《现代数字通信与编码理论》讲义 Principles of Advanced Digital Communications and Coding 白宝明 西安电子科技大学 综合业务网国家重点实验室 2010年7月 1
1 《现代数字通信与编码理论》讲义 Principles of Advanced Digital Communications and Coding 白宝明 西安电子科技大学 综合业务网国家重点实验室 2010 年 7 月
Course Information for 0122229 现代数字通信与编码理论 (Principles of advanced digital communications and coding) The goal of this class is to introduce the information transmission techniques used in modern cor mmun with e advanced 各种信道模型（包括功率受限、带宽受限、ISl、衰落、多天线等）及其Shannon容量的计算： 最新的可达容量限的信道码的编译码原理；现代编码通信系统的性能分析技术。 Prerequisite:Principles of communications Error control coding(preferable but not necessary) Instructor:Prof.Baoming BAI Assistant: Time and place:Monday 8:30-10:05 am.and Wednesday 3:35-5:10 p.m.in Classroom 2.04 Grading:50%Homework 50%Project (The project will involve in writing a report as well as an oral presentation) Class WWW page: Outline Preliminaries -Phase splitter and analytic signal -Complex baseband representation of passband signals -Signal space representations ric Gaussian processes Signal constellation PAM and QAM transmission systems Capacity for M-PAM and M-QAM signaling -The gap between uncoded performance and the Shannon limit -Performance analysis of small signal constellations -Design of signal constellations Performance Analysis of Coded Commuication Systems -Approac ing capacity with coding
3 Course Information for 0122229 现代数字通信与编码理论 （Principles of advanced digital communications and coding） The goal of this class is to introduce the information transmission techniques used in modern communication systems, with emphasis on information-theoretic and advanced coding aspects. This is done by understanding the following course contents: 各种信道模型（包括功率受限、带宽受限、ISI、衰落、多天线等）及其 Shannon 容量的计算； 最新的可达容量限的信道码的编译码原理；现代编码通信系统的性能分析技术。 Prerequisite: Principles of communications Error control coding (preferable but not necessary) Instructor: Prof. Baoming BAI Assistant: Time and place: Monday 8:30 – 10:05 a.m. and Wednesday 3:35 – 5:10 p.m. in Classroom J2-04 Grading: 50% Homework 50% Project (The project will involve in writing a report as well as an oral presentation) Class WWW page: Outline Preliminaries - Phase splitter and analytic signal - Complex baseband representation of passband signals - Signal space representations - Circularly symmetric Gaussian processes - Some facts from information theory Digital Transmission of Information over Ideal AWGN Channels (10 hours) - Discrete-time AWGN channel model - Signal constellation - PAM and QAM transmission systems - Capacity for M-PAM and M-QAM signaling - The gap between uncoded performance and the Shannon limit - Performance analysis of small signal constellations - Design of signal constellations Performance Analysis of Coded Communication Systems - Approaching capacity with coding
-Techniques for performance analysis of coded communication systems -Bhattacharyya bound and Gallager bound Introduction to Modern Coding Theory (8 hours) Trellis representation of codes and decoding on a trellis(linear block codes,VA. BCJR) codes and the iterative decoding principles D nce analysis -LDP de ed on graphs and the sum-product algorithm es Bandvidth-Efficient Coded-Modulation Techniques (for Ideal Band-limited Channels)(8 hours) -Lattice constellations Shaping gain -TCM principles and performance analysis techniques Multi-dimentional TCM and multiple TCM -TCM codes ultilevel cod age decoding teeaed codedmodulousin Turbo codes and LDPC codes (Gallager ng a pping llation shaping techniques Transmission over linear gaussian channels (6 hours) -Iinear Gaussian channels -Equivalent discrete-time model -Principles of"water pouring"and evaluation of the channel capacity -Optimal receiver in the presence of both ISI and AWGN Optimal detection:MAP,ML sequence detection Symbol-by-symbol equalization methods:MMSE-LE,ZF-LE and MMSE-DFE Tomlinson-H arishima precoding Coding for ISI channels Principl s of Turbo equalization -Approaching capacity with parallel transmission:COFDM Comn over Fading Channels(5 hours) nel r -Capacity of wireless channels -Diversity techniques -Coding for fading channels(including adaptive coding&modulation) -Bound on the probability of decoding error -Information-theoretic aspects of spread-spectrum communications unications(5 hours) ntenna el models I s cn and spatia I mu plexing ng a ce-t Ce- or space-time codes on fading channels coding sch 4
4 - Techniques for performance analysis of coded communication systems - Bhattacharyya bound and Gallager bound Introduction to Modern Coding Theory (8 hours) - Trellis representation of codes and decoding on a trellis (linear block codes, VA, BCJR) - Turbo codes and the iterative decoding principles - Performance analysis - Codes defined on graphs and the sum-product algorithm - LDPC codes Bandwidth-Efficient Coded-Modulation Techniques (for Ideal Band-limited Channels) (8 hours) - Lattice constellations - Shaping gain - TCM principles and performance analysis techniques - Multi-dimentional TCM and multiple TCM - Turbo-TCM codes - Multilevel coding and multistage decoding - Bit-interleaved coded modulation using Turbo codes and LDPC codes (Gallager mapping) - Constellation shaping techniques Transmission over Linear Gaussian Channels (6 hours) - Linear Gaussian channels - Equivalent discrete-time model - Principles of “water pouring” and evaluation of the channel capacity - Optimal receiver in the presence of both ISI and AWGN - Optimal detection: MAP, ML sequence detection - Symbol-by-symbol equalization methods: MMSE-LE, ZF-LE and MMSE-DFE - Tomlinson-Harishima precoding - Coding for ISI channels - Principles of Turbo equalizations - Approaching capacity with parallel transmission: COFDM Communications over Fading Channels (5 hours) - Wireless channel models - Capacity of wireless channels - Diversity techniques - Coding for fading channels (including adaptive coding & modulation) - Bound on the probability of decoding error - Information-theoretic aspects of spread-spectrum communications MIMO Wireless Communications (5 hours) - Multi-antenna (MIMO) channel models - Capacity of MIMO wireless channels - Diversity and spatial multiplexing - Approaching capacity with space-time coding - Performance analysis and design criteria for space-time codes on fading channels - Various space-time coding schemes
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