TY - JOUR
T1 - Block Sparse Vector Codes for Ultra-Reliable and Low-Latency Short-Packet Transmission
AU - Zhang, Yanfeng
AU - Zhu, Xu
AU - Liu, Yujie
AU - Fan, Xi'an
AU - Guan, Yong Liang
AU - Wong, M. L.Dennis
AU - Lau, Vincent K.N.
N1 - Publisher Copyright:
© 1972-2012 IEEE.
PY - 2025/4/18
Y1 - 2025/4/18
N2 - Sparse vector coding (SVC) is a promising short-packet transmission method for ultra reliable low latency communication (URLLC) in next-generation communication systems. In this paper, a block SVC (BSVC) based short-packet transmission scheme is proposed to further enhance the transmission performance of SVC. The core idea behind the proposed scheme is to transmit short-packet data information after block sparse transformation. At the transmitter, the information bits are divided into two parts: one part is mapped into the non-zero indexes of block sparse vectors, and the other part is mapped into non-zero values through phase or amplitude modulation. After pseudo-random spreading, the block sparse vectors are mapped to time-frequency resources for transmission. At the receiver, the decoding problem is transformed into a block sparse signal recovery problem. A cyclic block orthogonal matching pursuit (CBOMP) algorithm is proposed for decoding by leveraging block-structured sparse prior information. The upper bound of block error rate (BLER) performance over Rayleigh channels is derived to verify the decoding performance of the proposed CBOMP algorithm. Extensive simulation results verify that the proposed BSVC scheme outperforms the existing SVC schemes in terms of BLER, transmission latency and spectral efficiency over fading channels.
AB - Sparse vector coding (SVC) is a promising short-packet transmission method for ultra reliable low latency communication (URLLC) in next-generation communication systems. In this paper, a block SVC (BSVC) based short-packet transmission scheme is proposed to further enhance the transmission performance of SVC. The core idea behind the proposed scheme is to transmit short-packet data information after block sparse transformation. At the transmitter, the information bits are divided into two parts: one part is mapped into the non-zero indexes of block sparse vectors, and the other part is mapped into non-zero values through phase or amplitude modulation. After pseudo-random spreading, the block sparse vectors are mapped to time-frequency resources for transmission. At the receiver, the decoding problem is transformed into a block sparse signal recovery problem. A cyclic block orthogonal matching pursuit (CBOMP) algorithm is proposed for decoding by leveraging block-structured sparse prior information. The upper bound of block error rate (BLER) performance over Rayleigh channels is derived to verify the decoding performance of the proposed CBOMP algorithm. Extensive simulation results verify that the proposed BSVC scheme outperforms the existing SVC schemes in terms of BLER, transmission latency and spectral efficiency over fading channels.
KW - block-sparse recovery algorithm
KW - short-packet communications
KW - sparse vector coding
KW - ultra reliable low latency communication
UR - https://openalex.org/W4409580952
UR - https://www.scopus.com/pages/publications/105002809989
U2 - 10.1109/TCOMM.2025.3562520
DO - 10.1109/TCOMM.2025.3562520
M3 - Journal Article
SN - 0090-6778
JO - IEEE Transactions on Communications
JF - IEEE Transactions on Communications
ER -