Telecommunication Systems

Radio Frequency (RF) and Microwave Spectral Analysis

The display of electromagnetic radiation as a function of wavelength is termed to as electromagnetic spectrum. Based upon the wavelengths, the spectrum is divided into various frequency bands as illustrated in the figure below:

Electromagnetic spectrum

With the rapid advancement of wireless technology and satellite sensor technology, there is need for more and more accurate field measurements to complement overhead data in providing higher spectral resolution over progressively broader wavelengths. In performing spectral analysis, the following factors are considered:

  • Power in band
  • Occupied bandwidth
  • Adjacent channel power
  • Resolution bandwidth
  • Harmonic distortion
  • Noise specification

Power in Band

It is the measurement of total power within any specified range or band. The power in band is calculated by the following equation:

Where X, is the input power spectrum from a specified band, fl is the low bound of the frequency and fh is the high bound of the frequency band. The low and high bounds of this band can be determined from the center frequency.

Occupied Bandwidth

It is the measurement of frequency band or bandwidth that contains a specified percentage of the total power of the signal. Occupied bandwidth is the inverse of power in band. For example, if the specified percentage is 99, then the occupied bandwidth is the bandwidth that contains 99% of the total power of the signal i.e. the frequency range in between vertical lines as illustrated below:

Spectrum of an RF signal

Adjacent Channel Power

It measures the way a particular channel and its two adjacent channels distribute power. The measurement is performed by calculating the total power in the surrounding upper and lower channels.

Resolution Bandwidth

This is determined by the smallest frequency that can be resolved. In Fourier-transform-based spectrum analysers, the resolution bandwidth is inversely proportional to the number of samples acquired or the length of the window function. By taking more samples in the time domain or making the acquisition time longer, while keeping the sampling rate the same, the resolution bandwidth will be lowered, meaning higher frequency resolution.

You can also read: Basics of Radio Frequency (RF) and Wireless Communication Systems

Harmonic Distortion

This is a measure of the amount of power that is contained in the harmonics of a fundamental signal. Harmonic distortion is inherent to devices and systems which possess nonlinear characteristics -the more nonlinear the device, the greater its harmonic distortion.

When a signal of a particular frequency f1 passes through a nonlinear system, the output of the system consists of f1 and its harmonics f2 and f3.

Harmonic distortion is usually expressed as either power or percentage ratio, where harmonic power distortion is PHD which is obtained from:

PHD = Pfund – Pharm (dB)

Where, PHD is the power of harmonic distortion in dBc i.e. relative to the carrier frequency, Pfund is the fundamental signal power in dB or dBm, and Pharm is the power of the harmonic of interest in dB or dBm.

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Fundamental frequency f1 with harmonics f2 and f3

To represent the distortion in the form of percentage ratio, it is converted into voltage, and calculated as follows:

Where, Vharm and Vfund are the harmonic voltage and fundamental voltage respectively.

In some applications, harmonic distortion is measured as a total percentage harmonic distortion (THD). This measurement requires the power summation of all the harmonics in the spectrum band as defined by the below equation:

Phase Noise

There are various sources of noise in RF and Microwave systems. When the carrier signal contains noise due to phase and frequency modulation of the signal then the noise is called Phase noise. The spectrum of phase noise is normally close to the carrier spectrum, and is measured in decibels relative to the carrier frequency (dBc). Noise floor is a specified noise level below which signals cannot be detected under a specified measurement conditions.

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John Mulindi

John Mulindi is an Industrial Instrumentation and Control Professional with a wide range of experience in electrical and electronics, process measurement, control systems and automation. In free time he spends time reading, taking adventure walks and watching football.

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