TY - GEN
T1 - Sparse Matrix Codes
T2 - 56th Annual Conference on Information Sciences and Systems, CISS 2022
AU - Adiga, Sudarshan
AU - Tandon, Ravi
AU - Bose, Tamal
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - In this paper, we present a new channel coding technique, namely sparse matrix codes (SMC), for URLLC applications with the goal of achieving higher reliability, and low decoding complexity. The main idea behind SMC is to map the message bits to a structured sparse matrix which is then multiplied by a spreading matrix and transmitted over the communication channel over time-or frequency resources. At the decoder, we recover the message from the channel output using a low-decoding complexity algorithm which is derived by leveraging and adapting tools from 2D compressed sensing. We perform various experiments to compare our approach with sparse vector code (SVC) and Polar codes for block error rate (BLER). From our experiments, we show that for a fixed code rate and reliability requirement (BLER), SMC operates at shorter blocklengths compared to Polar codes and SVC.
AB - In this paper, we present a new channel coding technique, namely sparse matrix codes (SMC), for URLLC applications with the goal of achieving higher reliability, and low decoding complexity. The main idea behind SMC is to map the message bits to a structured sparse matrix which is then multiplied by a spreading matrix and transmitted over the communication channel over time-or frequency resources. At the decoder, we recover the message from the channel output using a low-decoding complexity algorithm which is derived by leveraging and adapting tools from 2D compressed sensing. We perform various experiments to compare our approach with sparse vector code (SVC) and Polar codes for block error rate (BLER). From our experiments, we show that for a fixed code rate and reliability requirement (BLER), SMC operates at shorter blocklengths compared to Polar codes and SVC.
UR - http://www.scopus.com/inward/record.url?scp=85128754136&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85128754136&partnerID=8YFLogxK
U2 - 10.1109/CISS53076.2022.9751171
DO - 10.1109/CISS53076.2022.9751171
M3 - Conference contribution
AN - SCOPUS:85128754136
T3 - 2022 56th Annual Conference on Information Sciences and Systems, CISS 2022
SP - 66
EP - 71
BT - 2022 56th Annual Conference on Information Sciences and Systems, CISS 2022
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 9 March 2022 through 11 March 2022
ER -