Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Millan Philipose

dblp:299/2218 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
1since 2021 · last 2021
—ORCID · none

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 · 70% Internet of things and sensor networks · 30%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Physical-layer communications
interference cancellation
0.512021
Concurrent interference cancellation: decoding multi-packet collisions in LoRa · SIGCOMM 2021
Internet of things and sensor networks › LPWAN
lora
0.512021
Concurrent interference cancellation: decoding multi-packet collisions in LoRa · SIGCOMM 2021
Physical-layer communications › interference cancellation
parallel interference cancellation
0.512021
Concurrent interference cancellation: decoding multi-packet collisions in LoRa · SIGCOMM 2021
YearPublicationVenuePosition
2021 Concurrent interference cancellation: decoding multi-packet collisions in LoRa
abstract
LoRa has seen widespread adoption as a long range IoT technology. As the number of LoRa deployments grow, packet collisions undermine its overall network throughput. In this paper, we propose a novel interference cancellation technique -- Concurrent Interference Cancellation (CIC), that enables concurrent decoding of multiple collided LoRa packets. CIC fundamentally differs from existing approaches as it demodulates symbols by canceling out all other interfering symbols. It achieves this cancellation by carefully selecting a set of sub-symbols -- pieces of the original symbol such that no interfering symbol is common across all sub-symbols in this set. Thus, after demodulating each sub-symbol, an intersection across their spectra cancels out all the interfering symbols. Through LoRa deployments using COTS devices, we demonstrate that CIC can increase the network capacity of standard LoRa by up to 10x and up to 4x over the state-of-the-art research. While beneficial across all scenarios, CIC has even more significant benefits under low SNR conditions that are common to LoRa deployments, in which prior approaches appear to perform quite poorly.
Muhammad Osama Shahid, Millan Philipose, Krishna Chintalapudi, Suman Banerjee 0001, Bhuvana Krishnaswamy
SIGCOMM2