Phase demodulation using Hilbert transform – application of analytic signal

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Pre-requisites

Sampling theorem – baseband sampling
How to Interpret FFT results – complex DFT, frequency bins and FFTShift
Analytic signal, Hilbert Transform and FFT
Extracting instantaneous amplitude,phase,frequency – application of Analytic signal/Hilbert transform

Phase modulated signal:

The concept of instantaneous amplitude/phase/frequency are fundamental to information communication and appears in many signal processing application. We know that a monochromatic signal of form \(x(t) = a cos(\omega t + \phi) \) cannot carry any information. To carry information, the signal need to be modulated. Different types of modulations can be performed – Amplitude modulation, Phase modulation / frequency modulation.

In amplitude modulation, the information is encoded as variations in the amplitude of a carrier signal. Demodulation of an amplitude modulated signal, involves extraction of envelope of the modulated signal. This was discussed and demonstrated here.

In phase modulation, the information is encoded as variations in the phase of the carrier signal. In its generic form, a phase modulated signal expressed as an information-bearing sinusoidal signal modulating another sinusoidal carrier signal is expressed as

$$ x(t) = A cos \left[ 2 \pi f_c t + \beta + \alpha sin \left( 2 \pi f_m t + \theta \right) \right]   \;\;\;\;\;\;\; (1)$$

where, \( m(t) = \alpha sin \left( 2 \pi f_m t + \theta \right) \) represents the information-bearing modulating signal, with the following parameters

\(\alpha\) – amplitude of the modulating sinusoidal signal
\(f_m\) – frequency of the modulating sinusoidal signal
\(\theta\) – phase offset of the modulating sinusoidal signal

The carrier signal has the following parameters

\(A\) – amplitude of the carrier
\(f_c\) – frequency of the carrier and \(f_c >> f_m\)
\(\beta\) – phase offset of the carrier

Demodulating a phase modulated signal:

The phase modulated signal shown in equation \((1)\), can be simply expressed as
$$ x(t) = A cos \left[ \phi(t)\right]    \;\;\;\;\;\;\; (2) $$
Here,  \(\phi(t)\) is the instantaneous phase  that varies according to the information signal \(m(t)\).

A phase modulated signal of form \(x(t)\) can be demodulated by forming an analytic signal by applying hilbert transform and then extracting the instantaneous phase. This method is explained here.

We note that the instantaneous phase is \( \phi(t) = 2 \pi f_c t + \beta + \alpha sin \left( 2 \pi f_m t + \theta \right)  \) is linear in time, that is proportional to \(2 \pi f_c t\). This linear offset needs to be subtracted from the instantaneous phase to obtained the information bearing modulated signal. If the carrier frequency is known at the receiver, this can be done easily. If not, the carrier frequency term \(2 \pi f_c t\) needs to be estimated using a linear fit of the unwrapped instantaneous phase. The following Matlab and Python codes demonstrates all these methods.

Matlab

Python

Results

Figure 1: Phase modulation - modulating signal and modulated (transmitted) signal
Figure 1: Phase modulation – modulating signal and modulated (transmitted) signal
Demodulated signal from the noisy received signal
Figure 2: Demodulated signal from the noisy received signal and when the carrier frequency/phase is unknown at the receiver
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  • Vitor Lopes Garcia

    Hey Mathuranathan, thank you very much for this new article! It really helped me to understand the phase demodulation using Hilbert Transform. Using practical examples and codes after the theory in a article is such a great idea! Once again, thank you very much!!

    • Thanks to you for giving the lead for this new article :) !!!