Implementing a Channel Coding Scheme for an Indoor Wireless System

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Implementing a Channel Coding Scheme for an
Indoor Wireless System

• Christopher Taylor
• Professor Robert W. Brodersen
• Dept. of EECS
• University of California, Berkeley
• January, 2000

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Motivation

• Recent system designs and implementations did not
  include channel coding.
• Provide coding gain to possibly relax the SNR
  requirement of front-end receiver for a fixed
  BER.
• Take advantage of varying channel conditions by
  adapting the coding rate w.r.t to the quality of
  the channel.
• Utilizing multiple transmit and receive antennas
  to enhance coding gains.

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Project Goals

• Conduct an analysis on the effects of different
  modulation and coding schemes using Viterbi
  Algorithm.
• Trellis-code Modulation Block Codes
• Convolutional Codes
• Capture system performance requirement for higher
  modulation schemes.
• What requirements dictated by the algorithm can
  be met by the front-end receiver?

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Coding Approaches

• Separation of Modulation and Coding
• Adaptive coding approach
• Trade-off between data rate and complexity
  against transmitted power
• Used by most Block, Convolutional coding schemes

• Feedback

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Adaptive Coding

• Puncturing
• Selective deletion of bits
• Allows for standard use of a rate 1/2 encoder
• Simplifies complexity of decoder
• Adaptive system using BPSK/QPSK/8PSK
  constellations and code rates varying from 1/2 to
  3/4
• Adaptation is based on channel quality conditions
• Feedback from channel estimator
• Metric used to determine switching thresholds is
  BER prediction

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Coding Approaches

• Coded Modulation
• Provide coding gain without expanding signal
  bandwidth
• Increase number of signal points to compensate
  for redundancy

• Example Trellis-Coded Modulation
• TCM schemes improve gain by 3dB without
  sacrifice of bandwidth

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Viterbi Algorithm

• Optimum Maximum-likelihood decoding algorithm
• Used for decoding Convolutional or trellis codes.
• Algorithm determines most likely path through a
  weighted trellis.

PM S BM (Branch metrics)
The most likely path is determined
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Space-Time Coding

• Uses multiple transmit and receive antennas to
  exploit spatial diversity
• Encoding/decoding complexity comparable to
  trellis codes for Gaussian channels
• Data encoded and split into n streams that are
  transmitted using n transmit antennas
• Can increase bandwidth efficiency by factor of 2-4

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Future Research

• To implement a channel coding scheme that will
  leverage performance gains from varying channel
  conditions
• Research different coding schemes
• Analyze tradeoff between signal processing
  complexity and coding gain
• Optimize tradeoff between transmitted signal
  power and channel bandwidth
• Create a fixed-point Simulink model of a Viterbi
  decoder to map to hardware modules