ECE 543 Principles of Digital Communications Systems Monsoon
- Slides: 43
ECE 543: Principles of Digital Communications Systems Monsoon 2019 Prof. Anand Srivastava
Course Overview 2
Introduction - Course Objectives • The aim of this course is to provide a comprehensive coverage and in-depth treatment of theory and design of digital communications at a level required for first year graduate students - • -Emphasis is placed on system goals and the need to trade off basic system parameters such as signal-to-noise ratio, probability of error, and bandwidth (spectral) and energy efficiency 13
Course Description Introduction to Digital Communication (4 Classes) Probability and Random Process Representation of Bandpass Signals and Systems Information Theory (6 Classes) Fundamental limits on performance Introdution to Information Channels and their Models Representation of Information Channels Entropy, Source/Channel Coding Theorem Mutual Information Properties of Mutual Information and Introdution to Channel Capacity Calculation of Channel Capacity for different Information Channels Sources with memory…. Markov source of mth order Optimum Receiver Design in Additive Gaussian Noise Channels (8 Classes) Vector representation of signals, Waveform channels, Geometric representations - Bases and Signal Sets Maximum Likelihood Receivers – Matched filter; Decision regions Performance Evaluation – Probability of Symbol errors; Union Bound on probability of error
Estimation (8 Classes) Maximum Likelihood (ML), Properties – Mean/ Variance of Estimate Wireless Flat-Fading Channel Estimation, Pilot-based ML Estimate Cramer-Rao Bound (CRB) Vector Parameter Estimation Multi-Antenna Downlink Mobile Channel Estimation Channel Equalization Zero-Forcing (ZF) Equalizer, ZF Example, MMSE example
Post Conditions of the Course At the conclusion of this course, the students should have a good understanding of the following: Ø The student will be able estimate limits on maximum rate at which reliable communication can take place over a noisy channel Ø The student will be able to develop optimal receiver designs for digital communications using statistical communication theory principles Ø The student will be able to analyse performance of digital communication system by considering equivalent signal sets and geometry of decisions regions. Ø The student will be able to design various signal processing procedures in communication systems such as channel estimation, equalization, synchronization etc. , which are employed in 3 G/ 4 G/5 G wireless systems
Textbook and References J. Wozencraft & I. Jacobs, “Principles of Communication Engineering” John Wiley Digital Communications Haykin, Wiley John G. Proakis and M. Salehi, Digital Communications, 5 th Edition, Mc. Graw. Hill, New York, 2007. Fundamentals of Statistical Signal Processing - Author: Steven M. Kay Volume I: Estimation Theory Robert G. Gallager, Principles of Digital Communication, Cambridge University Press, 2008. 15
Course Grading The course will be graded on your results in Mid Sem Exam Final Exam 2 Assignments: After Mid Sem Mini Project/ Paper Implementaion: The final grade will be determined as a weighted combination of the homework and the exam according to the following: Mid Sem Exam: 25% 45% Final Exam: Mini Project/ Paper I’mentation: 20% Assignments: 10% 17
Paper Implementation • On some advanced topics taken from IEEE papers • Potential topics will be provided • Main purposes - To learn some advanced topics related to this course - To prepare you for future research or Industry R & D 18
Necessary Background • It is assumed that students taking this course are familiar with the following topics: - Signal and Linear System Analysis - Noise and Stochastic Processes Random Variables Random Processes Correlation Functions and Power Spectra - Binary modulation - Linear algebra and matrix operation - Experience with MATLAB/Python 20
Related Journals/Conferences • Journals - IEEE Transactions on Communications - IEEE Transactions on Wireless Communications - IEEE Journal on Selected Areas in Communications - IEEE Transactions on Vehicular Technology - IEEE Transactions on Signal Processing - … • Conferences - IEEE International Conferences on Communications (ICC) - IEEE Global Communications Conference (Globecom) - IEEE Wireless Communications and Networking Conference (WCNC) - … 11
Wireless Everywhere Medical applications Various Info/Media Distributed Environmental & Bio Sensing Next generation phones Security Smart RFID New Mobile Devices People to Machines to Machines Tomorrow Trillions of Wireless devices 7
Wireless Revolution 4
Performance Targets of 5 G. . Pushing the Envelope • 1 -10 Gbps connections to end points in the field (i. e. not theoretical maximum) • 1 millisecond end-to-end round trip delay (latency) • 1000 x bandwidth per unit area • 10 -100 x number of connected devices • (Perception of) 99. 999% availability • (Perception of) 100% coverage • 90% reduction in network energy usage • Up to ten year battery life for low power, machine-type devices
Spectral Efficiency slowing down
RF Spectrum Crunch
Unit Value Example Kilobytes (KB) 1, 000 bytes a paragraph of a text document Megabytes (MB) 1, 000 Kilobytes a small novel Gigabytes (GB 1, 000 Megabytes Beethoven’s 5 th Symphony Terabytes (TB) 1, 000 Gigabytes all the X-rays in a large hospital Petabytes (PB) 1, 000 Terabytes half the contents of all US academic research libraries Exabytes (EB) 1, 000 Petabytes about one fifth of the words people have ever spoken 1, 000 Exabytes as much information as there are grains of sand on all the world’s beaches 1, 000 Zettabytes as much information as there atoms in 7, 000 human bodies Zettabytes (ZB) Yottabytes (YB)
Telecommunications in India
Three Segments
Telecommunications Base in India
Wireless Growth
NATIONAL DIGITAL COMMUNICATIONS POLICY - 2018
Digital Communications • Nowadays communications is essential to all sectors of society. Fast and reliable information transmission is EXTREMELY IMPORTANT. • In this era of information technology, it is believed that the prosperity and continued development of modern nations will depend primarily on communications. 12
Transmission Systems • Analog Communications - Continuous modulation - Fidelity is usually defined in terms of SNR. • Digital Communications - Signals made up of discrete symbols selected from a finite set (e. g. , binary data). - Fidelity or Accuracy is specified in terms of bit error rate (Probability of making a bit error). 00011011110 23
Why Digital Communications? 1. Any noise introduces irrecoverable distortion in the analog signal. In comparison, the a digital receiver needs to distinguish only a finite number of transmitted data. Thus, it is possible to nearly remove the effect of noise. 2. Many performance enhancing signal processing techniques, such as source coding, channel coding, encryption, etc. , require digital processing. 3. Digital Integrated Circuits (ICs) have become very powerful and are inexpensive to manufacture. 4. Digital Communications allows integration of voice, video and data on a single system. 5. Compared to analog communication systems, digital communications provides a better tradeoff of bandwidth efficiency against energy efficiency.
Simplified block diagram of a digital communication system Binary interface Information Source Encoder Channel Encoder Modulator Noise Received Information Source Decoder Channel Demodulator 26
Digital Communication Systems -- Source Encoder • Sampling - makes signal discrete in time - signals can be sampled without introducing distortion • Quantization - makes signal discrete in amplitude - Good quantizers are able to use few bits and introduce small distortion • Source Coding - compression of digital data to eliminate redundant information (squeeze out redundant information) - does not introduce distortion 29
Digital Communication Systems -- Channel Encoder • Encryption - ensures data privacy • Channel coding - Provides protection against transmission errors by selectively inserting redundant data - plays an extremely important role in system design • Modulation - Converts digital data to a continuous waveform suitable for transmission (usually a sinusoidal wave) - Information is transmitted by varying one or more parameters of the transmitted signal • Varying Phase such as in Phase Shift Keying (PSK) • Varying Frequency such as in Frequency Shift Keying (FSK) • Varying Amplitude such as in Amplitude Shift Keying (ASK) 30
Parameters that can be modulated: Amplitude: this is called On Off Keying (OOK) or Amplitude Shift Keying (ASK). 1 ⇒ s(t) = Acos(2πfct) 0 ⇒ s(t) = 0 Frequency: this is called Frequency Shift Keying (FSK). 1 ⇒ s(t) = A cos(2πfc 1 t) 0 ⇒ s(t) = A cos(2πfc 2 t) Phase: this is called Phase Shift Keying (PSK). 1 ⇒ s(t) = Acos(2πfct) 0 ⇒ s(t) = A cos(2πfc t + π) = −A cos(2πfc t)
Parameters that can be modulated…contd Amplitude and Phase: this is called Quadrature Amplitude Modulation (QAM). Modern Communications Theory views channel coding and modulation as single operation e. g. , Trellis coded modulation. Choice of modulation greatly affects the system performance
A more detailed picture 27
Challenges 10
Communication Channels • Wireline channels - Telephone network - Twisted-pair wire lines and coaxial cable • Fiber-optic channels - Higher bandwidth, THz • Underwater acoustic channels - With increasing interest, but very challenging to design • Storage channels - Magnetic tape, magnetic disks, optical disks, compact disks • Wireless channels 34
Communication Channels • Channel carries the transmitted signals - could be a telephone wire, free space and often presents distorted signal to demodulator • Impairments include - Attenuation - Transmitted power typically decreases as inverse of square distance - Noise (e. g. , additive white Gaussian noise or AWGN. ) - Filtering • Channel can have a bandwidth that is small compared to the signal bandwidth (e. g. , in a telephone channel). • Transmitted pulses will be changed in shape and smeared out in time causing Inter-symbol interference or ISI. - Fading • Signal amplitude can change in a random fashion - Time Variation • Time-varying channels cause signal fading. • Different components of the signal can be faded at different levels and this often causes random filtering of the signals (hence ISI). 31
Regulation of Radio Spectrum • Government effectively owns radio spectrum and regulates it - In India this regulation is performed by Do. T - Generally one must obtain a license from Do. T to make use of the radio spectrum • Do. T coordinates spectrum with the world authority ITU (International Telecommunications Union) • ITU is an organization under the United Nations - Headquartered in Geneva - Web site http//www. itu. int/ • Radio spectrum is expensive 38
What makes Communications Systems Challenging? • Transmission in a particular application depends on many factors. This includes: � information rate (bit rate) � cost � number of users � quality of service (BER, Delay, SNR) � medium over which the information is to be sent Channel. • Example: wireless systems requires a different design from an optical fibre communications link. 40
What are the Features of a Good Communication System? • Small signal power (measured in Watts or d. Bm) • Large data rate (measured in bits/sec) • Small bandwidth (measured in Hertz) • Low distortion (measured in SNR or bit error rate) • Low cost In practice, there must be tradeoffs made in achieving these goals 41
System Design Tradeoffs Data Rate vs. Bandwidth • Bandwidth Efficiency - defined as the ratio of data rate R to bandwidth W (bits/sec/Hz) Want large bandwidth efficiency - Typical current wireless systems provide < 1 bit/sec/Hz - Newly researched systems can provide > 10 bits/sec/Hz • Increased data rate leads to shorter data pulses which leads to larger bandwidth - This tradeoff (Data Rate vs. Bandwidth) cannot be avoided. • Some modulation schemes use bandwidth more efficiently than others. 42
System Design Tradeoffs Fidelity vs. Signal Power • Energy Efficiency • defined as the ratio of transmitted data to consumed energy (bits/Joule) Want Energy Efficient modulation schemes • One way to get an error free signal would be to use huge amounts of power to blast over the noise - Not practical. • Some types of modulation achieve relatively error free transmission at lower powers than others 43
BE and EE Tradeoff As it often is the case in the life, it is hard to get best of both the worlds. Typically an increase in ηB translates to a decrease in ηE and vice versa. Binary modulation sends only one bit per use of the channel. M−ary modulation sends multiple bits for each use of the channel and provides for an increase in the bandwidth efficiency ηB. However, M−ary modulation schemes are typically energy inefficient and have low ηE. Channel coding increases redundant bits to provide better bit error rate for a given Eb/N 0 or a reduced Eb/N 0 for a given BER. Thus, channel coding improves ηE. However, the redundant bits require greater bandwidth for transmission, and therefore, channel coding reduces ηB.
Bandwidth efficiency As data rate R increases, the pulse width of transmitted signal reduces and therefore the bandwidth B, which is inversely proportional to the transmitted pulse width, increases. This cannot be avoided; however some schemes use the available bandwidth more efficiently than the others We will denote the ratio R/W as the bandwidth efficiency ηB. It is obviously better to have ηB as large as possible. However, there is a cost associated to making ηB large.
Energy Efficiency • • • Digital communication systems are characterized by the ratio Eb/N 0 of required energy per bit Eb to thermal noise floor N 0 that is required to attain a certain performance, e. g. , bit error probability Pb that is below certain threshold 10− 6. Typically making ηB large requires Eb/N 0 to be large; this entails a corresponding increase in transmit energy Eb. We will define energy efficiency ηE = 1 − Eb/ Eb, min Greater the required energy Eb compared to the minimum required energy Eb, min, the smaller the energy efficiency.
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