Technology Futures - Amazon Web Services
Transcript of Technology Futures - Amazon Web Services
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Technology FuturesSpotlight on the mobile and wireless chapter
January 2021
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Criteria:
• Enables the delivery of new services which
are valued highly by people and businesses
• Broadens and deepens access to services
• Increases the performance of networks,
improving the experience for people
• Lowers barriers to entry for providers,
enabling choice for people
• Reduces the cost of delivering services,
increasing access and maximising value for
customers
• Changes the way we authorise and
regulate networks/services
• Reduces the total environmental impact of
delivery of communication services and
associated activities
• Assures the security and resilience of
service delivery
Scope of the report
Immersive communications and
applications
Mobile and wireless technologies
Fixed and optical technologies
Broadcasting and media technologies
Satellite technologies
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How we did it…
Internal experts78 world leading external experts
30 CFI responses 285 references
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Our output…
Report available hereVideos available here
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A snapshot of some technologies discussed in the report…
Immersive communications
• Haptic comms• Spatial audio• Speech interfaces• Virtuality• Olfactory comms• Brain-machine
interface • Inclusive comms
Mobile & wireless• Cell-free networks• Extremely large
arrays• AI-native mobile• Terahertz• Joint
communication and sensing Beyond Shannon
Fixed & optical• Multicore fibre• Hollow core fibre• Spatial division
multiplexing• Dense integrated
optics• Robotic
technologies for network installation
Broadcast & media• Light field cameras• Object-based
media• 5G production &
distribution• Medium-
independent content
• Evolved content navigation methods
Satellite• Reconfigurable
satellites• NGSO
constellations• Satellite flocks• Direct mobile-
satellite• Optical links• Flat panel mobile
antennas• Manufacturing in
Space
AI
Softwarisation / cloudification
Metamaterials
Hybrid topologies
Evolving computing architectures (e.g. neuromorphic)
Quantum
Energy reduction
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Focus of this presentation
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Mobile and wireless chapter
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Looking back to look ahead – limits on communication
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Beyond Shannon?
• Using metamaterials (sub-wavelength arrays of electronically controlled scatterers) to design intelligent reflective surfaces
• Designing extremely large, distributed antenna arrays with an irregular structure and a separation larger than a wavelength
• Shannon assumed a memory-less channel, he did not consider the meaning of a given message. If we store past information to build a context we enter in to the domain of “semantic communications”
Source: Linkoping University
Source: Ofcom
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Quantum Shannon theory
• Quantum communication uses photons in states of superposition to represent multiple combinations of 1 and 0 simultaneously.
• Researchers also propose further advances where both information carriers and the channels can be in quantum superposition.
• Therefore, in theory recent advances in quantum technology could take us beyond Shannon by establishing new fundamental limits and the potential of extending Shannon's theory to situations where different transmission lines can be combined in a quantum way.
• However, a lot of work is needed to get there, e.g. each node in a Quantum Communication network must be a Quantum Computer
Source: G. Chiribella and H. Kristastjansson
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Looking back to look ahead – limits on computation
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Neuromorphic computing and spiking neural networks
• A new architecture for computing, inspired by the human brain
• Based on spiky, asynchronous, event-driven neural networks (very different from today’s)
• Benefits: energy efficiency, latency
H. Jang, O. Simeone, B. Gardner, A. Grüning, “An Introduction to Spiking Neural Networks: Probabilistic Models, Learning Rules, and Applications”, IEEE Signal Processing Magazine, 2019.
Why relevant for communications: federated learning, joint communication and sensing
Source: Ofcom
Source: King’s College London
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AI in communication networks: autoencoders
A. Felix, S. Cammerer, S. Doerner, J. Hoydis, S. Ten Brink, ”OFDM-autoencoder for end-to-end learning of communications systems”, IEEE SPAWC 2018.
Very relevant for enabling spectrum sharing
• Traditional transmitter and receiver digital processing blocks can be replaced by two deep neural networks
• Benefits: end-2-end optimisation, resilience, scenario-specific
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Distributed artificial intelligence/ federated learning
https://towardsdatascience.com/ai-differential-privacy-and-federated-learning-523146d46b85
High data rates and low latency might be required
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Joint communication, sensing and positioning• Sensing capabilities can be provided as an
add-on to existing communication systems or natively embedded into the design of a new system
• Native support requires optimisation of waveforms, frame system and network architecture
• Terahertz bands for spatial and temporal resolution
• Historically, wireless communications and radar systems have developed mostly independently. Joint design of single system to meet both applications could provide flexibility and spectrum efficiency
Source: MIT
Spectrum requirements are not driven only by communication.Opportunities for spectrum sharing.
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Changing topologies, and moving beyond cells
• Cell-free cellular networks
• Coverage to the sky and from the sky
• Mobile platforms
Source: Linkoping University
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Thanks!