Signal Processing for Communication Systems
Key focus: Sinc pulse shaping of transmitted bits, offers minimum bandwidth and avoids intersymbol interference. Discuss its practical considerations & simulation. Sinc pulse shaping As suggested in the earlier post, the pulse shape that avoids ISI with the least amount of bandwidth is a sinc pulse of bandwidth $latex F_{sym}/2$. Here, $latex F_{sym}=1/T_{sym}$ is the … Read more
Key focus: Model and simulate m-sequence generator using Galois linear feedback shift registers (LFSR) that implement linear recursion. Plot correlation properties. Maximum-length sequences (also called as m-sequences or pseudo random (PN) sequences) are constructed based on Galois field theory which is an extensive topic in itself. A detailed treatment on the subject of Galois field theory … Read more
In coherent detection, the receiver derives its demodulation frequency and phase references using a carrier synchronization loop. Such synchronization circuits may introduce phase ambiguity $latex \phi = \hat{\theta}-\theta $ in the detected phase, which could lead to erroneous decisions in the demodulated bits. For example, Costas loop exhibits phase ambiguity of integral multiples of $latex … Read more
Key focus: Demodulation of phase modulated signal by extracting instantaneous phase can be done using Hilbert transform. Hands-on demo in Python & Matlab. This post contains interactive python code which you can execute in the browser itself. Phase modulated signal: The concept of instantaneous amplitude/phase/frequency are fundamental to information communication and appears in many signal … Read more
Key focus: Learn how to use Hilbert transform to extract envelope, instantaneous phase and frequency from a modulated signal. Hands-on demo using Python & Matlab. If you would like to brush-up the basics on analytic signal and how it related to Hilbert transform, you may visit article: Understanding Analytic Signal and Hilbert Transform Introduction The … Read more
Key focus of this article: Understand the relationship between analytic signal, Hilbert transform and FFT. Hands-on demonstration using Python and Matlab. Introduction Fourier Transform of a real-valued signal is complex-symmetric. It implies that the content at negative frequencies are redundant with respect to the positive frequencies. In their works, Gabor [1] and Ville [2], aimed … Read more
A brief intro to modeling a frequency selective fading channel using tapped delay line (TDL) filters. Rayleigh & Rician frequency-selective fading channel models explained. Tapped delay line filters Tapped-delay line filters (FIR filters) are best to simulate multiple echoes originating from same source. Hence they can be used to model multipath scenarios. Tapped-Delay-Line (TDL) filters with … Read more
Key focus: With examples, let’s estimate and plot the probability density function of a random variable using Matlab histogram function. Generation of random variables with required probability distribution characteristic is of paramount importance in simulating a communication system. Let’s see how we can generate a simple random variable, estimate and plot the probability density function … Read more
Synopsis: Cyclic prefix in OFDM, tricks a natural channel to perform circular convolution. This simplifies equalizer design at the receiver. Hands-on demo in Matlab. Cyclic Prefix-ed OFDM A cyclic-prefixed OFDM (CP-OFDM) transceiver architecture is typically implemented using inverse discrete Fourier transform (IDFT) and discrete Fourier transform (DFT) blocks (refer Figure 13.3). In an OFDM transmitter, … Read more
In the previous post, Interpretation of frequency bins, frequency axis arrangement (fftshift/ifftshift) for complex DFT were discussed. In this post, I intend to show you how to interpret FFT results and obtain magnitude and phase information. Outline For the discussion here, lets take an arbitrary cosine function of the form \(x(t)= A cos \left(2 \pi … Read more