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DSP Algorithms for RF Systems
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Figure 3: An example of a time invariant IIR filter. Note that an IIR filter can be transformed into an FIR filter by setting all feedback coefficients to zero.

Time Invariant and Time Varying Filters

September 3, 2021

Introduction The response of time invariant filters is independent of time and have filter weights which do not change over time. Time invariance (TI) is

Figure 1: A moving average filter is implemented by delaying the input signal x[n] and then scaling by 1/3 and summing all results.

Digital Signal Processing through the Lens of the FIR Filter

September 1, 2021

Digital signal processing has two components: signals and filters.

A signal is a time-series which has information (RF vocabulary) and filters are useful in applying a desired affect to a signal. These affects can be:

  • enhancing information elements of a signal,
  • attenuating or minimizing noise,
  • or some other modification.

Figure 3: Environmental noise corrupts the receive signal. The difference between the transmit signal and receive signal is the error.

Signal and Noise: The Vocabulary of RF

August 31, 2021

All DSP scenarios will include a signal and noise.

But what are they? Using a common set of clearly defined terms is important to properly understand what information is trying to be conveyed.

Richard Hamming

Richard Hamming, Acorns and the Engineering Mindset

August 31, 2021

Richard Hamming was a pioneer in the fields of electrical engineering, computer engineering and computer science. You might not know he has also had a positive and significant impact on engineering culture with his talk “You and Your Research”.

Figure 3: Filtered BPSK symbols have a distribution that has both continuous and discrete elements.

Central Limit Theorem: Fact or Fiction?

August 30, 2021

Where were you when you first heard about the Central Limit Theorem (CLT)?

If you are like me, you heard of the CLT in the classroom as a justification for the assumption of Gaussian noise in the RF environment. The CLT states that the summation of independent random variables (RV) approaches a Gaussian distribution with an increasing number of random variables.

The CLT is convenient in simplifying mathematics, but when and how should it be used? Under what circumstances is it valid?

Let’s take a brief look at how well three different random variables follow the CLT.

Welcome to Wave Walker DSP!

August 28, 2021

Thanks for coming to Wave Walker DSP! I plan to bridge the gap between academic knowledge found in the classroom with the intuition of the

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