Demo Data from SIGIR 2026 / reviewers in the wild / expert
Bastian Knerr
dblp:37/6435
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2010
—ORCID · none
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 · 80% Physical-layer communications · 20% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Internet of things and sensor networks › RFID systems
anti-collision protocol |
0.1 | 1 | 2010 | Slot-wise maximum likelihood estimation of the tag population size in FSA protocols · IEEE Trans. Commun. 2010 |
Internet of things and sensor networks › RFID systems › anti-collision protocol
framed slotted aloha |
0.1 | 1 | 2010 | Slot-wise maximum likelihood estimation of the tag population size in FSA protocols · IEEE Trans. Commun. 2010 |
Physical-layer communications › channel estimation
maximum likelihood estimation |
0.1 | 1 | 2010 | Slot-wise maximum likelihood estimation of the tag population size in FSA protocols · IEEE Trans. Commun. 2010 |
Internet of things and sensor networks
RFID systems |
0.1 | 1 | 2010 | Slot-wise maximum likelihood estimation of the tag population size in FSA protocols · IEEE Trans. Commun. 2010 |
Internet of things and sensor networks › RFID systems › cardinality estimation
tag cardinality estimation |
0.1 | 1 | 2010 | Slot-wise maximum likelihood estimation of the tag population size in FSA protocols · IEEE Trans. Commun. 2010 |
Methods — techniques the papers use, named apart from their topics
maximum likelihood estimation · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2010 | Slot-wise maximum likelihood estimation of the tag population size in FSA protocolsabstractFramed Slotted Aloha (FSA) is a popular anticollision technique in state-of-the-art RF-ID systems, as in ISO/IEC CD 18000-6 for 900MHz or the EPCglobal HF Gen 2 draft for 13.56MHz. In many applications the number of tags entering and leaving the detection range of the reader is subject to a strong fluctuation and usually unknown. The current number of tags in the field is a crucial parameter to operate the FSA anti-collision in an optimal manner. Therefore, a lot of effort is spent on the estimation of this parameter and a range of different estimation techniques exist. The contributions of this paper are: 1) a closed formula for the probability of any observed event defined by the number of empty, singleton, and collision slots in the observed frame is developed and empirically verified. 2) This formula is then modified to compute the probability for partly observed frames as well which is of great interest as the referred standards allow for the in-frame adjustment of the frame size without quitting the interrogation round. 3) Then, a maximum likelihood estimator is formulated to yield the estimated number of tags on a slot-wise basis. 4) Its superior estimation performance is compared to the known best estimators over the complete parameter set. While its performance is strongly superior compared to Schoute¿s estimate, compared to Vogt¿s MSE estimator only marginally improvement is obtained1. Bastian Knerr, Martin Holzer 0002, Christoph Angerer, Markus Rupp |
IEEE Trans. Commun. | 1 |