Sevda Ögüt

dblp:307/5428 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2023
0009-0005-0152-5073ORCID · reported

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

Computer networks · 1 · 1 since 2021

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
Physical-layer communications · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Physical-layer communications
channel coding and estimation
0.712023
Towards Practical and Scalable Molecular Networks · SIGCOMM 2023
Physical-layer communications
molecular communication
0.712023
Towards Practical and Scalable Molecular Networks · SIGCOMM 2023

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

packet detection · 0.7encoding/decoding · 0.7
YearPublicationVenuePosition
2023 Towards Practical and Scalable Molecular Networks
abstract
Molecular networks have the potential to enable bio-implants and biological nano-machines to communicate inside the human body. Molecular networks send and receive data between nodes by releasing molecules into the bloodstream. In this work, we explore how we can scale molecular networks from a single transmitter single receiver paradigm to multiple transmitters that can concurrently send data to a receiver. We identify unique challenges in enabling multiple access in molecular networks that prevent us from using standard multiple access protocols. These challenges include the lack of synchronization and feedback, the non-negativity of molecular signals, the extremely long tail of the molecular channel leading to high ISI (Inter-Symbol-Interference), and the limited types of molecules that can be used for communication. We present MoMA (Molecular Multiple Access), a protocol that enables a molecular network with multiple transmitters. We introduce packet detection, channel estimation, and encoding/decoding schemes that leverage the unique properties of molecular networks to address the above challenges. We evaluate MoMA on a synthetic experimental testbed and demonstrate that it can scale up to four transmitters while significantly outperforming the state-of-the-art.
Jiaming Wang 0003, Sevda Ögüt, Haitham Hassanieh, Bhuvana Krishnaswamy
SIGCOMM2