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arxiv: 1901.03641 · v1 · pith:6AJCFPXKnew · submitted 2019-01-04 · 💻 cs.IT · cs.DC· cs.NI· math.IT

Convolutionally Coded SNR-Adaptive Transmission for Low-Latency Communications

classification 💻 cs.IT cs.DCcs.NImath.IT
keywords communicationscasescodedcodesconvolutionallydecodinglow-latencysystems
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Fifth generation new radio aims to facilitate new use cases in wireless communications. Some of these new use cases have highly de-manding latency requirements; many of the powerful forward error correction codes deployed in current systems, such as the turbo and low-density parity-check codes, do not perform well when the low-latency requirement does not allow iterative decoding. As such, there is a rejuvenated interest in noniterative/one-shot decoding algorithms. Motivated by this, we propose a signal-to-noise ratio-adaptive convolutionally coded system with optimized constellations designed specifically for a particular set of convolutional code parameters. Numerical results show that significant performance improvements in terms of bit-error-rate and spectral efficiency can be obtained compared to the traditional adaptive modulation and coding systems inlow-latency communications.

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