DSSS BPSK

DSSS BPSK with Jamming Signal

1.

1.1

1

LITERATURE SURVEY

INTRODUCTION TO SPREAD SPECTRUM COMMUNICATION

In all communications systems, the modulated waveform occupies a frequency bandwidth that is dependent upon the modulation method used and the data being sent. In a spread spectrum system, the transmitted bandwidth of the signal has been "spread" over a larger bandwidth than the original modulated bandwidth [1]. This transforms the power spectral density into a more uniform spectrum much like that of noise [2]. [2]. To qualify as spread spectrum, a system must satisfy the following three conditions [3]:

1.

The signal occupies a bandwidth much in excess of the minimum

bandwidth required by the information.

2.

Spreading is accomplished through the use of a code signal independent of

the data itself.

3.

At the receiver, despreading is accomplished by the correlation of the

received signal with a replica of the spreading co de used at the transmitter.

Spread spectrum systems is a class of (primarily) wireless digital communication systems specifically designed to overcome a jamming situation, i.e., when an adversary intends to disrupt the communication. To disrupt the communication, the adversary needs to do two things,

(a) to detect that a transmission is taking place and (b) to transmit a jamming signal which is designed to co nfuse the receiver.

Department of Electronics and Communication, LMCST


2

ffi

A spread spectrum system is therefore designed to make these tasks as di cult as

ffi

possible. Firstly, the transmitted signal should be di cult to detect by an adversary, i.e., the signal should have a low probability of intercept (LPI). Secondly, the signal should be

ffi

di cult to disturb with a jamming signal, i.e., the transmitted signal should possess an anti-jamming (AJ) property.

Clearly, the intentional jamming situation is most common in a military context, and spread spectrum systems were originally developed specifically specifically for military applications. However, in later years, spread spectrum systems have been introduced in many commercial applications that require good anti-jamming properties. An example of commercial spread spectrum systems are systems that are designed to be used in so-called unlicensensed bands, such as the Industry, Scientific, Medical (ISM) band around 2.4 GHz. Typical applications are here cordless telephones, wireless LANs, and cable replacement systems as Bluetooth.

Since the band is unlicensed, there is no central control over the radio resources, and the systems have to function even in the presence of severe interference from other communication systems and other electrical and electronic equipment (e.g.,microwave ovens, radars, etc.). Here the jamming is not intentional, but the interference may nevertheless be enough to disrupt the communication for non-spread spectrum systems.

Code-division multiple access systems (CDMA systems) use spread spectrum techniques to provide communication to several concurrent users. CDMA is used in one second generation (IS-95) and several third generation wireless cellular systems (e.g., cdma2000 and WCDMA). One advantage of using jamming-resistant signals in these applications is that the radio resource management (primarily the channel allocation to the active users) is significantly reduced.



2

ffi

A spread spectrum system is therefore designed to make these tasks as di cult as

ffi

possible. Firstly, the transmitted signal should be di cult to detect by an adversary, i.e., the signal should have a low probability of intercept (LPI). Secondly, the signal should be

ffi

di cult to disturb with a jamming signal, i.e., the transmitted signal should possess an anti-jamming (AJ) property.

Clearly, the intentional jamming situation is most common in a military context, and spread spectrum systems were originally developed specifically specifically for military applications. However, in later years, spread spectrum systems have been introduced in many commercial applications that require good anti-jamming properties. An example of commercial spread spectrum systems are systems that are designed to be used in so-called unlicensensed bands, such as the Industry, Scientific, Medical (ISM) band around 2.4 GHz. Typical applications are here cordless telephones, wireless LANs, and cable replacement systems as Bluetooth.

Since the band is unlicensed, there is no central control over the radio resources, and the systems have to function even in the presence of severe interference from other communication systems and other electrical and electronic equipment (e.g.,microwave ovens, radars, etc.). Here the jamming is not intentional, but the interference may nevertheless be enough to disrupt the communication for non-spread spectrum systems.

Code-division multiple access systems (CDMA systems) use spread spectrum techniques to provide communication to several concurrent users. CDMA is used in one second generation (IS-95) and several third generation wireless cellular systems (e.g., cdma2000 and WCDMA). One advantage of using jamming-resistant signals in these applications is that the radio resource management (primarily the channel allocation to the active users) is significantly reduced.



3

The name spread spectrum stems from the fact that the transmitted signal occupies a much wider frequency band than what is necessary. This enables the transmitter to hide

ff

its signal in a large bandwidth. There are many di erent erent ways to use the bandwidth. The most common ones are called direct-sequence (DS) and frequency-hopping (FH) spread spectrum (SS).

In FH-SS, the transmitter changes the carrier frequency of the relatively narrowband transmitted signal in a fashion which appears random to the jammer. At any given time, only a small fraction of the available bandwidth is used, and exactly which fraction is made a secret for the jammer. The jammer is therefore uncertain where in the system bandwidth the signal is being transmitted, and it is di

ffi

cult for the jammer to

detect and disturb the transmitted signal. In DS-SS, the power of the transmitted signal is spread over the entire system bandwidth in a way that looks random for the jammer.

Again, this makes the signal hard to detect and to jam. Several other spread spectrum strategies are available; however, the clear majority of the implemented systems are either frequency-hopping or direct-sequence (or h ybrids of these basic schemes).

The bandwidth necessary for the transmission of a digital communications signal is determined by the data rate, Rb, (measured in the number of information bits transmitted per second) and the chosen modulation format. For binary pass band modulation mod ulation (suitable for wireless transmission), the minimum required bandwidth is approximately Wmin = R b Hz. If we denote the actual bandwidth of the transmitted signal by Wss, then for a spread

ffi

spectrum system Wss >>R b. The spectral e ciency of the spread spectrum communication link is R b/Wss bits/second/Hz.



4

ffi

By definition, the definition, the spectral e ciency of a spread spectrum system is very low. This seems to render spread spectrum techniques useless for systems that need to use spectrum

ffi

e ciently. However, this is not necessarily the case since several users using spread spectrum signals can share the same bandwidth (at the same time), and the system’s

ffi

spectral e ciency (measured in the total number of information bits transmitted per second) may be still be very good, even if the individual links have low spectral

ffi

e ciencies.

We know that we can communicate over a channel disturbed by additive white Gaussian noise (an AWGN channel). White noise has infinite power, but since the power is spread over an infinite number of signal space dimensions (or infinite bandwidth), the power per signal space dimension is finite. Hence, by concentrating the transmitter power to a finite-dimensional finite-dimensional signal space, we can gain a power advantage over the noise.

The same idea is used in a jamming situation. However, we must make the choice of signal space dimensions used for transmission a secret for the jammer. Otherwise, the jammer can concentrate its power to the same dimensions, and nothing is gained. This implies that we need to hide the transmitted signal in a space with many more dimensions than what is needed for the transmitted signal.

Spread spectrum is developed initially for military ant jammin g communications in the mid-1950s, spread spectrum (SS) has been found a wide range of applications in commercial wireless systems [4]. The underlying idea of spread spectrum is to spread a signal over a large frequency band and transmit it with low power per unit bandwidth. Among many possible ways of spreading the bandwidth, the predominant type is DS spread-spectrum. DS spread spectrum achieves band spreading by modulating the information symbol stream with a higher rate chip sequence.



5

In practice, pseudorandom noise (PN) chip sequences are often employed to make the spreading signal as random as possible. After spreading, the chip sequence is usually shaped by a chip pulse shaping filter, p(t), to limit the bandwidth of the output. Most of the work done in spread spectrum throughout the 1950s, 1960s and 1970s was heavily backed by the military and drowned in secrecy. Spread spectrum also has wide application in many other fields such as Wireless local area network (WLAN), Space systems, Global positioning system (GPS).etc.

Other unevitable application of DSSS is in CDMA technology. In CDMA spreadspectrum transmission, user channels are created by assigning different codes to different users. This type of system provides privacy by controlling distribution of user-unique code sequences. The new scheme in CDMA provides flexibility in the selection of modulation pcodes and FH patterns. By partitioning the modulation codes, our two-level scheme can be modified to support more possible users without increasing the number of FH patterns [5]. DSSS also provide modifications to conventional MT-DS-SS signaling to both improve spectral efficiency and reduce receiver RF complexity.

The first modification to the conventional MT scheme is a simple reduction in subcarrier frequency spacing, which provides a small improvement in bandwidth efficiency at no cost in complexity or performance. The second modification entails the use of fewer receiver local oscillators (LOs) than the number of subcarrier [6 ].

The FHSS and DSSS signals are widely used in military satellite communication systems. a new concept of "normalized throughput of information" is proposed according to the property of jammed signals.[7].Spread-spectrum technology will find more and more commercial applications ranging from cordless telephony to wireless LAN and wireless data, digital cellular telephony and even p ersonal communication services.



6

Anti-jamming techniques are critical to maintain the integrity and functionality of GPS systems in various applications. One of the major problems with existing array-based anti-jamming GPS receivers is the errors introduced in the carrier phase, affecting the GPS solution [8].

Spread spectrum (SS) has its origin in the military communications

1) susceptible to detection=interception by the enemy and 2) vulnerable to intentionally introduced unfriendly interference (jamming).

Communication

systems

that

employ

spread

spectrum

to

reduce

the

communicator’s detectability and combat the enemy-introduced interference are respectively referred to a slow probability of intercept (LPI) and antijam (AJ) communication systems. With the change in the current world political situation where in the U.S. Department of Defense (DOD) has reduced its emphasis on the development and acquisition of new communication systems for the original purposes, a host of new commercial applications for SS has evolved, particularly in the area of cellular mobile communications. This shift from military to commercial applications of SS has demonstrated that the basic concepts that make SS techniques so useful in the military can also be put to practical peacetime use. In the next section, we give a simple description of these basic concepts using the original military application as the basis of explanation.



1.2

7

TYPES OF SPREAD SPECTRUM COMMUNICATION

Spread Spectrum is a modulation technique that spreads a signal’s power over a wide band of frequencies.

Fig 1.2.1 Spread Spectrum

Three Types of Spread Spectrum Communications are



Frequency Hopping



Time Hopping



Direct Sequence

1.2.1. Frequency Hopping

Frequency-hopping spread spectrum (FHSS) is a method of transmitting radio signals

by

rapidly

switching

a carrier among

many

frequency channels, using

a pseudorandom sequence known to both transmitter and receiver. In this the signal is rapidly switched between different frequencies within the hopping bandwidth pseudorandomly, and the receiver knows beforehand where to find the signal at any given time.



8

In an FH-CDMA system, a transmitter "hops" between available frequencies according to a specified algorithm, which can be either random or preplanned. The transmitter operates in synchronization with a receiver, which remains tuned to the same center frequency as the transmitter. A short burst of data is transmitted on a narrowband. Then, the transmitter tunes to another frequency and transmits again. The receiver thus is capable of hopping its frequency over a given bandwidth several times a second, transmitting on one frequency for a certain period of time, then hopping to another frequency and transmitting again. Frequency hopping requires a much wider bandwidth than is needed to transmit the same information using only one carrier frequency. It is utilized as a multiple access method in the frequency-hopping code division multiple access (FH-CDMA) scheme.

Fig 1.2.2 Carrier Frequency Hopping from one frequency to other

1.2.2. Time hopping

Time-hopping (TH) is a communications signal technique which can be used to achieve anti-jamming (AJ) or low probability of intercept (LPI). It can also refer to pulsek

position modulation, which in its simplest form employs 2 discrete pulses to transmit k bit(s) per pulse. To achieve LPI, the transmission time is changed randomly by varying the period and duty cycle of the pulse (carrier) using a pseudo-random sequence.



9

The transmitted signal will then have intermittent start and stop times. Although often used to form hybrid spread-spectrum (SS) systems, TH is strictly speaking a non-SS technique. Spreading of the spectrum is caused by other factors associated with TH, such as using pulses with low duty cycle having a wide frequency response. Here the signal is transmitted in short bursts pseudo-randomly, and the receiver knows beforehand when to expect the burst. An example of hybrid SS is TH-FHSS or hybrid TDMA (time division multiple access).

. Fig 1.2.3 Time Hopping

1.2.3. Direct sequence

The digital data is directly coded at a much higher frequency. The code is generated pseudo-randomly, the receiver knows how to generate the same code, and correlates the received signal with that code to extract the data.

Fig1.2.4 General Structure of Spread Spectrum Department of Electronics and Communication, LMCST


10

1.3 DIRECT SEQUENCE SPREAD SPECTRUM

In telecommunications, direct sequence spread spectrum (DSSS) is a modulation technique. As with other spread spectrum technologies, the transmitted signal takes up more bandwidth than the information signal that modulates the carrier or broadcast frequency. The name 'spread spectrum' comes from the fact that the carrier signals occur over the full bandwidth (spectrum) of a device's transmitting frequency.

Characteristics of DSSS



Highest potential data rates from individual physical layers



Smallest number of geographically separate radio cells due to a limited number of channels.



Direct sequence, has a high potential for data rates, which would be best for bandwidth intensive applications. In general direct sequence modulation c(t)is formed by linearly modulating the output sequence c{n} of a pseudorandom number generator onto a train of pulses, each having a duration Tc called the chip time. In mathematical form,

  ∑ 

(1)

Where p(t) is the basic pulse shape and is assumed to be of rectangular form. This type of modulation is usually used with binar y phase-shift-keyed (BPSK) information.

The real transmitted signal is

* Department of Electronics and Communication, LMCST

}

(2)


11

Since Tc is chosen so that T b>>Tc, then relative to the bandwidth of the BPSK information signal, the bandwidth of the DS BPSK signal is effectively increased by the ratio T b=Tc.

1.3.1 Signal Transmission Method

Direct-sequence spread-spectrum transmissions multiply the data being transmitted by a "noise" signal. This noise signal is a pseudorandom sequence of 1 and −1 values, at a frequency much higher than that of the original signal. The resulting signal resembles white noise. However, this noise-like signal can be used to exactly reconstruct the original data at the receiving end, by multiplying it by the same pseudorandom sequence (because 1 × 1 = 1, and −1 × −1 = 1). This process, known as "de-spreading", mathematically constitutes a correlation of the transmitted PN sequence with the PN sequence that the receiver believes the transmitter is using. The resulting effect of enhancing signal to noise ratio on the channel is called process gain. This effect can be made larger by employing a longer PN sequence and more chips per bit, but physical devices used to generate the PN sequence impose practical limits on attainable processing gain.

If an undesired transmitter transmits on the same channel but with a different PN sequence (or no sequence at all), the de-spreading process results in no processing gain for that signal. This effect is the basis for the code division multiple access (CDMA) property of DSSS, which allows multiple transmitters to share the same channel within the limits of the cross-correlation properties of their PN sequences.



12

1.3.2 PN Sequence

A pseudo noise(PN) sequence is a periodic binary sequence with a noise like waveform that is usually generated by means of a feed back shift register. A feed back shift register consist of an ordinary shift register made up of number of flip flops and a logic circuit that are inter connected to form a multiloop feedback circuit. The flip flops in the shifT register are regulated by a single timing clock. The logical circuit in feedback shift register forms a boolean function.

gr

gr-1

gr-2

mr-1

mr-2

g1

g0

m0

Fig 1.3.1 Structure of a PN Sequence Generator

In CDMA communication system, for each channel the base station generates a unique code that changes for every connection. The base station adds together all the coded transmissions for every subscriber. The subscriber unit correctly generates its own matching code and uses it to extract the appropriate signals.



13

In order for all this to occur, the pseudo-random code must have the following properties:



It must be deterministic. The subscriber station must be able to independently generate the code that matches the base station code.



It must appear random to a listener without prior knowledge of the code (i.e. it has the statistical properties of sampled white noise).



The cross-correlation between any two codes must be small (see below for more information on code correlation).



The code must have a long period (i.e. a long time before the code repeats itself).

A maximal length sequence is a simple shift register generator (SSRG) is a shift register generator in which all feedback signals are returned to a single input.The sequence generated by an N-stage SSRG is a maximal length sequence if it has length 2N-1.

The properties are:



Maximal length sequences have pseudorandomness properties



2



Balanced runs, except there is no run of N zeros



Binary valued autocorrelation function equal to 1 if M equals 0 and -1/N

N-1

N-1

ones and 2

– 1 zeros

otherwise.

1.3.3 Code Correlation

In this context, correlation has a specific mathematical meaning. In general the correlation function has these properties: 

It equals 1 if the two codes are identical



It equals 0 of the two codes have nothing in common



14

Intermediate values indicate how much the codes have in common. The more they have in common, the harder it is for the receiver to extract the appropriate signal. There are two correlation functions:



Cross-Correlation: The correlation of two different codes. As we’ve said, this should be as small as possible.



Auto-Correlation: The correlation of a code with a time-delayed version of itself. In order to reject multi-path interference, this function should equal 0 for any time delay other than zero.

The receiver uses cross-correlation to separate the appropriate signal from signals meant for other receivers, and auto-correlation to reject multi-path interference.

1.3.4 Pseudo-Noise Spreading

The coded Information data modulates the pseudo-random code, as shown in given fig 1.6.

Fig 1.3.2 Spreading of the sequence



15

Some terminology related to the pseudo-random code:



Chipping Frequency (fc): the bit rate of the PN code.



Information rate (fi): the bit rate of the digital data.



Chip: One bit of the PN code.



Epoch: The length of time before the code starts repeating itself (the period of the code). The epoch must be longer than the round trip propagation delay (The epoch is on the order of several seconds).

1.3.5 Code Acquisition and Lock

The receiver generates its own complex PN code that matches the code generated by the transmitter. However, the local code must be phase-locked to the encoded data.

1.3.6 Correlation and Data Despreading

Once the PN code is phase-locked to the pilot, the received signal is sent to a correlator that multiplies it with the complex PN code, extracting the actual data. It is shown in fig 1.7.

Fig 1.3.3 Despreading of the signal



16

Thus the local PN random generator that generates the PN waveform at the receiver used for despreading must be aligned (synchronized) to within one chip of the PN waveform of the received DS=BPSK signal. This is accomplished by employing some sort of search algorithm which typically steps the local PN waveform sequentially in time by a fraction of a chip (e.g., half a chip) and at each position searches for a high degree of correlation between the received and local PN reference waveforms. The search terminates when the correlation exceeds a given threshold, which is an indication that the alignment has been achieved. After bringing the two PN waveforms into coarse alignment, a tracking algorithm is employed to maintain fine alignment.



17

2. PROPOSED METHOD

2.1 AIM

Our aim is to carry out the baseband simulation of a DSSS communication system, including the transmitter and receiver end and to estimate the bit error rate (BER). This DSSS system uses BPSK modulation in AWGN channel. Performance comparison between a basic BPSK and DSSS system is to be done. Further we wish to extend these comparisons to evaluate the performance of the above two systems to sinusoidal jamming interference. The antijamming characteristics and the processing gain of the DSSS system is further explored for different values of jamming power; which is proportional to the square of the amplitude of the jamming signal.

2.2 MOTIVATION FOR BASEBAND SIMULATION

The baseband description of the transmitted signal is ve ry convenient because it is more compact than the passband signal as it does not include the carrier component while retaining all relevant information.



2.2.1

18

Pass Band System

√ 

√  NP(t)

x

LPF

R 1(t)

x

x

LPF

R Q(t)

√ 

√ 

S1(t)

x SP(t) h p (t)

+ SQ(t)

+

R P(t)

Fig 2.2.1 Pass Band System

2.2.2 Baseband Equivalent System

NP(t) R P(t)

SP(t)

+

h p (t)

Fig 2.2.2 Equivalent baseband diagram

The passband system can be interpreted as follows to yield an equivalent s ystem that employs only baseband signals: 

baseband equivalent transmitted signal: S (t ) = S I (t ) − j · S Q(t )


(3)


19



baseband equivalent channel with complex valued impulse response: h(t ).



baseband equivalent received signal: R(t ) = R I (t ) − j · RQ(t ).



(4)

complex valued, additive Gaussian noise: N (t )

Thus it can be summarized as follows



The baseband equivalent channel is much simpler than the passband model.

o Up and down conversion are eliminated. o Expressions for signals do not contain carrier terms. 

The baseband equivalent signals are easier to represent for simulation.

o Since they are low-pass signals, they are easily sampled. 



No information is lost when using baseband equivalent signals. Standard, linear system equations hold: R(t ) = s(t ) ∗ h(t ) +n(t )

(5)

R( f ) = S ( f ) · H ( f ) + N ( f )

(6)



20

2.3. PERFORMANCE EVALUATION OF THE SYSTEM

2.3.1 Processing Gain

Fig 2.3.1 Processing Gain

In a spread spectrum system, the process gain is the ratio of the spread bandwidth to the unspread bandwidth. It is usually expressed in decibels (dB).The process gain does not reduce the effects of wideband thermal noise. It can be shown that a direct sequence spread spectrum (DSSS) system has exactly the same bit error behavior as a non-spread spectrum system with the same modulation format. Thus, on an additive white Gaussian noise (AWGN) channel without interference, a spread system requires the same transmitter power as an unspread system, all other things being equal. PG helps to measure the performance advantage of spread spectrum against narrow band waveforms.

Figure 2.3 illustrates the concept of processing gain for DS waveforms as seen at the receiver end. The unspread signal is the narrowband PSK signal before applying the widebandmodulation. The spread signal is with the addition of the wideband modulation utilizing the PN code. It is apparent that the spread signal is wider in frequency BW but with lower powerspectral density per Hz.



21

The spread signal is actually shown to be close to the noise floor.PG for a DS system can be visualized as the jamming margin that exists as the difference between the unspread and spread waveforms. The primary benefit of processing gain is its contribution towards interference resistance. The PN code spreads the transmitted signal in bandwidth and it makes it less susceptible to narrowband interference within the spread BW. The receiver of a DS system can be viewed as unspreading the intended signal and at the same time spreading the interfering waveform.

The processing gain is equal to the ratio of the chipping frequency to the data frequency:

 

(7)

There are two major benefits from high processing gain:



Interference rejection: the ability of the system to reject interference is directly proportional to PG.



System capacity: the capacity of the system is directly proportional to PG.

2.3.2. Antijamming Characteristics

Fig 2.3.2 Antijamming Characteristics Department of Electronics and Communication, LMCST


22

One of the most important application of spread spectrum techniques is that of resistance to intentional interference or jamming.

    – 

(8)

A predictor jammer observes the SS signal and via computational capabilities breads the PN-code. It uses this knowledge of the code to predict the PN-code choice made by the SS system and allocates its resources to jam that choice .The predictor jammer’s ability to break the PN-code is a function of the code type and not a function of the SS technique used. A follower jammer observes the PN-code choice made by the SS system and allocates its resources to jam that choice . To be effective the follower jammer must determine the PN-code choice, generate the appropriate jamming signal, and deliver that jamming signal to the receiver prior to the receiver switching to the next PN-code choice. The goal of a jammer is to disturb the communication of his adversary.

The goals of the communicator are to develop a jam-resistant communication system under the following assumptions.



Complete invulnerability is not possible



Complete invulnerability is not possible bands, timing, traffic etc.



The jammer has no a priori knowledge of the PN spreading code

Protection against jamming waveforms is provided by purposely making the information-bearing signal occupy a bandwidth far in excess of the minimum bandwidth necessary to transmit it. This has the effect of making the transmitted signal assume a noiselike appearance so as to blend into background.



23

2.3.3. SNR vs Eb/N0

Signal-to-Noise (SNR) is probably the most common and well understood performance measure characteristic of a digital communication system. Most often this is measured at the output of the receiver and is thus directly related to the data detection process itself.

Signal-to-noise ratio is a term for the power ratio between a signal (meaning ful information) and the background noise:

       

(9)

where Ps is average signal power and Pn is average noise power, and A is root mean square (RMS) amplitude for signal and noise (for example, typically, RMS voltage).

E b/ N 0 (the energy per bit to noise power spectral density ratio) is an important parameter in digital communication or data transmission. It is a normalized signal-to-noise ratio (SNR) measure, also known as the "SNR per bit".

  where, E b



→ Energy

→ Power

per bit

Spectral Density


(10)


24

2.3.4. Bit Error Rate

The bit error rate or bit error ratio (BER) is the number of bit errors divided by the total number of transferred bits during a studied time interval. BER is a unit less performance measure, often expressed as a percentage. The bit error probability pe is the expectation value of the BER. The BER can be considered as an approximate estimate of the bit error probability. This estimate is accurate for a long time interval and a high number of bit errors . Bit error Rate, sometimes bit error ratio (BER) is the most fundamental measure of system performance. That is, it is a measure of how well bits are transferred end-to-end. While this performance is affected by factors such as signal-to-noise and distortion, ultimately it is the ability to receive information error-free that defines the quality of the link .Bit error ratio (BER) is the number of bits received in error, divided by the total number of bits received. It is the percentage of bits that have errors relative to the total number of bits received in a transmission, usually expressed as ten to a negative power. For example, a transmission might have a BER of 10-5, meaning that on average, 1 out of every of 100,000 bits transmitted exhibits an error. The BER is an indication of how often a packet or other data unit has to be retransmitted because of an error. If the BER is higher than typically expected for the system, it may indicate that a slower data rate would actually improve overall transmission time for a given amount of transmitted data since the BER might be reduced, lowering the number of packets that had to be resent.

The BER can be considered as an approximate estimate of the bit error probability. This estimate is accurate for a long time interval and a high number of bit errors.



25

In a noisy channel, the BER is expressed as a function of the normalized carrier-tonoise ratio measure denoted E b/N0, (energy per bit to noise power spectral density ratio), or Es/N0 (energy per modulation symbol to noise spectral density).

For example, in the case of BPSK modulation and AWGN channel, the BER as function of the E b/N0 is given by:

   

(11)

2.3.5 ERFC

It is the Complementary error function, defined as

  √  ∫  

(12)

2.3.6. Q function

Formally, the Q-function is defined as

      √  ∫    In statistics,

the Q-function is

the tail

probability of

(13)

the standard

normal

distribution. In other words, Q( x) is the probability that a normal (Gaussian) random variable will obtain a value larger than x standard deviations above the mean.



26

Other definitions of the Q-function, all of which are simple transformations of the normal cumulative distribution function, are also used occasionally. Because of its relation to the cumulative distribution function of the normal distribution; the Q-function can also be expressed in terms of the error function, which is an important function in applied mathematics and physics. The Q-function can be expressed in terms of the error function, or the complementary error function, as

      √ 

(14)

The error function is closely related to the Q-function, which is the tail probability of the standard normal distribution. The Q-function can be expressed in terms of the error function as

   ∗√ 

(15)

2.3.7. Eb/N0 vs. BER for a basic BPSK system in AWGN Channel

Consider a BPSK system in AWGN channel with energy per bit E b and noise power spectral density N0/ 2. Here let us assume E b=1 unit.

       Let us take

 

We know the bit error rate for BPSK in AWGN is given by


(16)


√ 

27

(17)

where Q( ) denotes the Q function

Probability of Error is given by ,

          

(18)

Since Eb=1 we have

     (√  )

(19) (20)

2.3.8. Eb/N0 vs. BER for a DSSS system in AWGN Channel

The bit error rate of a DSSS system for Eb=1 in AWGN channel is given by

 ( ∗  )


(21)


28

2.4. HIGH LEVEL DESIGN

Fig 2.4.1 High Level Design of DSSS

2.4.1 Transmitter

The data that we are applying will be in binary form. The information rate is R bps, and the bit interval is T b==1/R seconds. For this purpose binary data generator is provided. In modulator section the date that is generated is BPSK modulated. Binary Phase Shift Keying (BPSK) is a type of phase modulation using 2 distinct carrier phases to signal ones and zeros. BPSK is the simplest form of PSK. It uses two phases which are separated by 180° and so can also be termed 2-PSK.



29

It does not particularly matter exactly where the constellation points are positioned, and, in this figure, they are shown on the real axis, at 0° and 180°. This modulation is the most robust of all the PSKs since it takes serious distortion to make the demodulator reach an incorrect decision. It is, however, only able to modulate at 1bit/symbol. Each modulated BPSK is spread into N chips by a DS spreader according to random data pattern generally PN sequence generator. The PN sequence has much higher data rate than information sequence. The information sequence is logically modulo 2 added with the PN sequence. The bandwidth of any digital system is inversely proportional to duration of transmitted pulse. Because the transmitted DSSS chips are N times narrower than information data bits, the bandwidth of DSSS signal is N times larger than signal without spreading.

2.4.2 Channel

In the channel section a White Gaussian noise and a high power, high frequency sinusoidal jamming signal are added to the signal. Additive White Gaussian Noise (AWGN) is the statistically random radio noise characterized by a wide frequency range with regards to a signal in a communications channel. The basic idea behind combatting jamming channels is to increase the dimensionality of the signal. By increasing the dimensionality of the signal in jamming environments, we force the jammer to transmit power in each of the dimensions. The signal can then randomly choose a limited number of the dimensions in which to transmit.



30

2.4.3 Receiver

The DSSS transmitter uses a locally generated PN code generator and de spreader also called as receiver correlator to separate the desired coded information from all possible signals. A DSSS is a special matched filter hat responds to signal that are encoded with a PN code that matches its own PN code.

This correlator does not respond to manmade or natural noise and interference. The peak of autocorrelation function is used to detect the transmitted bit. Autocorrelation refers to correlating a bit pulse with itself. This involves multiplying the bit pulse with a delayed version of itself and integrating the produ ct over the pulse duration.

The DS despread signal is then demodulated with BPSK demodulator. Then the signal is detected and it is compared with that of the binary data and with the help of error counter error is noted.

2.4.4. PN Synchronization

In a spread spectrum system, the generated PN code at the receiver end must be aligned to the received PN sequence, otherwise, the PN code misalignment will result in ineffective de-spreading of the signal. Synchronization is usually accomplished first by an acquisition of the initial PN code alignment and then followed by a tracking process to eliminate a possible new phase shift introduced to the received signal during the signal reception process. Without synchronization, the spread spectrum will appear as noise and ineffective de-spreading will be achieved at the receiver end. Therefore, synchronization of the PN code is crucial for data reception .Interference is added to the spread spectrum signal during transmission through the channel. The characteristics of the interference depend to a large extent on its origin. Usually the interference is categorized as being either broadband or narrowband relative to the bandwidth of the information bearing signal, and either continuous in time or pulsed in time.



3. 

31

APPLICATIONS

Used by European Galileo satellite navigation systems and The United States GPS systems



DS-CDMA (Direct-Sequence Code Division Multiple Access) is a multiple access scheme based on Direct-sequence spread spectrum, by spreading the signals from/to different users with different codes. It is the most widely used type of CDMA.



Used in Cordless phones operating in the 900 MHz, 2.4 GHz and 5.8 GHz bands



Used in IEEE 802.11b 2.4 GHz Wi-Fi, and its predecessor 802.11-1999 used in automatic meter reading.



Used in IEEE 802.15.4 (PHY and MAC layer for ZigBee)



Used in Satellite navigation



Used in Radio-controlled model vehicles



Miltary application such as antijam communication and low probability of intercept(lpi)



Low probability of detection underwater acoustic commun ications



32

4.



BENEFITS

Avoiding interception

In military communications, interception of hostile communications is commonly used

for

various

operations

such

as

identification,

jamming,

surveillance

or

reconnaissance. The successful interceptor usually measures the transmitted power in the allocated frequency band. Thus, spreading the transmitted power over a wider band undoubtedly lowers the power spectral density, and thus hides the transmitted information within the background noise. The intended receiver recovers the information with the help of system processing gain generated in the spread process. However, the unintended receiver does not get the advantage of the processing gain and consequently will not be able to recover the information. Because of its low power level, the spread spectrum transmitted signal is said to be a low probability of interception (LPI) signal.



Privacy of transmission

The transmitted information over the spread-spectrum system cannot be recovered without knowledge of the spreading code sequence. Thus, the privacy of individual user communications is protected in the presence of other users. Furthermore, the fact that spreading is independent of the modulation process gives the system some flexibility in choosing from a variety of modulation schemes.





33

Resistance to fading

In a multipath propagation environment, the receiver acquires frequent copies of the transmitted signal. These signal components often interfere with each other causing what is commonly described as signal fading. The resistance of the spread-spectrum signals to multipath fading is brought about by the fact that multipath components are assumed to be independent. This means that if fading attenuates one component, the other components may not be affected, so that unfaded components can be used to recover the information.



Accurate low power position finding

The distance (range) between two points can be determined by measuring the time in seconds, taken by a signal to move from one point to the other and back. This technique is exploited in the Global Positioning System (GPS). Since the signal travels at the speed 8

of light (3×10 meters/sec)

8

Range in meters = 3×10 ×

 

(22)

It is clear from the above expression that the accuracy of the transit time measurement determines the ultimate range accuracy. In practice, the transit time is determined by monitoring the correlation between transmitted and received code sequences. The transit time can be computed by multiplying the code duration by the number of code bits needed to align the two sequences. Clearly, higher resolution requires code symbols to be narrow which means high code rates. Thus, the sequences are selected to provide the required resolution so that if the code sequence has N chips, each with duration Tc seconds, then:

(23) Department of Electronics and Communication, LMCST


34

8

Maximum range = 1.5NTc × 10 meters

The range resolution requires the chip duration Tc to be small so that sequence chip rate is as high as possible. On the other hand, maximum range requires a long sequence (i.e. N is large) so that many chips are transmitted in a single sequence period.

The GPS system consists of twenty-four satellites orbiting the earth along six orbital planes, spaced 60 degrees apart with nominally four satellites in each orbit. These clusters of satellites provide any user with visibility of five to eight satellites from any point on earth. The position, in 3-D, of a moving receiver and its speed can be measured using signals received from at least four satellites. GPS provides two services. The precise positioning service uses very long code sequence at a code rate of 10.23 MHz. The standard positioning service, on the other hand, uses a shorter code (1023 bits) at a rate of 1.023 MHz. Each satellite is identified by a different phase of the short code.



Improved multiple access scheme

Multiple access schemes are designed to facilitate the efficient use of a given network resource by a group of users. Conventionally, there are two schemes in use: the Frequency Division Multiple Access (FDMA), and the Time Division Multiple Access (TDMA). In FDMA, the radio spectrum is shared between the users such that a fraction of the channel is allocated to each user at a time. On the other hand, in TDMA, each user is able to access the whole of the spectrum at a unique time slot. The spread spectrum offers a new network access scheme due to the use of unique code sequences. Users transmit and receive signals with access interference that can be controlled or even minimized.



35

5. SOFTWARE USED 5.1 MATLAB SOFTWARE

MATLAB is a high-level language and interactive environment for numerical computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built in math functions enable you to explore multiple approaches and reach a solution than with spreadsheets or traditional programming languages, such as C/C++ or Java. You can use MATLAB for a range of applications, including signal processing and communications, image and video processing, control systems, test and measurement, computational finance, and computational biology. More than a million engineers and scientists in industry and academia use MATLAB, the language of technical computing. It was written originally to provide easy access to matrix software developed by LINPACK (linear system package) and EISPACK (Eigen system package) projects. MATLAB is therefore built on a foundation of sophisticated matrix software in which the basic element is matrix that does not require pre dimensioning MATLAB includes a variety of tools for efficient algorithm development, including: 

Command Window – Lets you interactively enter data, execute commands and programs, and display results.



MATLAB Editor – Provides editing and debugging features, such as setting breakpoints and stepping through individual lines of code.



Code Analyzer – Automatically checks code for problems and recommends modifications to maximize performance and maintainability.



MATLAB Profiler – Measures performance of MATLAB programs and identifies areas of code to modify for improvement.



5.2

36

TYPICAL USE OF MATLAB

1. Math and computation 2. Algorithm development 3. Data acquisition 4. Data analysis, exploration and visualization 5. Scientific and engineering graphics

5.3

THE MAIN FEATURES OF MATLAB



High-level language for numerical computation, visualization, and application development.



Interactive environment for iterative exploration, design, and problem solving.



Mathematical functions for linear algebra, statistics, Fourier analysis, filtering, optimization, numerical integration, and solving ordinary differential equations.



Built-in graphics for visualizing data and tools for creating custom plots.



Development tools for improving code quality and maintainability and maximizing performance.



Tools for building applications with custom graphical interfaces.



Functions for integrating MATLAB based algorithms with external applications and languages such as C, Java, .NET, and Microsoft Excel.



Two-and three dimensional graphics for plotting and displaying data



A complete online help system



Powerful, matrix or vector oriented high level programming language for individual applications.



Toolboxes available for solving advanced problems in several application areas



5.4

37

THE MATLAB SYSTEM

The MATLAB system consists of five main parts:

5.4.1

Development Environment

This is the set of tools and facilities that help you use MATLAB functions and files. Many of these tools are graphical user interfaces. It includes the MATLAB desktop and Command Window, a command history, an editor and debugger, and browsers for viewing help, the workspace, files, and the search path.

5.4.2

The MATLAB Mathematical Function Library

This is a vast collection of computational algorithms ranging from elementary functions, like sum, sine, cosine, and complex arithmetic, to more sophisticated functions like matrix inverse, matrix Eigen values, Bessel functions, and fast Fourier transforms.

5.4.3

The MATLAB Language

This is a high-level matrix/array language with control flow statements, functions, data structures, input/output, and object-oriented programming features. It allows both "programming in the small" to rapidly create quick and dirty throw-away programs, and "programming in the large" to create large and complex application programs.



5.4.4

38

Graphics

MATLAB has extensive facilities for displaying vectors and matrices as graphs, as well as annotating and printing these graphs. It includes high-level functions for twodimensional and three-dimensional data visualization, image processing, animation, and presentation graphics. It also includes low-level functions that allow you to fully customize the appearance of graphics as well as to build complete graphical user interfaces on your MATLAB applications.

5.4.5

The MATLAB Application Program Interface (API)

This is a library that allows you to write C and FORTRAN programs that interact with MATLAB. It includes facilities for calling routines from MATLAB (dynamic linking), calling MATLAB as a computational engine, and for reading and writing MATfiles.



6.

39

SIMULATION IN MATLAB

6.1 PARAMETERS FOR THE SYSTEM SIMULATION

System Specifications: 

BPSK modulation, b Є {1,−1} with equal probabilities



Square Pulses



integrate-and-dump receiver front-end



correlation receiver



Symbol period, T=1sec



Normalized received symbol energy, Es=1



Number of symbol=10

5



AWGN with zero mean and power spectral density



PN sequence of length 7 and 31



Performance Measure: 

Bit-error rate as a function of E b/N0 for DSSS system



BER vs. E b/N0 of DSSS system as a function of sinusoidal jamming interference amplitude.



40

6.2 SIMULATION RESULTS

Fig 6.2.1 Comparison between theoretical DSSS system and simulated baseband DSSS system for PN of length 7

Fig 6.2.2 Comparison between theoretical DSSS system and simulated baseband DSSS system for PN of length 31 Department of Electronics and Communication, LMCST


41

Fig 6.2.3 Performance comparison between an ideal BPSK system and DSSS system in presence of sinusoidal jamming interference

Fig 6.2.4 Plot for different values of jamming amplitude with PN length 7



Fig 6.2.5 Plot for different values of jamming amplitude with PN length 31

Fig 6.2.6 Performance plot of DSSS for different lengths of PN sequence


42


43

7. OBSERVATIONS

The theoretical probability of error vs. E b/N0 (given in section 2.4.8) curve of a DSSS system is plotted. This is done by using qfunc( )in MATLAB. This curve is compared with the plot of probability of error vs. E b/N0 of the baseband DSSS system we simulated. The fig 6.1 represents this comparison. From the figure it is clear that the simulated output is perfectly matching with the theoretical values.

We can also observe that the performance of DSSS BPSK is more reliable than a basic BPSK modulated system. For E b/N0 = -5 dB it is seen that the probability of error for -2

-1

DSSS system is only 2×10 while for basic BPSK it is 2×10 .

Next objective was to evaluate the performance of the system when sinusoidal jamming signal is added. In baseband system it is done by adding the amplitude of the jamming sinusoid to the transmitted system. When sinusoidal jamming signal is added to BPSK modulated system, the data cannot be retrieved reliably. This is evident from fig 6.3. since for a particular value of E b/N0 the probability of error is very low for DSSS BPSK when compared to BPSK. For Example, for E b/N0=0 dB, the probability of error for -4

-1

DSSS system is 10 and that of BPSK is 2×10 .

The probability of error vs. E b/N0 curve is plotted for different values of jamming signal power. As the jamming power increases the probability of error also increases. Hence as the amplitude of this interference increases, the curve is shifted upwards. For example in fig 6.5 it is observed that if jamming power is doubled for E b/N0= 0 dB, BER -4

-4

is increased from 10 to 4×10 .



44

An important parameter that affects the probability of error to a great extend is the spreading factor, ie, the length of PN sequence. As the length of PN sequence increases we can see that the probability of error decreases. Figure 6.6 shows the DSSS system for a PN sequence of different lengths. From the figure it is seen that there has been an -1

-4

improvement of probability of error from 10 to 2×10 for say E b/N0 = 0 dB. This result corroborates the fact that, when PN sequence of higher length is multiplied with the data sequence, the data is transmitted like a high frequency noise and thus resists jamming interference and noise.



8.

45

CONCLUSIONS

In this project we have done the baseband simulation for complete DSSS system and the performance characteristics (E b/No vs. probability of error) is plotted. It is found that this baseband simulation of DSSS system result is matching with the theoretical equation for a PN sequence based BPSK system. Further we have added sinusoidal jamming interference to the above system and obtained the performance comparison results of a basic BPSK system and a DSSS system. We found that the DSSS system is relatively insusceptible to sinusoidal jamming interference than BPSK system. We had also carried out the above simulation with PN sequence of different length.



46

REFERENCE

[1]

Dixon, Robert C. Spread Spectrum Systems. John Wiley and Sons, 1984

[2]

Barnes, G.R. "Spread Spectrum Wireless Links," Fourth European Conference on RadioRelay Systems, 39-44 (October 1993).

[3]

Sklar, Bernard. Digital Communications Fundamentals and Applications. Prentice Hall.

[4]

R. A. Scholtz M. K. Simon, J. K. Omura and B. K. Levitt, Spread Spectrum Communications Handbook, NY: McGraw-Hill, 1994

[5]

Sung-Ming Wu,Guu Chang Yang,Cheng Yan Chang, “A Two-Level FH-CDMA Scheme for Wireless Communication Systems over Fading Channels,” IEEE Trans. On Commun., Vol. 59, No. 1, pp.38-44, January 2011.

[6]

Sen,I Matolak,W.G” Reduced-complexity bandwidth efficient multitone direct sequence spread spectrum” Vol. 59, No. 1, pp.131-134, April 2004.

[7]

Lu

RuiMin Ye

GanHua ; Ma

JinLing ; Li

YongChao ; Huang

Wei ”

A

Numerical Comparison Between FHSS and DSSS in Satellite Communication Systems with On Board Processing”, pp.1-4, October 2009 [8]

Y. Zhang, M. G. Amin, and A. R. Lindsey, “Anti-jamming GPS receivers based on bilinear signal distributions,” in Proc. IEEE Military Commun. Conf., Vienna, VA, Oct. 2001.



47

APPENDIX

close all; clear all; datal=100000; pnl=7 A=.5 a0=1 a1=0 a2=1 for i=1:pnl y=a2 d=xor(a0,a2) a2=a1 a1=a0 a0=d pn(1,i)=y end % pn=2*[ 1 0 1 0 0 1 1]-1 neg=-pn

% PN sequence generation

% negative of PN sequence

d=randint(datal,1,2);

% data generation

for i1=1:datal if d(i1)==0 trn(i1,:)=[neg']; else trn(i1,:)=[pn']; end end pp = trn'; pp = pp(:); ebno=-18;

% multiplying the data with PN Sequence

for loop=1:25 % Adding Noise z=10^(ebno/10); No=1/z; noisesignal=sqrt(No/2); noise=noisesignal*randn(1,datal*pnl); y1=pp'+noise; y=y1+A; % Adding sinusoidal Jamming interference % signal(equal to Amplitude in Baseband) e1=1; for i=1:datal % Retrieving the data s=0; i1=1; for j1=e1:e1+pnl-1 % Integration & dump operation s=s+(y(j1)*pn(i1)); i1=i1+1; end


DSSS BPSK

Recommend Documents