Digital Communications

In this lecture, we explain the quantization process and solve illustrative examples clarifying the meaning of quantization process.

In this lecture, we inspect the quantization noise, and derive the mathematical expression of the signal-to-noise ratio for quantizer.

The digital baseband modulation system called "pulse code modulation" is explained.

Delta modulation and demodulation are explained.

In this lecture, we provide a detailed example for delta modulation.

In this lecture, we explain differential pulse code modulation

Non-return-to-zero line codes are explained.

In this lecture, we explain the RZ line codes

In this lecture, we explain phase line codes

In this lecture, we explain multi-level lines codes

In this lecture, we explain duobinary signaling and precoding.

In this lecture, we provide information about the power spectral density of line codes.

In this lecture, we show how to calculate the power spectral density of a line code.

In this lecture, we provide information for the conditional distributions for the transmitted bits at the receiver side.

We derive bit detection error probability for binary transmission in AWGN channel

We provide information about the matched filter, and its use at the receiver side.

In this lecture, we solve examples for the use of matched filter

In this lecture, we obtain probability of bit error expressions for some base-band digital modulation methods.

In this lecture, we provide information about some fundamental definitions used by vector spaces, such as norm of a vector, dot product of two vectors, Euclidean distance between two vectors, linearly independent vectors, vector space of square-integrable functions, etc.

In this lecture, we explain the Gram-Schmidt Orthogonalization Procedure, and provide a numerical example for Gram-Schmidt Orthogonalization Procedure

In this lecture, we explain vector space representation of signals, and solve examples related to the topic.

In this lecture, we explain vector space representation of white Gaussian noise. We derive the joint probability density function for the noise vector.

In this lecture, we explain the optimum receiver for digitally modulated signals in additive-white-Gaussian noise. We derive formulas and design the structure of the optimum receiver.

In this lecture, we explain how to calculate the average symbol error probability in digital communicaiton.

In this lecture, we explain binary Amplitude Shift Keying (BASK) passband digital modulation technique.

In this lecture, we explain binary Phase Shift Keying (BPSK) passband digital modulation technique.

In this lecture, we explain binary Frequency Shift Keying (BPSK) passband digital modulation technique.

In this lecture, we explain Quadrature Phase Shift Keying pass-band digital modulation and demodulation.

In this lecture, we explain the ISI problem arising in digital communication through bandlimited AWGN channel. Besides, raised cosine pulse and eye diagram are explained.

In this lecture, we explain how to choose the transmit and receive filters for digital communication through bandlimited AWGN channels.