Rights statement: ©2022 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Accepted author manuscript, 421 KB, PDF document
Available under license: CC BY: Creative Commons Attribution 4.0 International License
Submitted manuscript
Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Symbol-level GRAND for high-order modulation over block fading channels
AU - Chatzigeorgiou, I.
AU - Monteiro, Francisco
N1 - ©2022 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
PY - 2023/2/1
Y1 - 2023/2/1
N2 - Guessing random additive noise decoding (GRAND) is a noise-centric decoding method, which is suitable for low-latency communications, as it supports error correction codes that generate short codewords. GRAND estimates transmitted codewords by guessing the error patterns that altered them during transmission. The guessing process requires the testing of error patterns that are arranged in increasing order of Hamming weight. This approach is fitting for binary transmission over additive white Gaussian noise channels. This letter considers transmission of coded and modulated data over block fading channels and proposes a more computationally efficient variant of GRAND, which leverages information on the modulation scheme and the fading channel. In the core of the proposed variant, referred to as symbol-level GRAND, is an expression that approximately computes the probability of occurrence of an error pattern and determines the order with which error patterns are tested. Analysis and simulation results demonstrate that symbol-level GRAND produces estimates of the transmitted codewords faster than the original GRAND at the cost of a small increase in memory requirements.
AB - Guessing random additive noise decoding (GRAND) is a noise-centric decoding method, which is suitable for low-latency communications, as it supports error correction codes that generate short codewords. GRAND estimates transmitted codewords by guessing the error patterns that altered them during transmission. The guessing process requires the testing of error patterns that are arranged in increasing order of Hamming weight. This approach is fitting for binary transmission over additive white Gaussian noise channels. This letter considers transmission of coded and modulated data over block fading channels and proposes a more computationally efficient variant of GRAND, which leverages information on the modulation scheme and the fading channel. In the core of the proposed variant, referred to as symbol-level GRAND, is an expression that approximately computes the probability of occurrence of an error pattern and determines the order with which error patterns are tested. Analysis and simulation results demonstrate that symbol-level GRAND produces estimates of the transmitted codewords faster than the original GRAND at the cost of a small increase in memory requirements.
KW - Additive noise
KW - block fading
KW - Demodulation
KW - Fading channels
KW - GRAND
KW - hard detection
KW - QAM
KW - Random linear codes
KW - Receivers
KW - short-packet communication
KW - Signal to noise ratio
KW - Symbols
KW - Ultra reliable low latency communication
KW - URLLC
KW - Decoding
KW - Error correction
KW - Gaussian noise (electronic)
KW - Quadrature amplitude modulation
KW - Signal receivers
KW - White noise
KW - Block fading
KW - Fadings channels
KW - Guessing random additive noise decoding
KW - Hard detection
KW - Low-latency communication
KW - Receiver
KW - Short packet communication
KW - Symbol
U2 - 10.1109/LCOMM.2022.3227593
DO - 10.1109/LCOMM.2022.3227593
M3 - Journal article
VL - 27
SP - 447
EP - 451
JO - IEEE Communications Letters
JF - IEEE Communications Letters
SN - 1089-7798
IS - 2
ER -