Compressed Sensing based ACK Feedback for Grant-Free Uplink Data Transmission in 5G mMTC

One of the three 5G key usage scenarios is massive machine type communication (mMTC), which is characterized by a very large number of connected devices typically transmitting a relatively low volume of non-delay sensitive data. To support the above mMTC communication, grant-free data transmission (GFDT) has been proposed, where mMTC devices have no dedicated transmission resource. One of the challenges faced by GFDT is to ensure the communication reliability, which can be enhanced by efficient acknowledgement (ACK) feedback. By exploiting the sparsity of user activity in mMTC, this paper proposes a compressed sensing based ACK feedback (CSAF) scheme for GFDT, to reduce the feedback signaling overhead. Furthermore, we propose a new CS recovery algorithm, named as regularized approximate message passing (RAMP), to improve the detection performance of CSAF in low SNR scenario. Simulation results show that, compared with the traditional method, the proposed CSAF scheme with the proposed RAMP algorithm reduces the feedback signaling overhead by up to 75.6% and has up to 3dB detection performance gain.