通信原理(英文版)8[40页]
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现代通信原理课件(英文版)
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1.2 Digital and Analog source and system
• The generation of communication system
Information input m(t)
Signal processing
Carrier circuits
Transmitter
channel noise
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1.2 Digital and Analog source and system
• Classification of communication patterm • Peer to peer communication :
simplex; half duplex; duplex • Parallel transmitting communication • Series transmitting communication
information from a analog source to the intended receiver(sink)
21
1.3 Deterministic and Random waveforms
1) Deterministic waveform It can be modeled as a completely specified function of time
现代通信原理课件Chapter One
1
Chapter One
Introduction
Why? Information Age Information Superhighway
2
Chapter One Application
military application; common application;
通信原理(英文版)
Chapter 2 Signals
2.1 Classification of Signals
2.1.1 Deterministic signals and random signals
• What is deterministic signal? • What is random signal?
2.1.2 Energy signals and power signals
f (t) f (t T) t
Its frequency spectrum is
/2
C( jn0 )
1 T
/ 2 Ve j n0t dt
/ 2
1 T
V
jn 0
e
j n0 t
/ 2
V e j n0 / 2 e j n0 / 2
f (t) sin(t) Its frequency spefct(rtu)m: f (t 1)
0 t 1 t
C(
jn 0 )
1 T0
T0 / 2 s(t )e jn0t dt
T0 / 2
1 sin(t )e j 2nt dt
Solution: Let the expression of the rectangular pulse be
Then its frequency spectral density is
its
Fourier
tragns(fto)rm:
1
0
t /2 t /2
G() / 2 e jt dt 1 (e j / 2 e j / 2 ) sin( / 2)
2.1 Classification of Signals
2.1.1 Deterministic signals and random signals
• What is deterministic signal? • What is random signal?
2.1.2 Energy signals and power signals
f (t) f (t T) t
Its frequency spectrum is
/2
C( jn0 )
1 T
/ 2 Ve j n0t dt
/ 2
1 T
V
jn 0
e
j n0 t
/ 2
V e j n0 / 2 e j n0 / 2
f (t) sin(t) Its frequency spefct(rtu)m: f (t 1)
0 t 1 t
C(
jn 0 )
1 T0
T0 / 2 s(t )e jn0t dt
T0 / 2
1 sin(t )e j 2nt dt
Solution: Let the expression of the rectangular pulse be
Then its frequency spectral density is
its
Fourier
tragns(fto)rm:
1
0
t /2 t /2
G() / 2 e jt dt 1 (e j / 2 e j / 2 ) sin( / 2)
现代通信原理课件(英文版)(ppt 35页)
are defined on continuum. 4. Digital communication system transfers information
from a digital source to the intended receiver(sink) 5. Analog communication system transfers
2) Note: The general principles of digital and analog modulation apply to all types of channels, although channel characteristics may impose constraints that favor a particular type of signaling
15
1.2 Digital and Analog source and system
2 the advantage of digital system
1）Relatively inexpensive digital circuits may be used
2） Privacy is preserved by using data encryption
8
1.2 Digital and Analog source and system
• The generation of communication system
Information input m(t)
Signal processing
Carrier circuits
Transmitter
channel noise
1. Selection of the information-bearing
from a digital source to the intended receiver(sink) 5. Analog communication system transfers
2) Note: The general principles of digital and analog modulation apply to all types of channels, although channel characteristics may impose constraints that favor a particular type of signaling
15
1.2 Digital and Analog source and system
2 the advantage of digital system
1）Relatively inexpensive digital circuits may be used
2） Privacy is preserved by using data encryption
8
1.2 Digital and Analog source and system
• The generation of communication system
Information input m(t)
Signal processing
Carrier circuits
Transmitter
channel noise
1. Selection of the information-bearing
通信原理(英文版)
6
【Example 2.4】Find the waveform and the frequency spectral density of a sample function. Solution: The definition of the sample function is
sin t Sa ( t ) t
d(t)
1
(f)
0
t
0
f
meaning of d function: It is a pulse with infinite height, infinitesimal width, and unit area. Sa(t) has the following property:
Physical
F ( ) lim
/2 / 2
cos 0 te
jt
sin[( 0 ) / 2] sin[( 0 ) / 2] dt lim 2 ( ) / 2 ( ) / 2 0 0
The frequency spectral density of d(t):
( f ) d (t )e
jt
d (t ) 0
t 0
dt 1 d (t )dt 1
7
d(t)
and its frequency spectral density:
f (t ) f (t 1) t
1
Its frequency spectrum:
1 C ( jn 0 ) T0
T0 / 2
T0 / 2
s(t )e
【Example 2.4】Find the waveform and the frequency spectral density of a sample function. Solution: The definition of the sample function is
sin t Sa ( t ) t
d(t)
1
(f)
0
t
0
f
meaning of d function: It is a pulse with infinite height, infinitesimal width, and unit area. Sa(t) has the following property:
Physical
F ( ) lim
/2 / 2
cos 0 te
jt
sin[( 0 ) / 2] sin[( 0 ) / 2] dt lim 2 ( ) / 2 ( ) / 2 0 0
The frequency spectral density of d(t):
( f ) d (t )e
jt
d (t ) 0
t 0
dt 1 d (t )dt 1
7
d(t)
and its frequency spectral density:
f (t ) f (t 1) t
1
Its frequency spectrum:
1 C ( jn 0 ) T0
T0 / 2
T0 / 2
s(t )e
通信原理 张水英版课件
4
通信发展概况
2. 近代：
1837年：莫尔斯发明电报系统。 1876年：贝尔发明电话。
5
通信发展概况
3.现代 20世纪60年代以后：
数字通信技术进入高速发展阶段。
近20多年：
数字通信迅猛发展； 光纤通信也携手同行。 两者都成为现代通行网的主要支柱。
6
通信发展概况
塞缪尔·莫尔斯 （Samuel
Finley Breese Morse
44
【例如】
有一个4PSK数字通信系统，现传输 20个码元，其中错了2个码元，那 么误码率为10%；如果每个错误码 元有一个比特错误，那么误比特率 为5%；如果每个错误码元有两个比 特错误，那么误比特率为10%；
45
【例如】
已知某四进制数字传输系统的信息传 输速率为2400（bit/s），接收端在 半小时内共收到216个错误码元，试 计算该系统的误码率。
缺点：
占用频带宽 对同步要求高、系统和设备比较复杂
17
1.3 通信系统的分类及通信方式
一、通信系统的分类
按消息的物理特征 按调制方式 按信号特征 按传输媒介 按复用方式
18
1、按消息的物理特征
电报通信系统 电话通信系统 数据通信系统 图像通信系统
。 。 。 。
19
2、按调制方式分类
基带传输：将未经调制的信号直接传送，
第1章
绪论
内容
1.1 通信的基本概念 1.2 通信系统的模型 1.3 通信系统分类及通信方式 1.4 信息的度量 1.5 通信系统的主要性能指标
2
1.1 通信的基本概念
消息、信息和信号 通信 通信发展概况
3
通信发展概况
1. 古代：
通信发展概况
2. 近代：
1837年：莫尔斯发明电报系统。 1876年：贝尔发明电话。
5
通信发展概况
3.现代 20世纪60年代以后：
数字通信技术进入高速发展阶段。
近20多年：
数字通信迅猛发展； 光纤通信也携手同行。 两者都成为现代通行网的主要支柱。
6
通信发展概况
塞缪尔·莫尔斯 （Samuel
Finley Breese Morse
44
【例如】
有一个4PSK数字通信系统，现传输 20个码元，其中错了2个码元，那 么误码率为10%；如果每个错误码 元有一个比特错误，那么误比特率 为5%；如果每个错误码元有两个比 特错误，那么误比特率为10%；
45
【例如】
已知某四进制数字传输系统的信息传 输速率为2400（bit/s），接收端在 半小时内共收到216个错误码元，试 计算该系统的误码率。
缺点：
占用频带宽 对同步要求高、系统和设备比较复杂
17
1.3 通信系统的分类及通信方式
一、通信系统的分类
按消息的物理特征 按调制方式 按信号特征 按传输媒介 按复用方式
18
1、按消息的物理特征
电报通信系统 电话通信系统 数据通信系统 图像通信系统
。 。 。 。
19
2、按调制方式分类
基带传输：将未经调制的信号直接传送，
第1章
绪论
内容
1.1 通信的基本概念 1.2 通信系统的模型 1.3 通信系统分类及通信方式 1.4 信息的度量 1.5 通信系统的主要性能指标
2
1.1 通信的基本概念
消息、信息和信号 通信 通信发展概况
3
通信发展概况
1. 古代：
通信原理(英文版)
can be generalized to power signal.
10
Energy spectral density
Let the energy of an energy signal s(t) be E, then the energy
of
the
signal
is
decided
byE
s2 (t)dt
is
S() s(t)e jt dt
The inverse Fourier transform of S() is the original signal:
s(t) S ()e jtd
【Example 2.3】Find the frequency spectral density of a rectangular pulse.
0, 当t 0,
u(t)
1,
当t 0
1
u(t) = d(t)
0
Fig. 2.2.6 Unit step function
t
➢ Difference between frequency spectral density S(f) of
energy signal and frequency spectrum of periodic power
Chapter 2 Signals
2.1 Classification of Signals
2.1.1 Deterministic signals and random signals
➢ What is deterministic signal? ➢ What is random signal?
通信原理(数字通信)PCM(41页英文ppt)
6/41
A First Course in Digital Communications
Chapter 4: Sampling and Quantization
Sampling Theorem
Theorem A signal having no frequency components above W Hertz is completely described by specifying the values of the signal at periodic time instants that are separated by at most 1/2W seconds. fs ≥ 2W is known as the Nyquist criterion, the sampling rate fs = 2W is called the Nyquist rate and its reciprocal called the Nyquist interval. Ideal sampling is not practical ⇒ Need practical sampling methods.
Sampling: How many samples per second are needed to exactly represent the signal and how to reconstruct the analog message from the samples? Quantization: To represent the sample value by a digital symbol chosen from a finite set. What is the choice of a discrete set of amplitudes to represent the continuous range of possible amplitudes and how to measure the distortion due to quantization? Encoding: Map the quantized signal sample into a string of digital, typically binary, symbols.
A First Course in Digital Communications
Chapter 4: Sampling and Quantization
Sampling Theorem
Theorem A signal having no frequency components above W Hertz is completely described by specifying the values of the signal at periodic time instants that are separated by at most 1/2W seconds. fs ≥ 2W is known as the Nyquist criterion, the sampling rate fs = 2W is called the Nyquist rate and its reciprocal called the Nyquist interval. Ideal sampling is not practical ⇒ Need practical sampling methods.
Sampling: How many samples per second are needed to exactly represent the signal and how to reconstruct the analog message from the samples? Quantization: To represent the sample value by a digital symbol chosen from a finite set. What is the choice of a discrete set of amplitudes to represent the continuous range of possible amplitudes and how to measure the distortion due to quantization? Encoding: Map the quantized signal sample into a string of digital, typically binary, symbols.
通信原理(英文版)
# For an equal probability binary symbol:
I = log2 [1/P(x)] = log2 [1/(1/2)] = 1 bit
4
# For an equal probability M-ary symbol:
I = log2 [1/P(x)] = log2 [1/(1/M)] = log2 M bit If M = 2k ，then I = k bit
Out put S/N increases with bandwidth according to exponential law.
10
Digital communication system model 11
2
1.2 Message, information & signal
Message：speech, letters, figures, images…
Information：effective content of message. Different types of messages may contain the same information
5
1.3 Digital Communication
1.3.1 Basic concept
Two categories of signals • Analog signal：Its voltage or current
can be expressed by a continuous function of time. For example, speech signal.
# Ex: “Rainfall will be 1 mm tomorrow” – information content small
I = log2 [1/P(x)] = log2 [1/(1/2)] = 1 bit
4
# For an equal probability M-ary symbol:
I = log2 [1/P(x)] = log2 [1/(1/M)] = log2 M bit If M = 2k ，then I = k bit
Out put S/N increases with bandwidth according to exponential law.
10
Digital communication system model 11
2
1.2 Message, information & signal
Message：speech, letters, figures, images…
Information：effective content of message. Different types of messages may contain the same information
5
1.3 Digital Communication
1.3.1 Basic concept
Two categories of signals • Analog signal：Its voltage or current
can be expressed by a continuous function of time. For example, speech signal.
# Ex: “Rainfall will be 1 mm tomorrow” – information content small
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T
0
n 2 (t )dt
2
k dimensional combined probability density function of the received voltage r(t) = s(t) + n(t) When the symbol 0 is transmitted
f 0 (r )
f ( n)
where n f 0 H
2 n
2 n
k
exp n0
0
n 2 (t )dt
f (n) f k (n1 , n2 , , nk ) f (n1 ) f (n2 ) f (nk )
Note that f (n) is not a function of time. n is a k dimensional quantity, which can be regarded as a point on the k dimensional space. f (n) is decided only by the noise energy
The meaning of “optimum” － minimum error probability Decision rule for optimum receiving Received vector r may be regarded as a point in a k dimensional space. The k dimensional space can be partitioned into two regions:A0 and A1
f (ni ) ni2 exp 2 2 2 n n 1
where n － standard deviation of the noise n2 － variance of the noise
1
k dimensional combined probability density function of noise sample voltage
Chapter 8 Optimum Receiving of Digital Signal
8.1 Statistical Characteristics of Digital Signal
Assume the highest transmission frequency of the communication system is fH , and the received voltage is expressed by its sample. One dimensional probability density of the noise sample voltage If the voltage is sampled at the sampling rate 2fH in a symbol interval; then k samples are obtained: n1, n2, …, ni, …, nk , and each sample is a random variable with normal distribution. Its one dimensional probability density can be written as
f1 ( r )
1 2 n
k
1 exp n0
0 r (t ) s1 (t ) dt
T 2
where s1 (t) － signal waveform of the transmitted symbol 1
3
8.2 Optimum Receiving Criterion of Digital Signal
f k (n1 , n2 , , nk ) f (n1 ) f (n2 ) f (nk )
1 2 n
k
1 exp 2 2 n
ቤተ መጻሕፍቲ ባይዱ
ni2 i 1
k
Average power of the received noise in a symbol duration T: k k 1 k 2 1 1 T 2 1 2 ni 2 f T ni or T 0 n (t )dt 2 f T ni2 k i 1 i 1 H i 1 H Substituting the above equation into the uppermost equation, we obtain 1 T 1
1 2 n
k
1 exp n0
0 r (t ) s0 (t ) dt
T 2
where r (t) － sum of the signal and noise voltages s0 (t) － signal waveform of the transmitted symbol 0 When the symbol 1 is transmitted
A0 A
0
A1
A1
Decision rule: If the received vector r falls into the region A0, then the decision is symbol o transmitted; If the received vector r falls into the region A1, then the decision is symbol o transmitted;
4
Total symbol error probability:
Pe P(1) P( A0 / 1) P(0) P( A1 / 0)
where
P( A0 / 1) f1 (r )dr － conditional probability of
A0
the vector r fallen in region A0 when 1 is transmitted