| Summary |
In the unsourced random access (U-RA), only a portion of users in a large number of users are active during the same time slot. Each user employs the same codebook, and the task of the decoder is to recover a list of transmitted messages, regardless of the user's identity. A concatenated coding approach, referred to as a coded compressed sensing scheme, decreases the computational complexity. However, there is a limitation that the inner CS decoding only decodes the support of a sparse vector, which leads to each user at the same sub-slot must send a different message, and the maximum tolerable active user number is low. In this paper, we consider an inner CS decoding scheme that initially decodes the amplitudes of a sparse vector and quantifies them to determine the number of active users choosing the same columns. This eliminates the constraint of requiring each user to send different messages in the same sub-slot, thereby increasing the maximum tolerable number of active users. We also show the maximum tolerable active user number with various codelengths. Next, we improve the survival probabilities' upper and lower bounds of the outer tree encoder. |
