The IEEE 802.11a specifications are used by many to understand a wireless communication link built using OFDM. In this post, I have put together a set of 10 multiple choice questions based on 802.11a specifications. The questions are on the building blocks in 802.11a specifications, preamble structure and so on. Upon completion of the quiz,…
In the recent past, we have discussed three receive diversity schemes – Selection combining, Equal Gain Combining and Maximal Ratio Combining. All the three approaches used the antenna array at the receiver to improve the demodulation performance, albeit with different levels of complexity. Time to move on to a transmit diversity scheme where the information…
Question 26 on Electronic Devices from GATE (Graduate Aptitude Test in Engineering) 2012 Electronics and Communication Engineering paper. Q26. The source of a silicon (), n-channel MOS transistor has an area of and a depth of . If the dopant density in the source is , the number of holes in the source region with…
This is the third post in the series discussing receiver diversity in a wireless link. Receiver diversity is a form of space diversity, where there are multiple antennas at the receiver. The presence of receiver diversity poses an interesting problem – how do we use ‘effectively‘ the information from all the antennas to demodulate the…
It might be interesting to interpret the output of the fft() function in Matlab. Consider the following simple examples. fsMHz = 20; % sampling frequency fcMHz = 1.5625; % signal frequency N = 128; % fft size % generating the time domain signal x1T = exp(j*2*pi*fcMHz*[0:N-1]/fsMHz); x1F = fft(x1T,N); % 128 pt FFT figure; plot([-N/2:N/2-1]*fsMHz/N,fftshift(abs(x1F)))…
Thanks to the nice article from Xilinx TechXclusives [XLNX-TECH], let us try to understand the probable digital implementation of resistor-capacitor based low pass filter. Consider a simple RC filter shown in the figure below. Assuming that there is no load across the capacitor, the capacitor charges and discharges through the resistor path. Figure: RC low…
Question 12 on math from GATE (Graduate Aptitude Test in Engineering) 2012 Electronics and Communication Engineering paper. Q12. With initial condition the solution of the differential equation, is (A) (B) (C) (D) Solution From the product rule used to find the derivative of product of two or more functions, Applying this to the above equation, we…
In a previous post, the variance of the in-band quantization noise for a first order sigma delta modulator was derived. Taking it one step furhter, let us find the variance of the quantization noise filtered by a second order filter. With a first order filter, the quantization noise passes through a system with transfer function…
An earlier post we discussed hard decision decoding for a Hamming (7,4) code and simulated the the bit error rate. In this post, let us focus on the soft decision decoding for the Hamming (7,4) code, and quantify the bounds in the performance gain.
Thanks to the keen observation by Mr. Phan Minh Hoang, I was notified that the Matlab/Octave scripts provided along with the topic raised cosine filtering was not behaving properly. Reason: I was not taking care of the division by zero when creating the raised cosine filter taps. 🙁
The definition of Toeplitz matrix from [1] is: A matrix is said to be Toeplitz if the elements are determined completely by the difference .
In TETRA specifications, one of the modulation technique used is Differential 8 Phase Shift Keying (D8PSK). We will discuss the bit error rate with non-coherent demodulation of D8PSK in Additive White Gaussian Noise (AWGN) channel.
Let us derive the theoretical 16QAM bit error rate (BER) with Gray coded constellation mapping in additive white Gaussian noise conditions. Further, the Matlab/Octave simulation script can be used to confirm that the simulation is in good agreement with theory.
For curve fitting using linear regression, there exists a minor variant of Batch Gradient Descent algorithm, called Stochastic Gradient Descent. In the Batch Gradient Descent, the parameter vector is updated as, . (loop over all elements of training set in one iteration) For Stochastic Gradient Descent, the vector gets updated as, at each iteration the…