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Introduction to

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Contents:• DEFINITION OF SPREAD SPECTRUM ( SS )

• CHARACTERISTICS OF SPREAD SPECTRUM

• BASIC PRINCIPLES OF DIRECT SEQUENCE SPREAD SPECTRUM ( DSSS )

• BASIC PRINCIPLES OF FREQUENCY HOPPING SPREAD SPECTRUM ( FHSS )

• PERFORMANCE IN THE PRESENCE OF INTERFERENCE

• PSEUDO-NOISE SEQUENCES ( PN )

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Definition of Spread Spectrum :

Spread spectrum is a modulation method applied to digitally modulated signals that increases the transmit signal bandwidth to a value much larger than is needed to transmit the underlying information bits.

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Spread Spectrum Signal Characteristics :

1. They are difficult to intercept for unauthorized person.

2. They are easily hidden, it is difficult to even detect their presence in many cases.

3. They are resistant to jamming.4. They have an asynchronous multiple-access

capability.5. They provide a measure of immunity to

distortion due to multipath propagation.

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Spread Spectrum Conditions:

• The signal occupies a bandwidth much larger than is needed for the information signal.

• The spread spectrum modulation is done using a spreading code, which is independent of the data in the signal.

• Dispreading at the receiver is done by correlating the received signal with a synchronized copy of the spreading code.

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Processing Gain :

The spread spectrum increases the bandwidth of the message signal by a factor N, called the processing gain where is the message signal bandwidth, ss is the corresponding SS signal bandwidth.

, N > 1

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Spread Spectrum Techniques:

There are several forms of spread Spectrums :

1. Direct sequence spread spectrum (DS/SS)2. Frequency hopping spread spectrum

(FH/SS)

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Direct Sequence Spread Spectrum

Building block of DSSS system.

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The channel output given by:

y(t) = x(t) + j(t)

= c(t) s(t)+ j(t)

The Coherent detector input u(t) : u(t) =c(t) y(t)

= s(t)+ c(t) j(t)

Where: for all t

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Spreading

Input:

•Binary data dt with symbol rate Rs = 1/Ts ( = Bit rate Rb for BPSK ).•Pseudo-noise code pnt with chip rate Rc = 1/Tc

Spreading:

The binary data is multiplied with the PN sequence which is independent on the binary data to produce the transmitted signal txb.

txb = dt . pnt

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The effect of multiplication is to spread the base band bandwidth Rs of dt to a base band bandwidth of RcBwinfo = Rs << BWss = Rc

Processing gain Gp=BWss/BWinfo = Rc/Rs = Tb/Tc =Nc

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Modulation

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DispreadingThe spread spectrum signal cannot be detected by a narrow band receiver. In the receiver, the received base band signal is multiplied with the PN code Pnr .

• If Pnt = Pnr and synchronized to the PN code in the received data, then the recovered binary data is produced on dr. the effect of multiplication of the spread spectrum signal rxb with the PN sequence pnt used in the transmitter to dispread the bandwidth of rxb to Rs.

• If then there is no dispreading action.

A receiver not knowing the PN code of transmitter cannot produce the transmitted data.

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Demodulation

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t:

Pnt = Pnr

Autocorrelation Ra 0)= average ( Pnt . Pnt)

+ =1

t:

Cross correlation Rc 0) = average ( Pnt . Pnt)

<< 1 , for all = 0

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The operating principle of DS-SS multiple access. Two users are sending two separate messages m1(t) and m2(t) through the same channel in the same frequency band at the same time.

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Pseudo-Noise Sequence

A pseudo-noise ( PN ) sequence is a periodic binary sequence with a noise like waveform that is usually generated by a means of a feed back shift register. It consists of a shift register made up of m flip-flops and a logic circuit to form a multiloop feedback circuit.

Feedback shift register.

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Properties of the PN sequences:

• An m-bit codeword produces a sequence of length

• The peak values are

• The autocorrelation function is equal to –1 other than at the peaks.

• The O/P sequence contains ones & Zeros.

• Their power density spectrum is uniform so they may used as white noise sources.

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The autocorrelation function of a bipolar waveform three-stage pseudo noise generator

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We use a correlation receiver to determine whether a +1 or a –1 was transmitted at time t

PN Decorrelators

PN Matched Filters

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A typical matched filter implements convolution using FIR filter whose coefficients are the time inverse of the expected PN sequence to decode the transmitted data.

If the receiver is not synchronized, then the received signal will propagate through the matched filter, which outputs the complete correlation function. The large peak confirms that the correct code is being received providing accurate synchronization. The output of the FIR filter is the decoded data.

The polarity of the large correlation peaks indicates the data value.

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Positive

1. Signal hiding (lower power density, noise-like) , non interference.

2. Secure communications (Privacy).

3. Code division multiple access CDMA.

4. Mitigation of multi path effect.

5. Protection to international interference (jamming)

6. Rejection of unintentional interference (narrow band)

Positive

1. Signal hiding (lower power density, noise-like) , non interference.

2. Secure communications (Privacy).

3. Code division multiple access CDMA.

4. Mitigation of multi path effect.

5. Protection to international interference (jamming)

6. Rejection of unintentional interference (narrow band)

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Negative

1. No improve in performance in the presence of

Gaussian noise.

2. Increase bandwidth (frequency usage, wideband

receiver).

3. Increase complexity and computational load.

Negative

1. No improve in performance in the presence of

Gaussian noise.

2. Increase bandwidth (frequency usage, wideband

receiver).

3. Increase complexity and computational load.

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References:References:

• Simon Haykin “Communication Systems” , John Wily

& Sons 2001.

• Emmanuel C. Ifeachor “Digital Signal Processing”,

Prentice Hall 2002.

• ir. J. Meel “Spread Spectrum introduction” DE NAYER

INSTITUTE. Belgium (www.denayer.be).

• B. P. Lathi “Modern Digital and Analog Communication

Systems”, Oxford University Press 1998.

• Simon Haykin “Communication Systems” , John Wily

& Sons 2001.

• Emmanuel C. Ifeachor “Digital Signal Processing”,

Prentice Hall 2002.

• ir. J. Meel “Spread Spectrum introduction” DE NAYER

INSTITUTE. Belgium (www.denayer.be).

• B. P. Lathi “Modern Digital and Analog Communication

Systems”, Oxford University Press 1998.