Efficient digital transmission of analog speech, audio or video requires source coding which introduces unavoidable quantization errors. The bit stream produced by the source encoder needs to be protected against transmission errors by channel coding. The split of a given gross bit rate between source and channel coding is a compromise taking into account the design target of the worst case channel. Thus, even in clear channel conditions the quality of the decoded source signal is limited because of the quantization errors. Hybrid digital-analog (HDA) codes address this limitation by additionally transmitting the quantization error with quasi-analog methods (discrete-time, quasi-continuous-amplitude) with neither increasing the transmit power, nor the occupied frequency bandwidth on the radio channel. However, the decoding complexity of existing HDA codes is infeasible for the required block lengths. In this paper, the decoding complexity problem is solved by a new design approach. These HDA codes benefit from well-known digital codes. Furthermore, theoretical bounds are derived and explicit guidelines for the design of superior HDA systems are given. By experimental verification it is shown that the HDA concept may outperform conventional purely digital transmission systems at all channel qualities while additionally eliminating the quality saturation effect.

One problem of conventional digital transmission systems is that the transmission fidelity always saturates at the design channel quality (worst-case channel condition); this saturation is due to the irreversible quantization error introduced by the source coder. Hybrid digital analog (HDA) codes address this problem by additionally transmitting the inherent quantization error by pseudo-analog methods. However, the design and the decoding of these HDA codes is complex or even impossible for long block lengths (look-up table decoding). In this study we propose an HDA transmission system for sources with correlation supporting long block lengths. This is achieved by combining transform coding with HDA transmission using well-known digital channel codes. For the evaluation Monte Carlo simulations are used with a normalized discrete cosine transform (DCTN) and Turbo codes as the digital part and LMMSE estimation in the pseudo-analog part of the HDA system. The proposed HDA system with transform coding outperforms the purely digital transmission system at all channel qualities and exploits the expected gain due to source correlation.

Robust speech enhancement relies on the estimation of stationary as well as non-stationary background noise. This contribution presents a novel approach for estimating the short-term power spectral densities (ST-PSDs) of rapidly time-varying harmonic noise as produced, e.g., by cars or motorcycles. The well-known Minimum Statistics algorithm is modified by frequency warping controlled by the fundamental frequency of the harmonic noise which is assumed to be known a priori. The resulting noise estimates are used for the enhancement of the noisy signal. A detailed description of the algorithm is given and it is shown by a thorough analysis that the new solution considerably outperforms two conventional noise ST-PSD estimation techniques.

In some applications the transmission of discrete-time but continuous-amplitude (or multilevel) source symbols is required which might be more bandwidth efficient than conventional digital transmission. An appropriate method is to apply a source channel mapping (SCM) of M source symbols to N channel symbols. A geometrical approach for SCM has been introduced by Shannon and Kotel'nikov (Shannon-Kotel'nikov mappings). These systems are used to map M continuous-amplitude and discrete-time source symbols to N continuous-amplitude and discrete-time channel symbols without the intermediate step of a binary representation. These schemes are usually decoded using a maximum likelihood (ML) decoder which leads to optimum results in the mean square error sense for very good channels, but is suboptimal for noisy channels. In this paper the performance of an improved decoder, the minimum mean square error (MMSE) decoder is assessed. As a special case of a 1:2 expansion case (rate 1/2) Shannon-Kotel'nikov mapping, the Archimedes spiral is considered. The properties of the ML and MMSE decoder are examined and a graphical interpretation of the superior performance of the MMSE decoder is given. Furthermore, the robustness of the MMSE decoder w.r.t. an inaccurate estimation of the channel quality is determined. The concepts of the MMSE decoder which lead to a superior performance to the ML decoder can be generalized and applied to all Shannon-Kotel'nikov mappings.