Digital Communication Comprehensive Course

Explore attenuation of signal, including conduction and dielectric losses in wired channels, wireless propagation losses, and decibel measures such as dB and dBm for power or voltage.

Explore m-ary FSK in depth, defining the modulation order m, symbol and bit durations, and the bandwidth implications. Calculate the ith frequencies, spacing, and a practical example to illustrate MFSK.

Explore differential phase shift keying (DPSK) within digital communication, including its transmitter and receiver, waveforms, and practical advantages, disadvantages, and applications in wireless, optical, and satellite communications.

Compare binary amplitude shift keying, binary frequency shift keying, and binary phase shift keying, highlighting their modulation characteristics, bandwidth, noise immunity, detection methods, and suitable applications.

Explore how analog signals become digital through sampling, quantization, and encoding, and learn to avoid aliasing by applying Nyquist rate and pre aliasing and receiver filters.

Examine how sampling with a given fs and ideal low-pass reconstruction recovers signal components, identifying surviving frequencies and the role of x(ω) and its shifted replicas.

Explore the sampling theorem for band pass signals, derive bandwidth as omega minus omega L, and determine the minimum sampling frequency using the integer k, with practical examples.

Explore ideal sampling, also known as impulse sampling, by multiplying the original signal with an impulse train and applying the Nyquist criterion to prevent band overlap.

Compare PAM, PWM, and PPM to reveal how modulation principle affects bandwidth, synchronization, power efficiency, noise immunity, and transmitter complexity across Ethernet, DSL, motor control, and drone remote control applications.

Compute the quantization parameters for a 12‑bit adc with ±2 v range, including step size, index, and the quantized signal for 1.33 v. Highlight quantization error, dynamic range, and snr.

Learn the fundamentals of pulse code modulation (PCM), covering low pass filtering, sampling, quantization, encoding, block diagrams, standards, and the tradeoffs in bitrate, bandwidth, and digital signal advantages.

solve three pcm examples: determine minimum bits per sample for a target snr of a sinusoid, and compute codeword length, bitrate, and bandwidth for a tv signal.

Explore PCM concepts with practical examples on quantization, RMSE, and quantization SNR, using a 12-bit quantizer and a six-bit encoder to compute bandwidth and SNR.

Explore mu-law companding basics and characteristics, and see a practical example illustrating nonuniform quantisation and the input‑output relation defined by y/xmax = ln(1+mu x/xmax)/ln(1+mu).

Explore delta modulation fundamentals, including one-bit per sample encoding, transmitter and receiver architectures, and waveforms; compare with PCM and differential PCM, and discuss slope overload and granular noise.

Adaptive delta modulation uses a variable step size to reduce slope overload and granular noise, transmitting one bit per sample and supporting both transmitter and receiver.

Convert digital data into waveforms for transmission over wired, optical, or wireless channels, while ensuring synchronization and applying line coding schemes such as unipolar, polar, bipolar, multilevel, and Manchester.

Derive the power spectral density for NRZ unipolar line coding by computing the Fourier transform of the energy pulse and its autocorrelation, then apply the Wiener-khinchin relation.

Explain duo binary signaling, correlative coding, and the encoder-decoder with recorder to prevent error propagation, then analyze the transfer function and frequency response of the duo binary filter.

Explore the fundamentals of information theory, including uncertainty and the measurement of information in bits. Learn how a source transmits messages through a channel to a receiver, despite noise.

Solve an example of Shannon-Fano encoding by ordering probabilities, bisecting into equiprobable subsets, assigning bits, deriving codewords and lengths, and analyzing entropy and efficiency.

Explore Shannon-Fano encoding with ambiguity and learn how to resolve equiprobable splits while analyzing efficiency, redundancy, and entropy to derive optimal codewords.

Explore three examples of channel capacity using Shannon-Hartley, applying C = B log2(1 + SNR) and noting SNR, S/N0, and the maximum information rate with infinite bandwidth.

Master the fundamentals of probability, including definitions, properties such as mutually exclusive, and the 0 to 1 range. Examine conditional probability, Bayes rule, and notations for A and B.

Compute the mean as the expectation using discrete sums or continuous integrals, then derive variance from E[(X - μ)^2] or E[X^2] - μ^2, and define standard deviation as the square root of variance.

Compute the mean, variance, and standard deviation of the number of red balls drawn when three balls are selected from eight (three red, five blue) using probability and combinations.

Explore how Chebyshev’s inequality bounds the probability that a random variable deviates from its mean using mu, sigma, and k.

Explore three Chebyshev's inequality examples, using mean and variance to bound probabilities, convert to standard form, and apply upper and lower bounds with mu, sigma, and k.

Explore the fundamentals of block codes, channel and codeword concepts, and the four by three parity example, plus the difference between systematic and non-systematic codes.

Explore the basics of block code for parity check, including encoding with a single parity bit and xor-based parity calculation, and decoding to detect one-bit errors.

Explore the basics of Hamming code, determine minimum parity bits, position data and parity bits, and learn to generate codewords and detect and correct errors with practical examples.

Explains linear block code with two worked examples, detailing generator and parity matrices. Shows deriving codewords and converting to systematic form using information bits and xor modulo two.

Explore convolutional codes through a detailed encoder example, deriving constraint length, code dimensions, rate, states, and trellis diagrams, and see how the Viterbi algorithm detects and corrects errors.

Explore frequency hopping spread spectrum, a spread spectrum technique using pseudo random carrier frequency changes to resist jamming, with slow and fast hopping and Bluetooth and RFID applications.