In typical wireless system simulations, there is a need to model the phase noise profile of the local oscillator. For eg, the phase noise profile of the oscillator can be of the shape described in the post on Phase Noise Power Spectral Density to Jitter. While looking around for example Matlab code, found two references…
Mr. Raghuram contacted me and informed about Happy Schools Blog. He writes about Graduate School Admission in U.S., Job opportunities for students, University Selection based on his personal experience. He recently published few articles which might of interest to some of our readers. Here are the URL for few articles:
My friend Mr. Balaji volunteers for Vibha, a non-profit organization whose mission is to ensure that every underprivileged child attains his or her right to education, health and opportunity. Vibha, which was founded in 1991 has a volunteer network of 825 members spread across Atlanta, Austin, Bay Area, Boston, Chicago, Dallas, Houston, Jacksonville, Los Angeles,…
The post on thermal noise described the noise produced by resistor ohms over bandwidth at temperature Kelvin. In this post, let us define the noise voltage at the input and output of a resistor network and further use it to define the Noise Figure of such a network.
In a previous post, we discussed about a probable first order digital PLL for tracking constant phase offset. The assumption was that as the phase offset is small and the bits gets decoded correctly, the phase difference between the ideal and actual constellation gives the initial value of phase. However, in typical scenarios it may…
I happened to stumble on Prof. Andrew Ng’s Machine Learning classes which are available online as part of Stanford Center for Professional Development. The first lecture in the series discuss the topic of fitting parameters for a given data set using linear regression. For understanding this concept, I chose to take data from the top…
From the previous post on OFDM (here), we have understood that an OFDM waveform is made of sum of multiple sinusoidals (also called subcarriers) each modulated independently. In this post, let us try to understand the estimation of frequency offset in a typical OFDM receiver (using the short preamble specified per IEEE 802.11a specification as…
Equivalence of Moving Average and CIC filter Let me briefly share my understanding on the cascaded integrator comb (CIC) filter, thanks to the nice article. For understanding the cascaded integrator comb (CIC) filter, firstly let us understand the moving average filter, which is accumulation latest samples of an input sequence .
Question 25 on math from GATE (Graduate Aptitude Test in Engineering) 2012 Electronics and Communication Engineering paper. Q25. If , then the value of is, (a) (b) (c) (d) 1
Its been a nice week for me, wherein I guest posted an article in DSPDesignLine.com. 🙂 The article derives the theoretical symbol error rate for M-QAM modulation. The theoretical results are further supplemented by Matlab/Octave simulation scripts. Those who are familiar with derivation of symbol error rate for 16-QAM modulation will find the equations easy…
Let us try to understand the formula for Channel Capacity with an Average Power Limitation, described in Section 25 of the landmark paper A Mathematical Theory for Communication, by Mr. Claude Shannon. Further, the following writeup is based on Section 12.5.1 from Fundamentals of Communication Systems by John G. Proakis, Masoud Salehi
My friend and colleague Mr. Vineet Srivastava pointed me to a nice article on clock jitter – Clock Jitter Effects on Sampling : A tutorial – by Carlos Azeredo-Leme, IEEE Circuits and Systems Magazine, Third Quarter 2011. In this post, let us discuss the total Signal to Noise Ratio at the output of an analog to…
Given that we have discussed Binary to Gray code conversion, let us discuss the Gray to BInary conversion. Conversion from Gray code to natural Binary Let be the equivalent Gray code for an bit binary number with representing the index of the bit. 1. For , i.e, the most significant bit (MSB) of the Gray…
In the previous post on Batch Gradient Descent and Stochastic Gradient Descent, we looked at two iterative methods for finding the parameter vector which minimizes the square of the error between the predicted value and the actual output for all values in the training set. A closed form solution for finding the parameter vector is possible, and in this post…