# Demystifying the Fourier Transform

The Fourier Transform is often used in Communication and Signal Processing to find the spectral content of a time-domain signal. The most common example is that of a sinusoid in the time domain, resulting in a sharply peaked signal in the frequency domain, also known as a delta function. A rectangular pulse in the time domain has a more complicated frequency domain equivalent, a sinc function. A rectangular pulse may be thought of as a combination of many sinusoids, hence its frequency domain equivalent is not that straightforward.

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# 5G Rollout in the USA: Long Way to Go

There is a 3 way race for 5G leadership in the US between T-Mobile(+Sprint), Verizon and AT&T. There are competing claims for the number of 5G subscribers, coverage area and download speeds. But let us look where the 5G industry stands today compared to the expectations a few years back. More than 80% of US population lives in urban areas which comprise of 2% of the total land area of about 10 million squared kilometers. That is 80% of the population lives in an area of about 200,000 squared kilometers.

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# Phase Lock Loop – Explained

Phase Lock Loops (PLLs) are an important component of communication systems, where they are used for carrier phase and frequency synchronization. They are also used in test and measurement equipment such as in Signal Generators and Vector Network Analyzers (VNAs) for frequency synthesis. Although not discussed here in detail but PLLs are also quite adept at generating multiples of a base frequency e.g. if you have a reference signal at 10MHz then a PLL can be used to generate a 100MHz signal (X=10) or even a 1GHz signal (X=100). In fact, you can also divide the frequency to get low frequency signals. In the first case the feedback frequency is divided by X and in the second case the reference or input frequency is divided by X.

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# KAY’s Single Frequency Estimator

As previously discussed, finding the frequency of a complex sinusoid embedded in noise is a classical problem in Signal Processing. The problem is compounded by the fact that number of samples available is usually quite small. So far, we have discussed Zero Crossing, FFT, MUSIC and ESPRIT methods of frequency estimation. Zero Crossing method is simplest of the above four but it can detect only one sinusoid at a time. Advantage of Zero Crossing method is that it is computationally not that complex. It does not require complex matrix manipulations as some of the other methods do.

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# A Comparison of FFT, MUSIC and ESPRIT Methods of Frequency Estimation

As discussed in previous posts it is frequently required in communications and signal processing to estimate the frequency of a signal embedded in noise and interference. The problem becomes more complicated when the number of observations (samples) is quite limited. Typically, the resolution in the frequency domain is inversely proportional to the window size in the time domain. Sometimes the signal is composed of multiple sinusoids where the frequency of each needs to be estimated separately. Simple techniques such as Zero Crossing Estimator fail in such a scenario.  Even some advanced techniques such as MATLAB function “pwelch” fail to distinguish closely spaced sinusoids.

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# Frequency Estimation Using Zero Crossing Method

A sinusoidal signal is the most fundamental type of signal that exists in communication systems, power systems, navigation systems etc. It is controlled by three parameters which are the amplitude, phase and frequency. The last two, that is phase and frequency, are interconnected. As discussed in my previous post Instantaneous Frequency (IF) is nothing but the rate of change of phase. This can be mathematically described as:

IF=Δφ/Δt

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