  Orthogonal time frequency space (OTFS) has emerged as the most sought-after
modulation technique in a high mobility scenario. Sparse code multiple access
(SCMA) is an attractive code-domain non-orthogonal multiple access (NOMA)
technique. Recently a code-domain NOMA approach for OTFS, named OTFS-SCMA, is
proposed. OTFS-SCMA is a promising framework that meets the demands of high
mobility and massive connectivity. This paper presents a channel estimation
technique based on the convolutional sparse coding (CSC) approach for OTFS-SCMA
in the uplink. The channel estimation task is formulated as a CSC problem
following a careful rearrangement of the OTFS input-output relation. We use an
embedded pilot-aided sparse-pilot structure that enjoys the features of both
OTFS and SCMA. The existing channel estimation techniques for OTFS in
multi-user scenarios for uplink demand extremely high overhead for pilot and
guard symbols, proportional to the number of users. The proposed method
maintains a minimal overhead equivalent to a single user without compromising
on the estimation error. The results show that the proposed channel estimation
algorithm is very efficient in bit error rate (BER), normalized mean square
error (NMSE), and spectral efficiency (SE).
