DIGITAL COMMUNICATIONS LECTURE NOTES B.TECH (III YEAR – II SEM) (2017-18) Prepared by: Mrs. P. Swetha, Assistant Professor Mrs. S. Rajani, Assistant Professor Mr. KDK Ajay, Assistant Professor Department of Electronics and Communication Engineering MALLA REDDY COLLEGE OF ENGINEERING & TECHNOLOGY (Autonomous Institution – UGC, Govt. of India) Recognized under 2(f) and 12 (B) of UGC ACT 1956 (Affiliated to JNTUH, Hyderabad, Approved by AICTE - Accredited by NBA & NAAC – ‘A’ Grade - ISO 9001:2015 Certified) Maisammaguda, Dhulapally (Post Via. Kompally), Secunderabad – 500100, Telangana State, India
MALLA REDDY COLLEGE OF ENGINEERING AND TECHNOLOGY III Year B.Tech. ECE-II Sem L T/P/D C 4 1/ - /- 3 (R15A0413) DIGITAL COMMUNICATIONS OBJECTIVES: 1. To understand the building blocks of digital communication system. 2. To prepare mathematical background for communication signal analysis. 3. To understand and analyze the signal flow in a digital communication system. 4. To analyze error performance of a digital communication system in presence of noise and other interferences. UNIT I Pulse Digital Modulation: Elements of digital communication systems, advantages of digital communication systems, Elements of PCM: Sampling, Quantization & Coding, Quantization error, Companding in PCM systems. Differential PCM systems (DPCM). Time Division Multiplexing & Demultiplexing. Delta Modulation: Delta modulation, its draw backs, adaptive delta modulation, comparison of PCM and DM systems, Noise in PCM and DM systems. Illustrative Problems. UNIT II Digital Modulation Techniques: Introduction, ASK modulator, Coherent and Non-Coherent ASK detector, FSK modulator, Spectrum of FSK, coherent reception, non-coherent detection of FSK. BPSK transmitter, Coherent reception of BPSK, DPSK, QPSK. Data Transmission: Base band signal receiver, probability of error, The optimum filter, Matched filter, probability of error using matched filter.Optimum filter using correlator.Probability of error of ASK,FSK,BPSK and QPSK. Illustrative Problems. UNIT III Information Theory: Discrete messages, Concept of amount of information and its properties. Average information, Entropy and its properties. Information rate, Mutual information and its properties, Illustrative Problems. Source Coding: Introduction, Advantages, Hartley Shannon’s theorem, bandwidth –S/N trade off, Shanon- Fano coding, Huffman coding, Illustrative Problems. UNIT IV Linear Block Codes: Introduction, Matrix description of Linear Block codes, Error detection and error correction capabilities of linear block codes, Hamming codes. Cyclic Codes: Encoding, Syndrome Calculation, Decoding, UNIT V Convolution Codes: Introduction, encoding of convolution codes, time domain approach, transform domain approach. Graphical approach: State, Tree and Trellis diagram. Decoding using Viterbi algorithm Illustrative Problems. TEXT BOOKS: 1. Digital communications - Simon Haykin, John Wiley, 2005 2. Principles of Communication Systems – H. Taub and D. Schilling, TMH, 2003 REFERENCES: 1. Digital and Analog Communication Systems – K.Sam Shanmugam, John Wiley, 2005.
2. Digital Communications – John Proakis, TMH, 1983. Communication Systems Analog & Digital – Singh & Sapre, TMH, 2004. 3. Modern Analog and Digital Communication – B.P.Lathi, Oxford reprint, 3rd edition, 2004. OUTCOMES: At the end of the course, the student will be able to: 1. Understand basic components of digital communication systems 2. Design Optimum receivers for digital modulation techniques 3. Analyze the error performance of digital modulation techniques 4. Know about different error detecting and error correcting codes.
UNIT-1 Digital Pulse Modulation Elements of Digital Communication Systems: Fig. 1 Elements of Digital Communication Systems 1. Information Source and Input Transducer: The source of information can be analog or digital, e.g. analog: audio or video signal, digital: like teletype signal. In digital communication the signal produced by this source is converted into digital signal which consists of 1′s and 0′s. For this we need a source encoder. 2. Source Encoder: In digital communication we convert the signal from source into digital signal as mentioned above. The point to remember is we should like to use as few binary digits as possible to represent the signal. In such a way this efficient representation of the source output results in little or no redundancy. This sequence of binary digits is called information sequence. Source Encoding or Data Compression: the process of efficiently converting the output of whether analog or digital source into a sequence of binary digits is known as source encoding. 1