Message Passing Based Channel Estimation, User Activity Detection and Multi-User Detection for Grant-Free NOMA

Non-orthogonal multiple access (NOMA), where a resource block is used to serve multiple users, is considered a promising technology to meet the needs of massive access in massive machine type communications (mMTC) scenario. The handshaking between access point and active users in the conventional grant-based network leads to large signaling overhead and high transmission latency, which are unacceptable in mMTC as the communication becomes inefficient due to the small amount of payload data. Therefore, grant-free transmission without handshaking procedure is highly desirable. In grant-free NOMA systems, the handshaking procedure is not required to establish wireless transmission link, and users can send signals to the access point randomly in a period of time, so the access point does not know which users are active before data detection. The major tasks for the access point of the system includes user activity detection, channel estimation and data detection of active users. The objective of this thesis is to provide insights on the receiver design of grant-free NOMA systems, where iterative receivers based on factor graph and hybrid message passing algorithms are designed to realize joint channel estimation, user activity detection and/or multi-user data detection.