Spread Spectrum Techniques in Wireless Communication

May 12, 2012 at 2:32 pm Leave a comment

Spread spectrum communication techniques including in-time and frequency domains for direct sequence, frequency hopping, and time hopping are currently used in a large number of wireless applications. This article provides an overview of these techniques. Results of laboratory tests of a ZigBee network are presented, and experimental results are compared with theoretical expectations. Part 2 of this paper will present an application we developed for a wireless distributed measurement sensing and actuating system for water quality assessment.

Early Wireless Applications

Many innovative people have faced the challenge of developing long distance communications with various levels of success. One of the earliest techniques was using fire and smoke as visual signals. The first technical contribution to the field of telecommunication was made by Guglielmo Marconi (1874) who developed a practical wireless system to transmit telegraph messages. Although unsuccessful, Marconi’s system introduced telegraphy for marine signaling. A ships’ crew could be warned of potential dangers like rocky coastlines if wireless telegraphs were installed. This breakthrough led to substantial improvements in safety warning systems with performance that was independent of weather conditions such as rain, wind and smog.

Subsequently, the American Telephone & Telegraph (AT&T) company pioneered in moving the communication field forward after Alexander Graham Bell invented the telephone [1-2]. AT&T’s satellite communications enabled the first live television transmission across the Atlantic. In the early 1980s, mobile telephones were introduced, and since then the number of wireless spread spectrum applications has never stopped growing. Development in mobile telephone systems, in particular, has been driven by concurrent technological progress in high integration level component devices and interoperability of equipment from different manufacturers.

Spread Spectrum Techniques

In 1987 in the USA, the Federal Communications Commission (FCC) allocated frequency bands for communication systems that use spread spectrum techniques [3]. These bands were dedicated to industrial, scientific and medical applications (ISM) [4]. The relative success of spread spectrum techniques comes from their reliability, robustness against jamming [5] effects, low sensitivity to interferences, their security and ability to ensure privacy, and their low power consumption. One of the most important applications in terms of security and privacy is the use of spread spectrum communication in military and police services, since it is almost impossible to track a spread spectrum (SS) transmission. In these systems, the signal bandwidth is spread over a large frequency range, and it is possible to use a very low radiofrequency (RF) power level to establish successful and secure communications. A figurative comparison can be made between the compromise between frequency bandwidth and signal to noise (S/N) ratio that occurs in SS systems and the compromise between conversion bandwidth and resolution that occurs in sigma delta analog to digital converters, respectively. Stated simply, spread spectrum systems exchange radiofrequency (RF) power for bandwidth and processing gain [6].

Two other critical contributing factors to the success of spread spectrum systems are that the range of frequencies used does not require government licenses, and the power consumption of the transceivers [7] are very low. Moreover, SS techniques enable multiple users to use the same transmission channel simultaneously as long as they use different scrambling codes. Each of the three main spread spectrum techniques: direct sequence spread spectrum (DSSS), frequency hopping spread spectrum (FHSS) and time hopping spread spectrum (THSS) is outlined in the following sections.

Direct Sequence Spread Spectrum

In the DSSS technique, the scrambling process is obtained by multiplying the user data signal by a pseudo noise (PN) signal [8]. This signal is a set of code sequences that are determined but whose spectral properties are similar to a white noise spectrum. The PN codes are obtained from a shift register generator with feedback loops, and their bit rate is much higher than the user data binary signal. This procedure generates a scrambled transmission signal whose spectrum amplitude is very small. In the receiver it is possible to recover the DSSS signal as long as the same PN code is used. Figure 1 is a block diagram of a DSSS transmitter. The terms used are: Udata- user data signal, PNgen- pseudorandom noise generator, DSSS- direct sequence spread spectrum signal, Mod.- modulator, RF ampradio frequency amplifier, BPSK- binary phase shift keying, QPSK- quadrature phase shift keying, FUD- user data signal frequency, FPN- pseudo noise signal frequency . In this paper, we represent only the block diagrams for the transmitters since the block diagrams for the receivers are inverse except that the modulator is replaced by a demodulator, and the RFamp is replaced by a low noise amplifier (LNA).

A Simulink ® program (a trademark of Mathworks) was developed to compare theoretical expectations with simulated results. In a first step the input signal, x(t), is considered continuous and is defined by,

where T represents the period of the user data signal. Applying the Fourier transform (FT) operator, we can obtain the FT of the rectangular signal previously defined that is given by,

Since the FT of the product of two functions is proportional to the convolution of their FTs, as long as the Dirichlet conditions [9] are verified for both signals, the DSSS signal that results from that convolution spreads the user data signal over a large bandwidth. We can roughly say that, in the frequency domain, the high spectral amplitude and narrow bandwidth of the user data signal is converted to a DSSS signal that has very low spectral amplitude and a very large bandwidth. Signal transmission distortion is very low as long as the PN codes used by the receiver and by the transmitter are equal, the frequency of the emitter and receivers oscillators (ω0) are very stable, and transmission problems and jamming effects are negligible.

The central frequency of the DSSS signal spectrum that corresponds to the frequency value of the PN signal and the bandwidth of its main lobe, from null to null, is twice the clock rate of the modulating code. As expected, the DSSS signal has a power spectrum with the same profile as the sinc2(x) function. The DSSS spectrum profile also depends on the data modulation type that is used (BPSK or QPSK). It is important to emphasize that the periodic character of the signals nearly results in a DSSS discrete spectrum but its envelope is still modulated by a sinc2(x) function profile.

Frequency Hopping Spread Spectrum

In the FHSS technique, the scrambling process is obtained by using the frequency shift keying (FSK) principle [10]. The user data transmission uses a set of different frequencies that are changed in a pseudo random way. As long as the frequency hopping sequence is known in the receiver, it is possible to recover the user data signal without losing any information. The main parameters that are used to characterize this spread spectrum technique are: the hop set representing the number of frequencies that are used; the hop rate (HR) representing the number of frequency changes per unit of time, and the dwell time (DW) representing the time interval that the same frequency (channel) is used continuously.

Figure 2a represents the block diagram of an FHSS transmitter and Figure 2b is a temporal diagram of communication channels time slots assignments. In this case, the PN codes are used to select each frequency of a frequency set during a time interval that is much lower than the user data signal’s period. This procedure generates a scrambled transmission signal whose spectrum amplitude is very small, enabling recovery of the user data signal as long the same frequency PN code is used in the receiver. This spread spectrum technique is more robust than the DSSS against pulse jamming because it precludes an intruder from using the same frequency hopping key for channel allocation [6]. Security is directly proportional to the number of channels (n) included in the hopping set and inversely proportional to dwell time interval (DW). Both factors spread the transmitted signal over a larger bandwidth reducing the effects of external interferences caused by narrow band signals.

Time Hopping Spread Spectrum

There are two variants of THSS. In a pulse period based (THSS1) system, each pulse of the modulated user data signal is replaced by a short pulse that has a pseudo random time interval triggered by the modulated user data signal (UDRF). In a pulse width based (THSS2) system, each pulse of the modulated user data signal is replaced by another pulse (PWM) whose time duration is controlled by the pseudo random generator.

Figure 3 is a block diagram of a THSS transmitter where the selector (Sel) can choose one of the two modes previously referred. Positions (1) and (2) of that selector are associated THSS1 and THSS2 variants, respectively. The power spectrum for THSS1 and THSS2 signals have lower intensity and do not contain harmonic behavior, so their spectra characteristics are similar to the spectrum of the desired noise. The figure uses the following terms: Udata- user data signal, UDRF- modulated user data signal, PNgen- pseudorandom noise generator, THSS- time hopping spread spectrum signal, Mod.- modulator, RFampradiofrequency amplifier, BPSK- binary phase shift keying, QPSK- quadrature phase shift keying, FPN- pseudo noise signal frequency, FUD- user data signal frequency, ETD- edge trigger detector, Sel- digital selector.

Laboratory Tests of the ZigBee System

This section presents the results of some measurements that were performed to compare data with the theoretical expectations and simulation results previously obtained. The measurement system that was used to collect signals contains a spectrum analyzer (SA) and the ZigBee [11] network. The distance between the SA and the ZigBee controller was equal to 10 m. The spectrum analyzer had a measurement frequency range between 10 MHz and 18 GHz, a resolution range between 100 Hz and 1 MHz, four different detection modes, namely, sample, max/ min peak, auto peak and RMS, a power dynamic range of 90 dBc (200 pW – 200 mW) and a reference power level from -80 dBm to +20 dBm [12]. These characteristics fulfilled all the requirements for an accurate measurement of the radiated ZigBee’s SS signal.

Before measurements were recorded, the Zigbee development kit was disabled to measure the environmental noise amplitude and to compare it with the spectrum baseline obtained when the Zigbee network is operable. This measurement is important especially with direct sequence spread spectrum (DSSS), since the power density of the scrambled data of the signal is very low and sometimes even lower than spectral noise power level. Figure 4 represents the experimental results that were obtained with the following configuration of SA equipment: resolution bandwidth equal to 300 kHz, pseudo random rate (PNR ) equal 2.5 MHz, a noise spectral density, measured when the ZigBee network is switched off, equal to –107 dBm/Hz and a measurement scan equal to 10MHz centered in the frequency equal to 2.440 GHz. From the experimental results it is possible to confirm the SS technique used by ZigBee (DSSS), identify the spectral noise power level with the ZigBee kit switched on and off (-107 dBm/Hz in both cases), verifiy the spectral requirements of the ZigBee protocol in terms of frequency values and bandwidth, and confirm the ZigBee channel used for communication. The central frequency that was obtained (2.440 GHz) is equal to the central frequency of channel 18 that is the default selection of the ZigBee kit.

There are drawbacks associated with all SS techniques since they require complex circuitry, have high development costs, have a low coverage range and are sensitive to signal loss caused by multipath distortion and fading effects, among others. Distortion and attenuation are especially problematic when the transmission path is over conductive surfaces (water) with variable levels caused by tides and wave levels.

Conclusion

In every spread-spectrum technique, the goal is to deliberately spread the transmitted electromagnetic energy in the frequency domain and receive the user data signal using the same pseudo random code used in the transmitter. Critical advantages of DSSS systems are related to their ability to provide secure communication and be robust against continuous time narrow band jamming with low spectral density power. Advantages of FHSS systems are related to their robustness against pulse jamming, and this robustness increases for higher values of frequencies contained in a hopping set and for a higher hopping rate. THSS is not a reliable technique for wireless SS systems since it is adversely affected by noise and may be easily jammed. There are some SS hybrid solutions that combine the best characteristic of DSSS and FHSS transmission systems.

Part 2 of this topic will review some transmission issues and their impact in spread spectrum communication systems. A few techniques that can be mitigate free space propaganda problems, namely fading, will be addressed. The last part will include some experimental results of a wireless transmission system for water quality assessment.

References

[1] I. Dorros, “History of Telecommunications”, IEEE Communications Magazine, vol.47, no.6, pp. 14-20, June 2009.

[2] “Milestones in AT&T History”, AT&T, [Online] Available:http:www.corp.att.com/history/milestones.html. (Accessed August 2009).

[3] “Connecting the Globe: VII. Spectrum Allocation, Assignment and Enforcement”, Federal Communications Commission, [Online] Available: http://www.fcc.gov/connectglobe/sec7.html. (Accessed August 2009).

[4] G. L. Stüber, “Principles of mobile communication,” Boston: Kluwer Academic, 1996.

[5] M. Li , I. Koutsopoulos, and R. Poovendran, “Optimal Jamming Attack and Network Defense Policies in Wireless Sensor Networks”, INFOCOM 2007, May 2007.

[6] S. Farahani, “ZigBee Wireless Netwoks and Transceivers”, Newnes, Elsevier, Amsterdam, 2008.

[7] F.H. Hsiao, J. Guo, S Lo, and T.Hsu, “A DSSS receiver for dualmode DSSS/OFDM wireless LAN systems”, Dept. of Computer Sci. & Inf. Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan, 2008.

[8] W.A Chren, Jr., “PN code generator with low delay-power product for spread-spectrum communication systems”, Circuits and Systems II: Analog and Digital Signal Processing, IEEE
Transactions on Signal Processing, Vol. 46, Issue 12, pp.1506 – 1511, Dec. 1999.

[9] R. Cristi, “Modern Digital Signal Processing”, Thomson, Brooks/ Cole, 2004.

[10]C.S. Vaucher, “Architectures for RF frequency Synthesizers”, Kluwer Academic Publishers, 2002.

[11]MRF24J40MA Data Sheet 2.4 GHz IEEE Std. 802.15.4™, RF Transceiver Module, Microchip Technology Inc., 2008, [Online] Available: http://www.microchip.com/, (Accessed August 2009).

[12]”Spectrum Analyzers FSH”, Rhode & Schwarz, [Online] Available: http://www.testequip.com, (accessed August 2009).

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