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Mohamed R. Abdelhamid

dblp:219/2581 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2020
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
1 paper
Internet of things and sensor networks · 67% Wireless networking · 33%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Energy-efficient computing · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Internet of things and sensor networks
backscatter communication
0.412020
Self-reconfigurable micro-implants for cross-tissue wireless and batteryless connectivity · MobiCom 2020
Internet of things and sensor networks › iot devices › battery-free devices
batteryless sensor
0.412020
Self-reconfigurable micro-implants for cross-tissue wireless and batteryless connectivity · MobiCom 2020
Wireless networking › link adaptation
rate adaptation
0.412020
Self-reconfigurable micro-implants for cross-tissue wireless and batteryless connectivity · MobiCom 2020
Energy-efficient computing › energy harvesting
RF energy harvesting
0.112020
Self-reconfigurable micro-implants for cross-tissue wireless and batteryless connectivity · MobiCom 2020

Methods — techniques the papers use, named apart from their topics

reprogrammable antenna · 0.9backscatter rate adaptation · 0.9
YearPublicationVenuePosition
2020 Self-reconfigurable micro-implants for cross-tissue wireless and batteryless connectivity
abstract
We present the design, implementation, and evaluation of μmedIC, a fully-integrated wireless and batteryless micro-implanted sensor. The sensor powers up by harvesting energy from RF signals and communicates at near-zero power via backscatter. In contrast to prior designs which cannot operate across various in-body environments, our sensor can self-reconfigure to adapt to different tissues and channel conditions. This adaptation is made possible by two key innovations: a reprogrammable antenna that can tune its energy harvesting resonance to surrounding tissues, and a backscatter rate adaptation protocol that closes the feedback loop by tracking circuit-level sensor hints.
Mohamed R. Abdelhamid, Ruicong Chen, Joonhyuk Cho, Anantha P. Chandrakasan, Fadel Adib
MobiCom1