Capacity estimation and code design principles for continuous phase modulation (CPM)
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Continuous Phase Modulation is a popular digital modulation scheme for systems which have tight spectral efficiency and Peak-to-Average ratio (PAR) constraints. In this thesis we propose a method of estimating the capacity for a Continuous Phase Modulation (CPM) system and also describe techniques for design of codes for this system. We note that the CPM modulator can be decomposed into a trellis code followed by a memoryless modulator. This decomposition enables us to perform iterative demodulation of the signal and improve the performance of the system. Thus we have the option of either performing iterative demodulation, where the channel decoder and the demodulator are invoked in an iterative fashion, or a non-iterative demodulation, where the demodulation is performed only once followed by the decoding of the message. We highlight the recent results in the estimation of capacity for channels with memory and apply it to a CPM system. We estimate two different types of capacity of the CPM system over an Additive White Gaussian Noise (AWGN). The first capacity assumes that optimum demodulation and decoding is done, and the second one assumes that the demodulation is done only once. Having obtained the capacity of the system we try to approach this capacity by designing outer codes matched to the CPM system. We utilized LDPC codes, since they can be designed to perform very close to capacity limit of the system. The design complexity for LDPC codes can be reduced by assuming that the input to the decoder is Gaussian distributed. We explore three different ways of approximating the CPM demodulator output to a Gaussian distribution and use it to design LDPC codes for a Bit Interleaved Coded Modulation (BICM) system. Finally we describe the design of Multi Level Codes (MLC) for CPM systems using the capacity matching rule.
Ganesan, Aravind (2003). Capacity estimation and code design principles for continuous phase modulation (CPM). Master's thesis, Texas A&M University. Texas A&M University. Available electronically from