TY - GEN
T1 - Joint User Identification and Channel Estimation in Massive Connectivity with Transmission Control
AU - Sun, Zhuo
AU - Wei, Zhiqiang
AU - Yang, Lei
AU - Yuan, Jinhong
AU - Cheng, Xingqing
AU - Wan, Lei
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - In this paper, we propose a transmission control scheme and design an approximate message passing (AMP) algorithm for the joint user identification and channel estimation (JUICE) in massive connectivity networks. In the proposed transmission control scheme, a transmission control function is designed to determine a user's transmission probability, when it has a transmission demand. By employing a step transmission control function for the proposed scheme, we derive the channel distribution experienced by the receiver to characterize the effect of transmission control on the design of AMP algorithm. Based on that, we propose a minimum mean squared error denoiser and design the AMP algorithm. We demonstrate that the proposed scheme can significantly improve the JUICE performance and reduce the average delay, compared to the conventional scheme without transmission control.
AB - In this paper, we propose a transmission control scheme and design an approximate message passing (AMP) algorithm for the joint user identification and channel estimation (JUICE) in massive connectivity networks. In the proposed transmission control scheme, a transmission control function is designed to determine a user's transmission probability, when it has a transmission demand. By employing a step transmission control function for the proposed scheme, we derive the channel distribution experienced by the receiver to characterize the effect of transmission control on the design of AMP algorithm. Based on that, we propose a minimum mean squared error denoiser and design the AMP algorithm. We demonstrate that the proposed scheme can significantly improve the JUICE performance and reduce the average delay, compared to the conventional scheme without transmission control.
UR - https://www.scopus.com/pages/publications/85062417402
U2 - 10.1109/ISTC.2018.8625352
DO - 10.1109/ISTC.2018.8625352
M3 - 会议稿件
AN - SCOPUS:85062417402
T3 - International Symposium on Turbo Codes and Iterative Information Processing, ISTC
BT - 2018 IEEE 10th International Symposium on Turbo Codes and Iterative Information Processing, ISTC 2018
PB - IEEE Computer Society
T2 - 10th IEEE International Symposium on Turbo Codes and Iterative Information Processing, ISTC 2018
Y2 - 3 December 2018 through 7 December 2018
ER -