Convolutionally Coded SNR-adaptive Transmission for Low-Latency Communications
5G new radio (NR) aims to facilitate new use cases in wireless communications. Some of these new use cases have highly demanding latency requirements; many of the powerful forward error correction (FEC) codes deployed in current systems, such as the turbo and low-density parity-check (LDPC) codes, do not perform well when the low-latency requirement does not allow iterative decoding. As such, there is a rejuvenated interest in non-iterative/one-shot decoding algorithms. Motivated by this, we propose an signal-to-noise ratio (SNR)-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 in low-latency communications.
|Journal||IEEE Transactions on Vehicular Technology|
Ilter, M.C. (Mehmet Cagri), & Yanikomeroglu, H. (2018). Convolutionally Coded SNR-adaptive Transmission for Low-Latency Communications. IEEE Transactions on Vehicular Technology. doi:10.1109/TVT.2018.2844019