Interplay between Distributed AI Workflow and URLLC

Distributed artificial intelligence (AI) has recently accomplished tremendous breakthroughs in various communication services, ranging from fault-tolerant factory automation to smart cities. When distributed learning is run over a set of wireless connected devices, random channel fluctuations, and the incumbent services simultaneously running on the same network affect the performance of distributed learning. In this paper, we investigate the interplay between distributed AI workflow and ultra-reliable low latency communication (URLLC) services running concurrently over a network. Using 3GPP compliant simulations in a factory automation use case, we show the impact of various distributed AI settings (e.g., model size and the number of participating devices) on the convergence time of distributed AI and the application layer performance of URLLC. Unless we leverage the existing 5G-NR quality of service handling mechanisms to separate the traffic from the two services, our simulation results show that the impact of distributed AI on the availability of the URLLC devices is significant. Moreover, with proper setting of distributed AI (e.g., proper user selection), we can substantially reduce network resource utilization, leading to lower latency for distributed AI and higher availability for the URLLC users. Our results provide important insights for future 6G and AI standardization.Comment: Accepted in 2022 IEEE Global Communications Conference (GLOBECOM

The concept of the sustainable port – ports becoming enablers of sustainability in trans-ports and logistics

Global transportation is one of the major contributors to greenhouse gas emissions. Portsplay an important role for the leap towards a more sustainable transport ecosystem. Overthe years, empowered by the Swedish innovation project I.Hamn, a concept for thesustainable port has been developed by the Swedish ports (see Appendix 1). This efforthas been financed by the Swedish Transport Administration’s industry programmeSustainable shipping managed by Lighthouse. The project is coordinated by the ResearchInstitutes of Sweden (RISE), and University of Gothenburg and Chalmers University ofTechnology are project partners.The result is a vision of the sustainable port, including a roadmap - developed togetherwith Lighthouse Focus group for Ports - supporting Swedish ports, in which the threepillars of sustainability have been addressed, i.e., economic, social, and environmentalsustainability.Globala transporter \ue4r en av de st\uf6rsta bidragsgivarna till utsl\ue4ppen av v\ue4xthusgaser. Hamnarna spelar en viktig roll f\uf6r spr\ue5nget mot ett mer h\ue5llbart transportekosystem. Genom insatser i innovationsprojektet I.Hamn har ett koncept f\uf6r den h\ue5llbara hamnen tagits fram av de svenska hamnarna (se Appendix 1). Satsningen har finansierats av Trafikverkets branschprogram H\ue5llbar sj\uf6fart som f\uf6rvaltas av Lighthouse. Projektet har koordinerats av Research Institutes of Sweden (RISE) tillsammans med G\uf6teborgs universitet och Chalmers tekniska h\uf6gskola.\ua0Resultatet \ue4r en vision om den h\ue5llbara hamnen, inklusive en f\ue4rdplan - framtagen tillsammans med Lighthouse Fokusgrupp Hamnar - som st\uf6djer svenska hamnar, d\ue4r de tre pelarna f\uf6r h\ue5llbarhet har tagits upp, det vill s\ue4ga ekonomisk, social och milj\uf6m\ue4ssig h\ue5llbarhet

Stora bostadsfastigheter i glesbygd : En studie av rättsfall och praxis

För att främja landsbygdens utveckling och till följd av förändringar i markpolitiken tilläts genom lag bildandet av stora bostadsfastigheter på landsbygden 1990. Detta skulle ske genom att öka den enskildes möjlighet att utforma sin fastighet efter egna önskemål. Glesbygd, som är landsbygd karaktäriserad av gles befolkning, är mer utsatt för de problem som landsbygden står inför. Syftet med studien är att undersöka om det finns eller borde finnas en skillnad mellan lands- och glesbygden vid fastighetsbildning av stora bostadsfastigheter. Studien utförs genom en genomgång av rättskällor, tolkning av rättsfall och analys av Lantmäteriets praxis. Resultaten visar att flera rättsliga faktorer, nämligen skyddszon, extensivt nyttjande, skogsmark, jordbruksmark och fastighetens belägenhet i glesbygd påverkar tillåtligheten av att bilda stora bostadsfastigheter. Vidare visas att inga avsevärda skillnader mellan lands- och glesbygd i Lantmäteriets praxis finns. Därutöver så tyder tolkningen av rättsfall på att domstolarna inte alltid beaktar markpolitikens främjande av glesbygden. Det starkaste motstående intresset för bildandet av stora bostadsfastigheter ligger i skyddet av skogsnäringen, som även till stor del sammanfaller geografiskt med glesbygden. Resultaten tyder på att nuvarande rättsläge och markpolitik inte tillräckligt beaktar glesbygdens regionalpolitiska intressen, i form av främjande av boende och sysselsättning.In order to promote rural development and due to land use policy changes, the formation of large residential properties in rural areas was permitted by law in 1990. This was to be made possible by increasing the opportunities for the individual to shape their real property according to their own requests. Sparsely populated areas, which are rural areas characterized by sparse population, are more prone to problems considered in rural development policies. The purpose of the study is to research if there is or should be a difference between rural and sparsely populated areas in formation of large residential properties. The study is performed through a review of legal sources, interpretation of judicial proceedings, and analysis of the property formation practice of Lantmäteriet. Presented results show that there are several judicial factors that affect the allowance to form large properties for residential purpose. The factors are protective zone, extensive use, forest land, agricultural land and real property location in sparsely populated areas. Further on, no substantial differences exist between rural and sparsely populated areas in the practices of Lantmäteriet. Moreover, the interpretation of judicial proceedings suggests that the courts do not always take into account the land use policies promotion of sparsely populated areas. The most inflexible opposing interest towards the creation of large residential properties resides in the protection of forestry land use, which also largely geographically coincides with sparsely populated areas. The findings suggest that current legal position and land policies do not sufficiently address the regional policy interests of sparsely populated areas

Öst till väst, hemma bäst? : En kvantitativ studie om marknadens reaktion vid svenska offentliggöranden av nordiska förvärv

Tidigare forskning är inte helt enig om ett offentliggörande av ett företagsförvärv skapar mervärde för det förvärvande företagets ägare. Framför allt tycks det råda delade meningar kring om den abnormala avkastningen skiljer sig mellan offentliggöranden av inhemska förvärv och gränsöverskridande förvärv. Studien syftar därför till att undersöka om abnormal avkastning uppstår när ett svenskt företag offentliggör ett inhemskt förvärv och om avkastningen skiljer sig från svenska gränsöverskridande förvärv inom Norden. Genom en eventstudie innehållandes 84 förvärvsannonseringar mellan 2015–2019 på Stockholmsbörsen undersöks marknadens reaktion. Studien finner att det uppstår abnormal avkastning vid offentliggörandet av inhemska förvärv. Vidare finner studien vissa belägg att inhemska förvärv genererar högre abnormal avkastning än gränsöverskridande förvärv

Öst till väst, hemma bäst? : En kvantitativ studie om marknadens reaktion vid svenska offentliggöranden av nordiska förvärv

Tidigare forskning är inte helt enig om ett offentliggörande av ett företagsförvärv skapar mervärde för det förvärvande företagets ägare. Framför allt tycks det råda delade meningar kring om den abnormala avkastningen skiljer sig mellan offentliggöranden av inhemska förvärv och gränsöverskridande förvärv. Studien syftar därför till att undersöka om abnormal avkastning uppstår när ett svenskt företag offentliggör ett inhemskt förvärv och om avkastningen skiljer sig från svenska gränsöverskridande förvärv inom Norden. Genom en eventstudie innehållandes 84 förvärvsannonseringar mellan 2015–2019 på Stockholmsbörsen undersöks marknadens reaktion. Studien finner att det uppstår abnormal avkastning vid offentliggörandet av inhemska förvärv. Vidare finner studien vissa belägg att inhemska förvärv genererar högre abnormal avkastning än gränsöverskridande förvärv

A Deep Learning Receiver for Non-Linear Transmitter

Non-linearity of wireless transceivers, specifically power amplifier (PA) non-linearity, could pose major limitations towards having high throughput, and cost and energy efficient wireless communication systems. Such limitations from the PA is typically compensated in the transmitter, e.g. by applying power back-off or performing digital-pre-distortion (DPD) aiming to linearize the transmitter. However, applying PA power back-off leads to lower energy efficiency, and lower output power, and hence lower coverage; and performing DPD results in higher complexity of the transmitters. This paper presents an alternative approach based on a receiver method to perform signal detection in the presence of distortions due to PA non-linearity. We propose a receiver technique using artificial neural networks (ANN) to compensate for the PA non-linearity at the receiver side. The paper presents link-level simulation results using pre-trained neural network models based on synthesized training data. The simulation results confirm that the designed receiver can tolerate higher distortions, hence allow the PA output power back-off to be reduced, leading to higher output power improving coverage, spectral efficiency, energy efficiency, and throughput.HexaX_WP

Pervasive artificial intelligence in next generation wireless: The Hexa-X project perspective

The European 6G flagship project Hexa-X has the objective to conduct exploratory research on the next generation of mobile networks with the intention to connect human, physical and digital worlds with a fabric of technology enablers. Within this scope, one of the main research challenges is the ambition for beyond 5G (B5G)/6G systems to support, enhance and enable real-time trustworthy control by transforming Artificial Intelligence (AI) / Machine Learning (ML) technologies into a vital and trusted tool for large-scale deployment of interconnected intelligence available to the wider society. Hence, the study and development of concepts and solutions enabling AI-driven communication and computation co-design for a B5G /6G communication system is required. This paper focuses on describing the possibilities that emerge with the application of AI/ML mechanisms to 6G networks, identifying the resulting challenges and proposing some potential solution approaches

The Hexa-X project vision on Artificial Intelligence and Machine Learning-driven Communication and Computation co-design for 6G

International audienceThis paper provides an overview of the most recent advancements and outcomes of the European 6G flagship project Hexa-X, on the topic of in-network Artificial Intelligence (AI) and Machine Learning (ML). We first present a general introduction to the project and its ambitions in terms of use cases (UCs), key performance indicators (KPIs), and key value indicators (KVIs). Then, we identify the key challenges to realize, implement, and enable the native integration of AI and ML in 6G, both as a means for designing flexible, low-complexity, and reconfigurable networks (\textit{learning to communicate}), and as an intrinsic in-network intelligence feature (\textit{communicating to learn }or, 6G as an efficient AI/ML platform). We present a high level description of down selected technical enablers and their implications on the Hexa-X identified UCs, KPIs and KVIs. Our solutions cover lower layer aspects, including channel estimation, transceiver design, power amplifier and distributed MIMO related challenges, and higher layer aspects, including AI/ML workload management and orchestration, as well as distributed AI. The latter entails Federated Learning and explainability as means for privacy preserving and trustworthy AI. To bridge the gap between the technical enablers and the 6G targets, some representative numerical results accompany the high level description. Overall, the methodology of the paper starts from the UCs and KPIs/KVIs, to then focus on the proposed technical solutions able to realize them. Finally, a brief discussion of the ongoing regulation activities related to AI is presented, to close our vision towards an AI and ML-driven communication and computation co-design for 6G

The Hexa-X project vision on Artificial Intelligence and Machine Learning-driven Communication and Computation co-design for 6G

International audienceThis paper provides an overview of the most recent advancements and outcomes of the European 6G flagship project Hexa-X, on the topic of in-network Artificial Intelligence (AI) and Machine Learning (ML). We first present a general introduction to the project and its ambitions in terms of use cases (UCs), key performance indicators (KPIs), and key value indicators (KVIs). Then, we identify the key challenges to realize, implement, and enable the native integration of AI and ML in 6G, both as a means for designing flexible, low-complexity, and reconfigurable networks (\textit{learning to communicate}), and as an intrinsic in-network intelligence feature (\textit{communicating to learn }or, 6G as an efficient AI/ML platform). We present a high level description of down selected technical enablers and their implications on the Hexa-X identified UCs, KPIs and KVIs. Our solutions cover lower layer aspects, including channel estimation, transceiver design, power amplifier and distributed MIMO related challenges, and higher layer aspects, including AI/ML workload management and orchestration, as well as distributed AI. The latter entails Federated Learning and explainability as means for privacy preserving and trustworthy AI. To bridge the gap between the technical enablers and the 6G targets, some representative numerical results accompany the high level description. Overall, the methodology of the paper starts from the UCs and KPIs/KVIs, to then focus on the proposed technical solutions able to realize them. Finally, a brief discussion of the ongoing regulation activities related to AI is presented, to close our vision towards an AI and ML-driven communication and computation co-design for 6G