Cooperative communication using turbo product codes with mutiple-source spatial and temporal correlations

Distributed Joint Source Coding and Trellis Coded Modulation for Symbol-Based Markov Sources

“…Thus, saving energy is crucial. Distributed source coding (DSC) constitutes a promising solution, since it is capable of exploiting the correlation of the sources for reducing the overall energy consumption [1]- [27]. Furthermore, it shifts the power-hungry signal processing to the central base station, whilst ensuring a low complexity at the sensor nodes.…”

“…The temporal correlation statistics can also be jointly exploited along with the spatial inter-source correlation for further enhancing the overall performance of the network. However, as compared to the number of studies exploiting either the spatial or temporal correlation, there is a paucity of contributions on handling the spatio-temporal correlation [24]- [27]. These investigations have demonstrated that further performance enhancements can be achieved upon jointly exploiting both the spatial and temporal correlations compared to exploiting only the spatial correlation.…”

“…These investigations have demonstrated that further performance enhancements can be achieved upon jointly exploiting both the spatial and temporal correlations compared to exploiting only the spatial correlation. However, the schemes proposed in [24]- [27] were designed for binary sources and for binary phase-shift keying (BPSK) transmission over either additive white Gaussian noise (AWGN) channels [24]- [26] or over Rayleigh fading channels [27].…”

“…We further develop the BPSK-aided AWGN scenario of [24]- [26] to more realistic uncorrelated Rayleigh fading channels and high-order modulation schemes. • Additionally, in contrast to the DJSCC schemes of [24]- [27] that are only capable of exploiting the spatiotemporal correlation of binary sources, we consider a generalized symbol-based DJSCC for exploiting the spatio-temporal correlation of symbol-based sources, which can be binary or non-binary. A symbol-based maximum a-posteriori (MAP) algorithm [40] is invoked for URC and TCM decoding in order to avoid information loss due to bit-to-symbol or symbol-to-bit conversion between the source and channel decoders.…”