Constant Curvature Curve Tube Codes for Low-Latency Analog Error Correction

Recent research in ultra-reliable and low latency communications (URLLC) for future wireless systems has spurred interest in short block-length codes. In this context, we analyze arbitrary harmonic bandwidth (BW) expansions for a class of high-dimension constant curvature curve codes for analog erro...

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Veröffentlicht in:IEEE transactions on information theory 2023-12, Vol.69 (12), p.1-1
Hauptverfasser: Buvarp, Anders M., Taylor, Robert M., Mishra, Kumar Vijay, Mili, Lamine, Zaghloul, Amir I.
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Taylor, Robert M.
Mishra, Kumar Vijay
Mili, Lamine
Zaghloul, Amir I.
description Recent research in ultra-reliable and low latency communications (URLLC) for future wireless systems has spurred interest in short block-length codes. In this context, we analyze arbitrary harmonic bandwidth (BW) expansions for a class of high-dimension constant curvature curve codes for analog error correction of independent continuous-alphabet uniform sources. In particular, we employ the circumradius function from knot theory to prescribe insulating tubes about the centerline of constant curvature curves. We then use tube packing density within a hypersphere to optimize the curve parameters. The resulting constant curvature curve tube (C3T) codes possess the smallest possible latency, i.e., block-length is unity under BW expansion mapping. Further, the codes perform within 5 dB signal-to-distortion ratio of the optimal performance theoretically achievable at a signal-to-noise ratio (SNR) < -5 dB for BW expansion factor n ≤ 10. Furthermore, we propose a neural-network-based method to decode C3T codes. We show that, at low SNR, the neural-network-based C3T decoder outperforms the maximum likelihood and minimum mean-squared error decoders for all n . The best possible digital codes require two to three orders of magnitude higher latency compared to C3T codes, thereby demonstrating the latter's utility for URLLC.
doi_str_mv 10.1109/TIT.2023.3302318
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In this context, we analyze arbitrary harmonic bandwidth (BW) expansions for a class of high-dimension constant curvature curve codes for analog error correction of independent continuous-alphabet uniform sources. In particular, we employ the circumradius function from knot theory to prescribe insulating tubes about the centerline of constant curvature curves. We then use tube packing density within a hypersphere to optimize the curve parameters. The resulting constant curvature curve tube (C3T) codes possess the smallest possible latency, i.e., block-length is unity under BW expansion mapping. Further, the codes perform within 5 dB signal-to-distortion ratio of the optimal performance theoretically achievable at a signal-to-noise ratio (SNR) &lt; -5 dB for BW expansion factor n ≤ 10. Furthermore, we propose a neural-network-based method to decode C3T codes. We show that, at low SNR, the neural-network-based C3T decoder outperforms the maximum likelihood and minimum mean-squared error decoders for all n . 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Codes
Curvature
Decoders
Decoding
Electron tubes
Error correction
Error correction & detection
Error correction codes
Hyperspheres
Knot theory
Mathematical problems
Maximum likelihood decoding
Network latency
Neural networks
Optimization
Packing density
Signal to noise ratio
Spirals
Tubes
Ultra reliable low latency communication
title Constant Curvature Curve Tube Codes for Low-Latency Analog Error Correction
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