EE 569 is a continuation of EE 568; Digital Communications -I. The course has been designed mainly to provide a good understanding of fundamental problems and countermeasure techniques in digital communications over dispersive channels. It starts with a review of optimum receiver principles in additive white Gaussian noise channels. This includes; geometrical signal representation, optimum MAP decision rule, correlator and matched-filter receivers, bit error probability (BER) analysis. This is followed by a review of baseband pulse transmission; design and performance of L-PAM for ideal channels, baseband pulse shaping and the Nyquist criterion, transceiver filters design for noise immunity. This is followed by the theory of bandlimited channels and performance evaluation in presence of intersymbol interference (ISI); examples of dispersive channels, effect of imperfect channels on the L-PAM system, BER analysis in ISI presence for L-PAM, eye-closure criterion, several methods for BER analysis in ISI presence, e.g., Chernoff bound by Saltzberg, Gauss-Quadrature-Rules and Maximum-Entropy Moment techniques. This is followed by the optimization of baseband systems; receiver optimization, transmitter optimization, joint transmitter and receiver optimization. Then, discrete time models for channel characterization, maximum-likelihood sequence estimation (MLSE) concept and receivers, discrete-time white noise model, ISI channel discrete-time model are discussed. This is followed by how to counter the deleterious effects of intersymbol interference (ISI) by equalization; linear equalizers, zero-forcing algorithm for tap coefficients adaptation, LMS algorithm and its convergence properties, performance with infinite taps and finite number of taps, fractionally-spaced taps equalizers, nonlinear decision feedback equalizers their adaptation and performance. Then, applications of MLSE to dispersive channels are discussed, including; maximum-likelihood sequence estimation and Viterbi algorithm, error event probability performance of MLSE as applied to ISI channels. This is followed by a treatment of digital signaling over fading channels and diversity combining, including; statistical characterization of fading channels; both discrete and continuous models for fast and slow fading, effect of signal characteristics on fading model; frequency-selective and non-selective fading, binary signals over frequency-non-selective and slow-fading channels, diversity and diversity combining techniques, digital signaling over frequency-selective channels and RAKE-receivers. This is followed by a discussion of basics of spread spectrum signaling direct-sequence and frequency-hopping spread spectrum techniques, code-division-multiple-access (CDMA) - - anti-jam and multi-path fading resolution capabilities.