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1 Overview of RFID System Anti-Collision Technology
Similarly, in digital communication systems, if we focus only on the discussion
of the coding and decoding, it is beneficial to adopt the concept of coding channel.
Coding channel refers to the part from the output of the encoder to the input of the
decoder. This is defined because, from the perspective of coding and decoding, the
output of the encoder is a sequence of numbers, while the input of the decoder is also
a sequence of numbers, which may be different sequences of numbers. Therefore,
from the output of the encoder to the input of the decoder, it can be summarized by
a box that transforms the sequence of numbers.
In order to analyze the general characteristics of a channel and its influence on
signal transmission, the mathematical models of the modulated channel and coded
channel are introduced based on the definition of a channel.
First, the modulation channel model is discussed. In any mode of communication with a modulation and demodulation process, the modulated signal output by
the modulator is fed into the modulation channel. For studying the performance of
modulation and demodulation, we only care about the final result of the modulated
signal after it passes through the modulation channel, that is, we only care about
the relationship between the output signal and the input signal of the modulation
channel, regardless of the transformation of the signal in the modulation channel
or the transmission media selected. After a lot of investigation on the modulation
channel, it can be found that it has the following commonalities:
(1) There are a pair (or many) of inputs and a pair (or many) of outputs.
(2) Most channels are linear, which satisfies the superposition principle.
(3) The signal has a delay time through the channel, and it is subject to (fixed or
time-varying) losses.
(4) Even if there is no signal input, there is still some power output (noise) at the
output end of the channel.
According to the above commonalities, we can use a two-pair (or multi-pair)
time-varying linear network to represent the modulation channel, which is called the
modulation channel model.
For the two-pair channel model, the relation between its output and input is
e 0 (t) = f [e i (t)] + n(t)
(1.1)
where e i (t) is the input modulated signal; e o (t) is the total channel output waveform;
n(t) is the additive noise (or additive interference). Here n(t) is independent of e i (t).
f [e i (t)] represents the linear transformation of the modulated signal through the
network.
Now, let’s say we can write f [e i (t)] as k(t)e i (t), where k(t) depends on the
properties of the network, and k(t) times e i (t) reflects what the properties of the
network do to e i (t). The existence of k(t) is a distraction for e i (t), usually referred
to as multiplicative noise. Thus, Eq. (1.1) can be expressed as
e 0 (t) = k(t)e i (t) + n(t)
(1.2)
1 Overview of RFID System Anti-Collision Technology
Similarly, in digital communication systems, if we focus only on the discussion
of the coding and decoding, it is beneficial to adopt the concept of coding channel.
Coding channel refers to the part from the output of the encoder to the input of the
decoder. This is defined because, from the perspective of coding and decoding, the
output of the encoder is a sequence of numbers, while the input of the decoder is also
a sequence of numbers, which may be different sequences of numbers. Therefore,
from the output of the encoder to the input of the decoder, it can be summarized by
a box that transforms the sequence of numbers.
In order to analyze the general characteristics of a channel and its influence on
signal transmission, the mathematical models of the modulated channel and coded
channel are introduced based on the definition of a channel.
First, the modulation channel model is discussed. In any mode of communication with a modulation and demodulation process, the modulated signal output by
the modulator is fed into the modulation channel. For studying the performance of
modulation and demodulation, we only care about the final result of the modulated
signal after it passes through the modulation channel, that is, we only care about
the relationship between the output signal and the input signal of the modulation
channel, regardless of the transformation of the signal in the modulation channel
or the transmission media selected. After a lot of investigation on the modulation
channel, it can be found that it has the following commonalities:
(1) There are a pair (or many) of inputs and a pair (or many) of outputs.
(2) Most channels are linear, which satisfies the superposition principle.
(3) The signal has a delay time through the channel, and it is subject to (fixed or
time-varying) losses.
(4) Even if there is no signal input, there is still some power output (noise) at the
output end of the channel.
According to the above commonalities, we can use a two-pair (or multi-pair)
time-varying linear network to represent the modulation channel, which is called the
modulation channel model.
For the two-pair channel model, the relation between its output and input is
e 0 (t) = f [e i (t)] + n(t)
(1.1)
where e i (t) is the input modulated signal; e o (t) is the total channel output waveform;
n(t) is the additive noise (or additive interference). Here n(t) is independent of e i (t).
f [e i (t)] represents the linear transformation of the modulated signal through the
network.
Now, let’s say we can write f [e i (t)] as k(t)e i (t), where k(t) depends on the
properties of the network, and k(t) times e i (t) reflects what the properties of the
network do to e i (t). The existence of k(t) is a distraction for e i (t), usually referred
to as multiplicative noise. Thus, Eq. (1.1) can be expressed as
e 0 (t) = k(t)e i (t) + n(t)
(1.2)