EE521 Analog and Digital Communications Today some topics will be presented on the whiteboard. The slides will be updated on the web site in a few days. EE521 Analog and Digital Communications James K. Beard, Ph. D. jkbeard@temple.edu Tuesday, February 15, 2005 http://astro.temple.edu/~jkbeard/ February 15, 2005 Week 5

Attendance 12/4/2018 Week 1

Essentials Text: Bernard Sklar, Digital Communications, Second Edition SystemView Student version included with text Trial version has 90-day timeout Office E&A 709 Tuesday afternoons 3:30 PM to 4:30 PM Tuesdays before class at Ft. Washington MWF 10:30 AM to 11:30 AM added 12/4/2018 Week 1

Today’s Topics SystemView Quiz Timeline Term Projects Bandpass Modulation and Demodulation Review of Bandpass Modulation and Detection Coherent and non-coherent detection Discussion (as time permits) 12/4/2018 Week 1

Quiz timeline Quiz today Follow-up quiz Grade on first quiz Open book Caclulator No notes Follow-up quiz Take-home Will require SystemView to complete Will be deployed on Blackboard this week Grade on first quiz Split with take-home depends on grades to today’s quiz Take-home can be up to 25% of quiz grade 12/4/2018 Week 1

Term Projects Interpret, plan, model Use SystemView Assignments will be deployed on Blackboard this week Your preferences and comments are encouraged Office hours Email 12/4/2018 Week 1

Bandpass Modulation and Demodulation Review: Topics from Text Chapter 4 4.1, Why Modulate? 4.2, Digital Bandpass Modulation Techniques 4.3, Detection of Signals in Gaussian Noise 12/4/2018 Week 1

Sklar Chapter 4 Legend: From other sources Essential Information Message symbols Optional Channel symbols X M I T Format Source encode Encrypt Channel encode Multi-plex Pulse modulate Bandpass modulate Fre-quency spread Multiple access Digital input Channel impulse response Bit stream Synch-ronization Digital baseband waveform Digital bandpass waveform Channel Digital output R C V Format Source decode Decrypt Channel decode Demul-tiplex Detect Demod-ulate & Sample Freq-uency despread Multiple access To other destinations Channel symbols Information sink Message symbols 12/4/2018 Week 1

Modulation Input for this stage is baseband encoded Output is IF Pulse modulation Bandpass or pulse shaping filtering Output is IF Ready to upconvert to RF and transmit Optional frequency spread may be added Optional multiple access may be added 12/4/2018 Week 1

Functions of Modulation Prepare for wireless transmission Modulate on carrier at RF in band allocated for wireless communication Formulate digital bandpass waveform Optional successive steps Spread-spectrum (Chapter 12, next semester) Multiple access (Chapter 11, next semester) 12/4/2018 Week 1

Digital Bandpass Modulation Transition From Baseband signaling To bandpass signaling Operations Coherent Special attention to tracking phase Phase used in demodulation Non-coherent 12/4/2018 Week 1

Baseband Signaling See Figure 4.1 page 170 PCM waveforms Non-return-to-zero Return to zero Phase encoded Multilevel binary M-ary pulse modulation PAM PPM PDM 12/4/2018 Week 1

Bandpass Signaling See Figure 4.1 page 170 Carrier strategies Coherent Non-coherent Modulation types Phase sift keying (PSK) Frequency shift keying (FSK) Amplitude shift keying (ASK) Continuous phase modulation (CPM) Hybrids 12/4/2018 Week 1

Phasor Representation of Tones Modulated on a Carrier Everything referenced to Carrier frequency Particular phase of carrier Physical meaning can be inferred Quadrature demodulation of tone L.O. is the reference carrier and phase Complex result is the phasor 12/4/2018 Week 1

Features of Phasor Concept Modulation is simple to represent Phase modulation changes direction of phasor Amplitude modulation changes length of phasor Modulation can be posed in terms of phases of the modulation sidebands Characterization of noise as 2-D Gaussian distribution 12/4/2018 Week 1

Detection in Gaussian Noise Characterization of Gaussian noise 2-D distribution in phasor plot Zero mean, sigma proportional to noise amplitude Phasor concept allows vector addition to represent signal plus noise Coherent detection Selection of portions of phasor space Design is reduced to definition of boundaries in phasor space 12/4/2018 Week 1

Detection Operation One-dimensional case from Figure 3.1 page 108 Two steps Downconvert and sample Quadrature demodulator, or Digital product dectector Equalize channel and filtering effects Decision thresholds The decision threshold input is the predection point Location of received Eb/N0 12/4/2018 Week 1

Design of Detection Design of matched filter This is the channel and filter equalization of Step 1 Maximizes received Eb/N0 Design of detection regions Examples given in book are conceptual Likelihood ratio defines decision region boundaries 12/4/2018 Week 1

Bandpass Modulation and Detection Topics from text Chapter 4 Coherent detection Non-coherent detection Complex envelope Error performance M-ary signalling and performance Symbol error performance for M-ary systems 12/4/2018 Week 1

Why We’re Doing This The Channel Coding Theory We want to get there The channel capacity is When messaging bit rate is below the channel capacity, a coding scheme exists that will achieve an arbitrarily low BER in that channel We want to get there We will get quite close 12/4/2018 Week 1

Nearest Neighbor Decision Weighted distance in vector space Squared distance d between vectors i and j is given by quadratic form The smallest distance “wins” the decision Decision is i == j Statistic can be chi-square if W is inverse of covariance matrix of noise in the two vectors 12/4/2018 Week 1

Coherent Detection Base block diagram Phase is known Figure 4.7 page 180 Correlate signal with each of M possible returns Threshold, or select the largest Phase is known PLL on synch pulse or bit Complex convolution or DPD part of PLL 12/4/2018 Week 1

MPSK Signals and Phasors Correlate with multiple phases Provide regions in phasor space for detection decisions See Figure 4.11 page 189 for example Demodulate to estimate of phase See Figure 4.12 page 190 for example These are equivalent 12/4/2018 Week 1

Coherent Detection of FSK Use a filter bank Simultaneously correlate with several cosines Each represents a frequency in the FSK palette Phase is same as that of the signal Decision boundary Nearest neighbor 12/4/2018 Week 1

Non-Coherent PSK Detection Defining characteristic is that no phase reference for signal is required or available Differential PSK Phase differences are detected Two pulses are detected and their phases subtracted No requirement for tracking phase of signal 12/4/2018 Week 1

Non-coherent FSK Correlation without phase is simply a frequency-selective filters Decision vector built from frequency filters The decision vector elements are a series of powers or amplitudes What is the equivalence to nearest-neighbor detection? 12/4/2018 Week 1

Text and Assignment Text Assignment: From Text Benard Sklar, Digital Communicatinons ISBN 0-13-084788-7 SystemView User's Manual, Elanix, Inc Assignment: From Text Look at Example 4.2 page 193 and be prepared to discuss Chapter 6, 6.1, 6.2, 6.3 Homework problem 6.1; look at and be prepared to discuss Browse appendices of text for review and supplementary material Look at TUARC K3TU, E&A 918; ask Dr. Silage for access Websites http://www.temple.edu/ece/tuarc.htm http://www.temple.edu/k3tu 12/4/2018 Week 1

Practice Quiz Problems from book homework Quiz will be similar Problem 1.1 page 51 Problem 2.2 page 101 Problem 3.1 page 162 Quiz will be similar From homework problems Modifications to problem statement and parameters 12/4/2018 Week 1