Joint Source-Channel Coding using Trellis Coded CPM
Doctoral thesis, 2005
The thesis investigates Joint Source and Channel Coding
(JSCC) using combined Trellis Coded Quantization (TCQ) and coded modulation. First we investigate a JSCC scheme using combined TCQ/Trellis Coded CPM (TCQ/TCCPM). Based on the BCJR algorithm for trellis coded CPM, we derive an optimal soft decoding algorithm for the considered systems. Analytical bounds on the channel distortion for jointly designed TCQ/TCCPM systems with maximum likelihood sequence detection are derived. These bounds are based on the transfer function technique, which has been modified and generalized to analog signals in discrete time for our purpose.
This work provides an analysis tool to estimate the performance for a given combined TCQ/TCCPM system. The analysis method is very general, and may be applied to any trellis based JSCC scheme. Next, we develop an iterative decoding approach to JSCC using serially concatenated TCQ/CPM. This iterative procedure exploits the structure of the TCQ encoder and the continuous phase modulator. A new trellis quantization scheme based on punctured ring convolutional codes is also proposed. It is demonstrated that the new trellis source encoding scheme is superior to conventional Trellis Coded Vector Quantization (TCVQ) scheme of the same complexity. Furthermore, an adaptive JSCC scheme using the combined new trellis quantization scheme with CPM is investigated.
The decoding algorithm is based on the BCJR algorithm for punctured ring convolutional coded CPM. An iterative decoding approach to the above mentioned adaptive JSCC scheme is also developed. The performance is analyzed by using the extrinsic information transfer chart.
serially concatenated CPM
punctured ring convolutional codes.
trellis coded quantization
turbo trellis coded modulation
ring convolutional coded CPM
continuous phase modulation
Joint source channel coding
13.15 HC1, Hörsalsvägen 14, Chalmers
Opponent: Professor Stephen G Wilson, Department of Electrical and Computer Engineering, University of Virginia, USA