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Low Crest Factor Modulation Techniques for Orthogonal Frequency ...

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Ubiquitous Computing and Communication Journal<br />

distributed variable having a mean of zero. And<br />

thus, the absolute value will have Rayleigh<br />

distribution.<br />

The crest factor of the discrete time representation<br />

x(k) is defined as the ratio of the peak magnitude<br />

value and the square root of the average power of<br />

this signal. For the OFDM signal as we mentioned it<br />

have a zero mean and thus the square root of the<br />

average power will be equal to the standard<br />

deviation δ. Thus the crest factor can be written as:<br />

CF = max(x(k )) = max(x(k )) (2)<br />

E ( x 2 ) δ<br />

Note that, the peak to average power ratio, widely<br />

used in literature, is simply the square of the crest<br />

factor. Both quantities coincide, if expressed in<br />

logarithmic scale (dB).<br />

An OFDM system is simulated using Matlab with<br />

512 sub-carriers; We have per<strong>for</strong>med a measure of<br />

normality, i.e., wither the composite time signal<br />

approaches the normal distribution or not, as a<br />

verification of the applicability of central limit<br />

theory to OFDM, and we get the following result as<br />

shown in figure (1)<br />

It can be noticed that the real and imaginary parts of<br />

the OFDM signal completely agree with the normal<br />

distribution.<br />

a. The minimum Euclidean distance amongst<br />

phasors, which is characteristics of the noise<br />

immunity of the scheme<br />

b. The minimum phase rotation amongst<br />

constellation points, determining the phase jitter<br />

immunity<br />

c. The peak to average phasor power, which is a<br />

measure of robustness against non-linear distortion<br />

introduced by power amplifiers.<br />

Fig.(2) Block diagram of OFDM system<br />

Probability<br />

0.999<br />

0.997<br />

0.99<br />

0.98<br />

0.95<br />

0.90<br />

0.75<br />

0.50<br />

0.25<br />

0.10<br />

0.05<br />

0.02<br />

0.01<br />

0.003<br />

0.001<br />

Normal Probability Plot<br />

The Bandwidth efficiency can be increased either by<br />

increasing the Number of signal phase levels, or by<br />

increasing the Number of signal amplitude levels<br />

[6],<br />

1. Increasing the signal amplitude levels has the<br />

drawback that the signal envelope is not constant<br />

and there<strong>for</strong>e non-linear amplification may cause<br />

spreading of the signal spectrum and increase in<br />

BER.<br />

2. Increasing the Number of phase levels will<br />

highly increase the BER.<br />

-0.5 -0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4<br />

Data<br />

Fig.(1) Normal probability plot of OFDM signal<br />

3. OFDM USING DIFFERENT MODULATORS<br />

In this section we will simulate an OFDM system<br />

as shown in the block diagram in figure (2) using<br />

different modulation techniques.<br />

We have simulated an OFDM system with different<br />

modulation techniques, namely, M-ary PSK, M-ary<br />

QAM (with M=4, 8, 16 and 32) and Minimum Shift<br />

Keying (MSK).<br />

When designing a constellation diagram <strong>for</strong> a<br />

modulation technique, some considerations must be<br />

given to [5]:<br />

Fig.(3)OFDM Spectrum with different modulation<br />

We have noted that <strong>for</strong> M-PSK, as M increases no<br />

effect has been occurred to the dynamic range and<br />

the PAR remains nearly the same, while <strong>for</strong> M-<br />

QAM, as M increases the dynamic range increase<br />

and so the PAR, but both of them agree in the<br />

Volume 2 Number 5 Page 112 www.ubicc.org

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