Processing & Properties of Floor and Wall Tiles.pptx
Fast and Reliable Estimation Schemes in RFID Systems.ppt
1. Fast and Reliable
Estimation Schemes in
RFID Systems
Murali Kodialam and Thyaga Nandagopal
Bell Labs, Lucent Technologies
2. What is RFID?
RFID, Radio Frequency Identification, is not a new subject
that is going to be proposed anymore.
It is an identification tag that stores the identity of
something.
It is very simple and cheap to be largely produced.
It has been used in various application ranging from
inventory control and tracking to medical-patient
management.
3. What is RFID? (cont.)
Most of them are designed to have a very long life.
It is because they are not designed to use any existing
energy sources for transmitting data.
Instead, a probe signal sent by a reader node is used as
energy for data transmission.
The probe itself can be performed via magnetic coupling
(called near-field) or electro-magnetic coupling (called far-
field).
Nowadays, the probe has much larger range and is
designed to read hundreds of tags at a time.
5. Common problem that arise
Some applications need to estimate the number of tags
as fast as possible for a givenaccuracy
Two major problems arise in anyRFIDdeployment
Identification
Estimation
Existing protocols are not fast enough
6. Identification Algorithm
The idea is described as following: the reader probes a set
of tags, and the tags reply back.
Since it operates in the wireless medium, Collisions might
happen in the process of probing a set of tags.
To hinder the collisions, anti-collision schemes needed to
be applied into the identification algorithms.
8. Probabilistic Identification
Algorithm
The reader communicates through a framed ALOHA
scheme length and the tags pick a particular slot in the
frame to transmit.
This process is repeated by the reader until all tags have
transmitted at least once successfully in a slot without
collisions.
In semi-passive and active tag systems, the reader can
acknowledge tags that have succeeded at the end of each
frame, therefore it shorts the overall identification time.
In passive tags, all tags will continue to transmit in every
frame, which lengthens the total time needed to identify
all tags.
9. Deterministic Identification
Algorithm
The reader identifies the set of tags that need to transmit
in a given slot, and tries to seduce the contending tag set
in the next slot based on the result in the previous slot.
These algorithms fall into the class of tree-based
identification algorithms, such as a binary tree.
On the binary tree, the tags are classified based on their id
and the reader moving down the tree at each step to
identify all nodes.
Deterministic algorithms are typically faster than
probabilistic schemes in terms of actual tag response slots
used, however, they suffer from large reader overhead
since address ranges need to be specified to isolate
contending tag subsets using a probe at the beginning of
each slot.
10. Algorithm Requirements.
An estimation of the actual number of tags t in the system
is required by both of the algorithms.
The estimation is used:
◦ To set the optimal frame size in framed ALOHA.
◦ To guide the tree-based identification process for computing
the expected number of slots needed for identification.
The estimation process should also be able to use non-
identifiable information, such as a string of bits used by all
tags, to compute the size of the tag set t.
11. System Model
readers and tags
Use a Listen-before-Talk model approach, where tags
listen to the reader’s request before they talk back.
12. System Model (cont.)
Assumption on the model:
There exist a separate estimation phase for identification
process.
Framed-slotted ALOHA model is used for tags to transmit
back to the reader.
The tags respond with a bit-string that contains some
error-detection (such as CRC) embedded in the string
when probed by the reader in the estimation phase. The
length of this common bit-string is defined as the
minimum length string such that the reader can detect
collisions when multiple tags transmit the same string in a
given slot. The reader can thus detect collisions in the
estimation phase and identify a successful transmission in
any slot by only one tag.
There is no identification problem.
13. System Model (cont.)
The estimator performance is measured in terms of the
number of slots needed to perform the estimation to the
desired accuracy level.
The goal is to achieve the desired performance in as little
time as possible.
In other words, if it takes le slots to compute ˆt, the
estimate of t tags with a certain accuracy, and li slots to
uniquely identify ˆt tags, then, we need se.le < li.si, where
se and si are the sizes of the bit strings transmitted during
the estimation and identification phases respectively.
14. System Model (cont.)
◦ Phillips I-Code system.
◦ A frame size f (typically a power of 2) is sent by the
readers along with a seed value which is 16-bit number.
◦ The seed information along with its identifier used by
the tag to hash into an integer in the range [1, f], which
specifies the slot in which the frame will contend.
15. System Model (cont.)
Model that is approached:
◦ Extend the scheme to support variable contention
probability p.
◦ Therefore, the reader now sends three parameters in
each probe:
the seed
the frame size f
the integer [f/p]
◦ The tag hashes the combined seed/identifier value into
the range [1, [f/p]].
◦ If the hashed value is greater than f, then the tag does
not transmit in this frame, else it transmit in the
computed slot.
◦ Therefore, a frame transmission probability of f/(f/p) =
p.
16. Deterministic Algorithm
The reader probes the tags with the frame size f
The tags pick a slot j in the frame uniformly at random and
transmit in that slot.
The indicator random variable Xj is used to determine
whether tag transmit to and not transmit to in slot j.
Xj = 1 if no tag transmit in slot j, referred as an empty slot,
and Xj = 0 otherwise.
Similarly, we set Yj = 1 if and only if there is exactly one
tag that transmits in slot j, referred as a singleton slot, and
Vj = 1 if and only if there are multiple tags that transmit in
slot j, referred as a collision.
So that, Xj + Yj + Vj = 1 for all slots j.
17. Deterministic Algorithm (cont.)
Let N0 = ∑ Xj from j = 1 to j = f denote the total number of
empty slots.
N1 = ∑ Yj from j = 1 to j = f denote the total number of
singleton slots.
Nc = f − N0 − N1 denote the number of collision slots.
P = t/f, t denotes numbers of tags and f denotes frame
size.
22. Deterministic Algorithm (cont.)
Compute the desired variance σ
Initial frame size f
Energize the tags and get n0 and nc
Compute (1) get fz
if fz >fmax then set fz = fmax and ρ=t’/fmax and set
repetition number
Let fc = ρ=t’*1.15. if fc >fmax then set fc=fmax. and set
repetition number
Select the littler one between fc and fz
23. Deterministic Algorithm (cont.)
Large number of slots needed for the desired accuracy
The estimation time is faster than the identification time within an
accuracy. 50 000 tags within an confidence interval of ±500 tags
in 4 .5 seconds.
