Number of goals scored by player 1 in each match
DSP

Basic Signals

As we saw here, a signal is any measurable quantity that varies with time (or some other independent variable). Classification of continuous-time and discrete-time signals deals with the type of independent variable. If the signal amplitude is defined for every possible value of time, the signal is called a continuous-time signal. However, if the signal takes values at specific instances of time but not anywhere else, it is called a discrete-time signal. Basically, a discrete-time signal is just a sequence of numbers. Example Consider a football (soccer) player participating in a 20-match tournament. Suppose that his running speed is recorded

Continue reading
Bandwidth, power and DSP correspond to the traditional trio of raw materials, energy and knowledge
DSP / Wireless/SDR

Why Building an SDR Requires DSP Expertise

In an introduction to signals, we discussed the idea that the any activities around us, starting from subatomic particles to massive societal networks, are generating signals all the time. Since mathematics is the language of the universe and digital signals are nothing but quantized number sequences, it is fair to say that the workings of the universe can be mapped to an infinitely large set of signals. With these number sequences in hand, an electronic computer can process the signals and either extract the information about the surrounding real world phenomena or even better influence its target environment. We saw

Continue reading
The counter, register and Tx and Rx start events
Localization

There and Back Again: Time of Flight Ranging between Two Wireless Nodes

With the growth in the Internet of Things (IoT) products, the number of applications requiring an estimate of range between two wireless nodes in indoor channels is growing very quickly as well. Therefore, localization is becoming a red hot market today and will remain so in the coming years. See the big picture of localization for general solutions to this problem. One question that is perplexing is that many companies now a days are offering cm level accurate solutions using RF signals. The conventional wireless nodes usually implement synchronization techniques which can provide around $\mu s$ level accuracy and if

Continue reading
Square-root Nyquist filters for three different excess bandwidths
DSP / Wireless/SDR

How to Design Nyquist and Square-Root Nyquist Pulse Shaping Filters

The radio spectrum is a very precious resource like real estate and must be utilized judiciously. Pulse shaping filters control the spectral leakage of the transmitted signal in a wireless channel due to the strict restrictions to comply with a spectral mask. This is even more important for the upcoming 5G wireless systems which are based on a variety of wireless transmission protocols (such as mobile networks, Internet of Things (IoT) and machine to machine communications) combined in one comprehensive standard. Even for wired channels, there is always a natural bandwidth of the medium (copper wire, coaxial cable, optical fiber)

Continue reading
A discrete-time integrator implemented through a forward difference and a backward difference technique
DSP

Discrete-Time Integrators

An integrator is a very important filter that proves useful in implementation of many blocks of a communication receiver such as symbol timing synchronization and Phase-Locked Loop (PLL). It is an inverse operation to a differentiator that is also used in many signal processing applications such as FM demodulation and image processing. In continuous-time case, an integrator finds the area under the curve of a signal amplitude. A discrete-time system deals with just the signal samples and hence a discrete-time integrator serves the purpose of collecting a running sum of past samples for an input signal. Looking at an infinitesimally

Continue reading