  Recently, a novel coded compressed sensing (CCS) approach was proposed in [1]
for dealing with the scalability problem for large sensing matrices in massive
machine-type communications. The approach is to divide the compressed sensing
(CS) problem into smaller CS sub-problems. However, such an approach requires
stitching the results from the sub-problems to recover the result in the
original CS problem. For this stitching problem, we propose a hierarchical
stitching algorithm that is easier to implement in hardware for parallelization
than the tree coding algorithm in [1]. For our algorithm, we also derive an
upper bound on the probability of recovery errors.
