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3F4 Data Transmission Introduction. Dr. I. J. Wassell. Pre-requisites. Familiarity with IB courses Signal and Data Analysis (Paper 7) Linear Systems and Control (Paper 6) Communications (Paper 6). Booklist.
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3F4 Data TransmissionIntroduction Dr. I. J. Wassell
Pre-requisites • Familiarity with IB courses • Signal and Data Analysis (Paper 7) • Linear Systems and Control (Paper 6) • Communications (Paper 6)
Booklist • Couch, L. W, “Digital and Analog Communication Systems,” Prentice Hall (5th Edition). Covers all except DFE. • Shanmugam, K. S. Digital and Analog Communication Systems,” Wiley. All except DFE. • Proakis, J. G, “Digital Communications,” McGraw Hill. • Wicker, S. B., “Error Control Systems for Digital Communication and Storage,” Prentice Hall, 1995.
Applications • Data transmission over copper cables and optical fibres, e.g., • computer local area networks (LANs) • integrated services digital network (ISDN) connections, e.g., Basic rate (2B+D) and primary rate (30B+2D) channels. B=64kBit/s, D=16kBit/s. • 30 channel pulse code modulation (PCM), i.e., 30 telephony channels, 2.048MBit/s. • Asynchronous transfer mode (ATM) in wide area networks (WANs), e.g., 25MBit/s, 155MBit/s
Applications • Data storage, • magnetic disk drives • magnetic tape drives • optical disk drives
Topics Covered • Communications System Model • Pulse Amplitude Modulation (PAM) for baseband data transmission • Intersymbol Interference (ISI), noise and bit error rates (BER) • Pulse Shaping for bandwidth control and elimination of ISI
Topics Covered • Line coding schemes • Optimum Transmit and Receive Filtering • Equalisation to compensate for undesirable channel characteristics • Error control coding (ECC)
Baseband Transmission • The transmitted signal is limited to a range from -B Hz to +B Hz. |X(f)| |X(f)| 0 0 -B B f -fc fc f Baseband Bandpass • Example baseband channels include • copper cable, magnetic disk, CD-(ROM)
Comms System Model • Transmission of digital data in communications channels • True digital data, eg, comms in a computer network • Analogue information which has been converted to a digital format, eg anti-alias LPF followed by A/D conversion
Error Control Coding Modulator (Transmit Filter, etc) Digital Source Source Encoder Line Coding X(w) Hc(w) Channel Transmitter N(w) Noise + Error Control Decoding Demod (Receive Filter, etc) Digital Sink Source Decoder Line Decoding Y(w) Receiver Transmission Model
Components of the Model • Assume input source is in the form of symbols, eg bytes from a PC, or 16-bit audio samples • Source encoding- Transforms digital symbols into a stream of binary digits (BITS), eg PCM • Error Control Coding- Adding extra bits (redundancy) to allow error checking and correction.
Components of the Model • Line Coding- Coding of the bit stream to make its spectrum suitable for the channel response. Also to ensure the presence of frequency components to permit bit timing extraction at the receiver. • Transmit Filtering- Generation of analogue pulses for transmission by the channel.
Components of the Model • Channel- Will affect the shape of the received pulses. Noise is also present at the receiver input, eg thermal noise, electrical interference etc. • We will concentrate on the components to the right of the vertical dashed line.
Channel Response Assumptions • Linear time-invariant (LTI) frequency response, ie, the channel frequency response Hc(w) is fixed, known and linear. • Additive Gaussian noise- The channel noise has a Gaussian amplitude distribution (pdf) is often assumed to be uncorrelated (ie white, flat power spectral density) and additive.
Channel Response Thus the received signal may be expressed as, Y(w)= Hc(w) X(w)+N(w) Where, Hc (w) is the channel frequency response X(w) is the transmitted signal spectrum N(w) is the noise spectrum In practice, • Channel response may be non-linear, time-varying or unknown • Noise may be non-Gaussian, particularly interference.