterprises owing to dependable wireless performance characteristics. With an increasing trend of network deployments in local licensed and/or shared spectrum, coexistence issues naturally arise. In this article, we present our detailed empirical results on the performance impact of a 5G NR indoor non-public network from a 5G NR outdoor network operating in the same mid-band spectrum. We present experimental results on the uplink and downlink performance impact of a non-public indoor network deployed on an industrial shopfloor. Our results quantify the impact on the uplink and downlink performance characteristics based on realistic traffic loads in a non-public indoor network when using synchronized and unsynchronized Time Division Duplex (TDD) patterns, different UE deployment locations and interference levels. We also present results on mitigating interference effects through robust link adaptation techniques. We believe that this is the first article, which reports quantified 5G NR cochannel coexistence results based on a detailed and systematic study, and provides signficant insights on the cochannel coexistence behavior in realistic deployment scenarios of an industrial shopfloor

Empirical Study on 5G NR Cochannel Coexistence

The 5G non-public network deployments for industrial applications are becoming highly interesting for industries and enterprises owing to dependable wireless performance characteristics. With an increasing trend of network deployments in local licensed and/or shared spectrum, coexistence issues naturally arise. In this article, we present our detailed empirical results on the performance impact of a 5G NR indoor non-public network from a 5G NR outdoor network operating in the same mid-band spectrum. We present experimental results on the uplink and downlink performance impact of a non-public indoor network deployed on an industrial shopfloor. Our results quantify the impact on the uplink and downlink performance characteristics based on realistic traffic loads in a non-public indoor network when using synchronized and unsynchronized Time Division Duplex (TDD) patterns, different UE deployment locations and interference levels. We also present results on mitigating interference effects through robust link adaptation techniques. We believe that this is the first article, which reports quantified 5G NR cochannel coexistence results based on a detailed and systematic study, and provides signficant insights on the cochannel coexistence behavior in realistic deployment scenarios of an industrial shopfloor