Publications in Scientific Journals:

B. Knerr, M. Holzer, C. Angerer, M. Rupp:
"Slot-Wise Maximum Likelihood Estimation of the Tag Population Size in FSA Protocols";
IEEE Transactions on Communications, 58 (2010), 2; 578 - 585.

English abstract:
Framed 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 obtained.

ML estimation, tag population, RFID, framed slotted aloha, anti-collision

"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)

Electronic version of the publication:

Related Projects:
Project Head Christoph Mecklenbräuker:
Christian Doppler Lab "Funktechnologien für nachhaltige Mobilität"

Created from the Publication Database of the Vienna University of Technology.