Guang-Chong Zhu

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We investigate the joint source-channel coding problem of transmitting nonuniform memoryless sources over binary phase-shift keying-modulated additive white Gaussian noise and Rayleigh fading channels via turbo codes. In contrast to previous work, recursive nonsystematic convolutional encoders are proposed as the constituent encoders for heavily biased(More)
We investigate the construction of joint source-channel (JSC) turbo codes for the reliable communication of binary Markov sources over additive white Gaussian noise and Rayleigh fading channels. To exploit the source Markovian redundancy, the first constituent turbo decoder is designed according to a modified version of Berrou's original decoding algorithm(More)
This work addresses the problem of designing turbo codes for nonuniform binary memoryless or independent and identically distributed (i.i.d.) sources over noisy channels. The extrinsic information in the decoder is modified to exploit the source redundancy in the form of nonuniformity; furthermore, the constituent encoder structure is optimized for the(More)
A robust soft-decision channel-optimized vector quantization (COVQ) scheme for turbo coded additive white Gaussian noise (AWGN) and Rayleigh fading channels is proposed, The log likelihood ratio (LLR) generated by the turbo decoder is exploited via the use of a q-bit scalar soft-decision demodulator. The concatenation of the turbo encoder, modulator, AWGN(More)
We investigate the use of finite-geometry low-density parity-check (FG-LDPC) codes for channels with stuckat defects. Such a channel is corrupted by a stuck-at defect pattern in addition to the usual channel-induced noise. When the defect pattern is known to the encoder but not to the decoder, the capacity of the channel is the same as if the defect pattern(More)
In this work, we try to collect useful emotional stress information from electrocardiogram (ECG) signals via a real-time wearable Wireless Body Area Network (WBAN). Discrete Wavelet Transform (DWT) is applied on collected ECG signals for feature extraction, which carries important information for stress level identification. After the stress level is(More)