TY - JOUR
T1 - Message-Passing Receiver Design for Joint Channel Estimation and Data Decoding in Uplink Grant-Free SCMA Systems
AU - Wei, Fan
AU - Chen, Wen
AU - Wu, Yongpeng
AU - Ma, Jun
AU - Tsiftsis, Theodoros A.
N1 - Funding Information:
Manuscript received January 29, 2018; revised July 12, 2018; accepted October 22, 2018. Date of publication November 6, 2018; date of current version January 8, 2019. This work was supported in part by NSF, China, under Grant 61671294 and Grant 61701301, in part by the National Major Project under Grant 2017ZX03001002-005 and Grant 2018ZX03001009-002, in part by Shanghai Kewei under Grant 616JC1402900 and Grant 17510740700, in part by NSF Guangxi under Grant 2015GXNSFDA139003, and in part by the Guangxi Key Laboratory of Automatic Detecting Technology and Instruments under Grant YQ14115. This paper was presented in part at the IEEE GLOBECOM Workshops, Singapore, 2017. The associate editor coordinating the review of this paper and approving it for publication was R. Tandon. (Corresponding author: Wen Chen).
PY - 2019/1
Y1 - 2019/1
N2 - The conventional grant-based network relies on the handshaking between the base station and active devices to achieve dynamic multi-user scheduling, which may result in large signaling overheads as well as system latency. To address those problems, a grant-free receiver design is considered in this paper based on sparse code multiple access (SCMA), one of the promising air interface technologies for 5G wireless networks. With the presence of unknown multipath fading, the proposed receiver performs joint channel estimation and data decoding without knowing the user activity in the network. Formulating a factor graph representation for the problem, we devise a message-passing receiver for the uplink SCMA that performs joint estimation iteratively. Motivated by the idea of approximate inference, we use expectation propagation to project the intractable distributions into Gaussian families such that a linear complexity decoder is obtained. The simulation results show that the proposed receiver can detect active devices in the network with a high accuracy and can achieve an improved bit-error-rate performance compared with existing methods.
AB - The conventional grant-based network relies on the handshaking between the base station and active devices to achieve dynamic multi-user scheduling, which may result in large signaling overheads as well as system latency. To address those problems, a grant-free receiver design is considered in this paper based on sparse code multiple access (SCMA), one of the promising air interface technologies for 5G wireless networks. With the presence of unknown multipath fading, the proposed receiver performs joint channel estimation and data decoding without knowing the user activity in the network. Formulating a factor graph representation for the problem, we devise a message-passing receiver for the uplink SCMA that performs joint estimation iteratively. Motivated by the idea of approximate inference, we use expectation propagation to project the intractable distributions into Gaussian families such that a linear complexity decoder is obtained. The simulation results show that the proposed receiver can detect active devices in the network with a high accuracy and can achieve an improved bit-error-rate performance compared with existing methods.
KW - SCMA
KW - expectation propagation
KW - grant-free
KW - joint channel estimation and data decoding
KW - user activity detection
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U2 - 10.1109/TWC.2018.2878571
DO - 10.1109/TWC.2018.2878571
M3 - Article
AN - SCOPUS:85056299613
VL - 18
SP - 167
EP - 181
JO - IEEE Transactions on Wireless Communications
JF - IEEE Transactions on Wireless Communications
SN - 1536-1276
IS - 1
M1 - 8525421
ER -