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Ultra-Dense Unsupervised Heterogeneous Wireless Cloud Coded Networks for 5G/B5G

Project description

Wireless cloud networks

While beyond 5G (B5G) wireless networks will have increased density and scale compared to current networks, fixed connections to all access nodes will be infeasible. For several significant B5G scenarios, therefore, it will be impractical to provide a global coordinating authority. These networks will be essentially left unsupervised. The EU-funded RECENT project aims to address such networks starting with fundamental theory and technology. Running in parallel to the technical activities, a rigorously crafted innovation management programme will assess business opportunities of RECENT technologies, taking into consideration standards and regulation, and hence ensure that they achieve their full industrial and societal impact.

Objective

"Beyond 5G (B5G) wireless networks will undoubtedly have greatly increased density and scale compared to current networks, resulting in massive interaction between nodes. It will be infeasible to provide fixed connections to all access nodes, and hence these networks will evolve towards a heterogeneous, multihop, self-organizing architecture. Moreover, for several significant B5G scenarios (such as vehicular networks in ""smart cities"") the topology may be a priori unknown and rapidly time-variant: therefore, it will be impractical to provide a global coordinating authority, and hence these networks will be essentially unsupervised. (Security remains paramount, and physical security mechanisms especially appropriate.) The conventional networking paradigm will be severely limited by interference in these scenarios, greatly reducing efficiency. It has already been shown in both theory and practice that wireless physical-layer network coding (WPNC) is nevertheless capable of resolving this situation because it can allow relay nodes to extract useful information from all combined received signals, rather than treating them as deleterious interference.
However, previous work on WPNC [1-5] has not addressed the case of large-scale, unsupervised, secure, dynamic networks. RECENT will address such networks starting with fundamental theory and technology, including information theory, network coded modulation (NCM) for WPNC, stochastic network theory, and physical layer security. The developed technologies will be deployed and validated in the system level simulator and hardware-in-the-loop (HIL) platform. Running in parallel to the technical activities, a rigorously crafted innovation management programme will assess business opportunities of RECENT technologies, taking into consideration standards and regulation, and hence ensure that they achieve their full industrial and societal impact."

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Programme(s)

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Topic(s)

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Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

MSCA-RISE - Marie Skłodowska-Curie Research and Innovation Staff Exchange (RISE)

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Call for proposal

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(opens in new window) H2020-MSCA-RISE-2018

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Coordinator

GREENSPHERE UNIPESSOAL LDA
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.

€ 285 200,00
Address
AVENIDA CALOUSTE GULBENKIAN 174
3750-102 AGUEDA
Portugal

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SME

The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.

Yes
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 285 200,00

Participants (3)

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