Abstract
Polar codes have strongly entered into action within the standardization of the next generation 5G mobile communication systems, which are expected to be an enabling technology for the Internet of Things where networks with a large number of sensors have to handle massive connectivity demands. This paper proposes and investigates the use of systematic polar codes for joint source-channel coding of correlated sources in wireless sensor networks, thus allowing the compression of the volume of data to be transmitted over the network on one hand, and on the other hand, the protection of this data from channel impairments. Results show that systematic polar codes can achieve a distributed compression with rates close to theoretical limits, with better error rates obtained for larger blocks, and a better robustness against transmission errors obtained with stronger compression and shorter block lengths. Furthermore, while the system is able to overcome the effect of noise on parity information with adequate power management, noisy side information significantly degrades system performance with remarkable gaps towards the case of distributed compression with an ideal transmission channel.
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