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Semantic-Aware Intelligent Localization and Sensing towards 6G

Project description

Streamlining 6G to cut redundancy for smarter networks

As smart cities and augmented reality applications expand, the demand for precise, low-latency localisation and sensing (L&S) in 6G communications intensifies. Current approaches flood transceivers with data from numerous sources, causing network congestion and redundancy. This inefficiency stems from a focus on accuracy over energy use, posing a challenge for 6G advancement. Addressing this issue is crucial for creating efficient communication networks. With the support of the Marie Skłodowska-Curie Actions programme, the SAILS-6G project aims to enhance energy efficiency in L&S through semantic communications, which prioritise useful information transmission over raw data. By integrating energy efficiency into L&S optimisation, SAILS-6G seeks to reduce energy consumption while maintaining performance, leading to significant progress in 6G technology.

Objective

The rise of applications like smart cities and augmented reality has emphasized the critical importance of precise, low-latency localization and sensing (L&S) in the context of 6G communications. Meeting L&S demands involves inundating transceivers with extensive data from sources like pilot signals and sensors, creating redundancy that overwhelms communication networks. Addressing this redundancy is a key aspect of semantic communications, aiming to enhance energy efficiency and support 6G technology. Semantic communications prioritize transmitting useful information over mere data transmission. SAILS-6G's goal is to improve the energy efficiency of L&S without compromising utility by leveraging the principles of semantic communications. Historically, L&S optimization has focused on primary KPIs, such as accuracy, neglecting energy efficiency. SAILS-6G bridges this gap by integrating energy efficiency into L&S optimization through three WPs: WP1 addresses energy-constrained optimization issues using optimization theory tools. WP2 tackles complex nonlinear optimization challenges from WP1, employing learning structures. WP3 extends energy-efficient L&S algorithms from WP1 and WP2, considering distributed processing and privacy constraints. The applicant's expertise in information theory, optimization theory, and privacy-preserving learning, along with the supervisor's localization knowledge, supports these WPs. The outcome is optimized transceivers, reducing energy consumption while meeting L&S requirements. Their performance is evaluated against traditional methods and theoretical bounds. The ultimate aim is to introduce a groundbreaking framework for semantic L&S widely accepted in the scientific community, marking a significant field advancement. Building this framework boosts the applicant's scientific impact and strengthens his managerial, educational, and research skills, facilitated by the supervisor's network, advancing his journey towards a professorship.

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Programme(s)

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Topic(s)

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Funding Scheme

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HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships

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Call for proposal

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(opens in new window) HORIZON-MSCA-2023-PF-01

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Coordinator

CHALMERS TEKNISKA HOGSKOLA AB
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 222 727,68
Address
-
412 96 GOTEBORG
Sweden

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Region
Södra Sverige Västsverige Västra Götalands län
Activity type
Higher or Secondary Education Establishments
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Total cost

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