From: 60 GHz ultra-wideband channel estimation based on a cluster sparsity compressed sensing
Step | Description/instruction |
---|---|
A | Cluster identification |
B | Cluster-based classification |
C | If sparsity of primary cluster is greater than threshold, go to step E, otherwise go to step D |
D | Extract the primary cluster as the first classification and the rest as the second part, go to F |
E | Extract the primary cluster and the second cluster as the first classification and the rest as the second part, go to F |
F | Reconstruction |
Input measurement vector h ∈ □N; sparsity K | |
Initialize index set Λ = ∅; and the residual error r = h. Repeat the following steps by K times or until |Λ| ≥ 2K | |
Select the maximum K nonzero values from measurement matrix u = Φr and insert into index set j | |
Regularization: let all subset j 0 ⊂ j for all k, l ∈ j 0 satisfy u(k)| ≤ 2|u(l)|. Then select the index set with a maximum energy as j0 | |
Update: add subset j 0 to index set: Λ ← Λ ∪ j 0 ,update the residual error r: | |
, r = h − Φy | |
If the iteration number is greater than K or the number of indexes is greater than 2 K, stop the iteration, otherwise continue the iteration | |
Index set: Λ ⊆ {1, … d}, then reconstruct the signal estimate as | |
G | Signal synthesis |