Signal Processing for Communication Systems
Power delay profile gives the signal power received on each multipath as a function of the propagation delays of the respective multipaths. Power delay profile (PDP) A multipath channel can be characterized in multiple ways for deterministic modeling and power delay profile (PDP) is one such measure. In a typical PDP plot, the signal power … Read more
Understand various characteristics of a wireless channel through multipath channel models. Discuss Wide Sense Stationary channel, uncorrelated scattering channel, wide sense stationary uncorrelated scattering channel models and scattering function. Introduction Wireless channel is of time-varying nature in which the parameters randomly change with respect to time. Wireless channel is very harsh when compared to AWGN … Read more
Why BLUE : We have discussed Minimum Variance Unbiased Estimator (MVUE) in one of the previous articles. Following points should be considered when applying MVUE to an estimation problem Considering all the points above, the best possible solution is to resort to finding a sub-optimal estimator. When we resort to find a sub-optimal estimator Common … Read more
Key focus: Understand step by step, the least squares estimator for parameter estimation. Hands-on example to fit a curve using least squares estimation Background: The various estimation concepts/techniques like Maximum Likelihood Estimation (MLE), Minimum Variance Unbiased Estimation (MVUE), Best Linear Unbiased Estimator (BLUE) – all falling under the umbrella of classical estimation – require assumptions/knowledge … Read more
The agenda for the subsequent series of articles is to introduce the idea of autocorrelation, AutoCorrelation Function (ACF), Partial AutoCorrelation Function (PACF) , using ACF and PACF in system identification. Introduction Given time series data (stock market data, sunspot numbers over a period of years, signal samples received over a communication channel etc.,), successive values … Read more
If a time series data is assumed to be following an Auto-Regressive (\(AR(N)\)) model of given form, the natural tendency is to estimate the model parameters \(a_1,a_2, \cdots, a_N\). Least squares method can be applied here to estimate the model parameters but the computations become cumbersome as the order \(N\) increases. Fortunately, the AR model … Read more
Key focus: “Why can’t I just use a matrix to solve ARMA?” The answer is right there in the shape of the surface—you can’t solve a “warped” landscape with a linear equation. Introduction In signal modeling, our goal is to find a set of coefficients (ak and bk) that best describe an observed signal. We … Read more
Key focus: AR, MA & ARMA models express the nature of transfer function of LTI system. Understand the basic idea behind those models & know their frequency responses. How do you describe a complex, random signal—like the sound of a human voice or the fluctuating power of a fading channel—using only a few numbers? The … Read more
Key focus: Applying Cramér-Rao Lower Bound (CRLB) for vector parameter estimation. Know about covariance matrix, Fisher information matrix & CRLB matrix. CRLB for Vector Parameter Estimation CRLB for scalar parameter estimation was discussed in previous posts. The same concept is extended to vector parameter estimation. Consider a set of deterministic parameters $latex \mathbb{\theta}=[ \theta_1, \theta_2, … Read more
Introducing The Kalman Filter – Ramsey Faragher PDF Text: click here PDF Text: click here Note: Click the playlist icon (located at the top left corner of the video frame) to watch all lectures Video Lectures: Watch, Listen and Learn !!! † Link will take you to external sites Disclaimer: All the materials posted in … Read more