Turbo Product Code-Aided Spatiotemporal 2-D Coded MIMO for URLLC
The ultra-reliable low-latency communication (URLLC) scenario beyond the fifth-generation mobile networks requires latency to shift from ms-level to ms-level while maintaining low packet error rates. Short block-length codes can reduce latency but suffer from performance degradation. Asymptotic analyses indicate that increasing spatial degrees of freedom in multiple-input multiple-output (MIMO) systems help to achieve target error rates with a fixed block length and signal-to-noise ratio. To approach the upper bound of the average maximal achievable information rate in massive MIMO systems, spatiotemporal 2-D channel coding has been proposed. However, a considerable gap remains between the performance of the existing coding scheme and the theoretical capacity bound. To bridge this gap, this article introduces turbo product codes aided spatiotemporal 2-D coded MIMO systems (TPCAS-MIMO). Multi-level design on the baseband MIMO transceiver, involving encoding, interleaving, modulation, detection, and decoding schemes, is explored to boost the performance of TPCAS-MIMO with low latency for URLLC. In comparison to prior arts, this work achieves a 5.5 dB SNR gain at a frame error rate of 10–5 using (64, 42)2 polar turbo product codes in a 64 x 128 MIMO system, narrowing to a mere 2.5 dB gap from the theoretical capacity bound.
Authors
- Xiaosi Tan (ORCID: https://orcid.org/0000-0003-2965-2662)
- Yongming Huang (ORCID: https://orcid.org/0009-0009-2545-2875)
- Xiaohu You (ORCID: https://orcid.org/0000-0002-0809-8511)
- Chuan Zhang (ORCID: https://orcid.org/0000-0002-7736-6487)
- Jiamin Li (ORCID: https://orcid.org/0000-0002-4527-3147)
- Yifei Shen (ORCID: https://orcid.org/0000-0003-4745-9145)
- Zongyao Li (ORCID: https://orcid.org/0009-0003-1081-4833)
- Wenyue Zhou (ORCID: https://orcid.org/0009-0004-6519-1589)
- Yu Tian (ORCID: https://orcid.org/0000-0001-5338-8035)
- Tiancan Xia
- Jian Zheng (ORCID: https://orcid.org/0009-0001-5742-3894)
Publication Details
- Journal
- IEEE Communications Magazine
- Published
- 2025-06-24
- DOI
- https://doi.org/10.1109/mcom.001.2400618
- Citations
- 2
- Primary Topic
- Gene expression and cancer classification
- Type
- article
- Field-Weighted Citation Impact
- 1.61