机译:Prior Information Aided Deep Learning Method for Grant-Free NOMA in mMTC
State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University (BJTU), Beijing, China;
Computer Laboratory, University of Cambridge, Cambridge, GB, U.K.;
Channel estimation; Receivers; NOMA; Multiuser detection; Artificial neural networks; Safety; Rails; Deep learning; massive machine-type communication; massive access; compressive sensing;