An Intelligent Grey Wolf Optimizer Algorithm for Distributed Compressed Sensing

Algorithm 1

DCS-GWO.

Input: The joint sparsity ; the wolf number set ; the limiting parameter ; the stopping criterion .

Initialization: Initialize the wolf’s position by using the Eq. (16); Initialize the best three positions by

, , ;

the iteration number ; the allowed maximum iterations number .

Judgement: if  , set , output the joint signal by using the Eq. (13) and stop. Otherwise, go to the iteration.

Iteration:

Step 1. Update all wolves’ positions  :

Step 1.1. Define .

Step 1.2. If , randomly choose elements from to forma set and define

. If , randomly choose elements from to form a set

and define .

Step 1.3. Use the least square method to estimate a temporary solution by using the Eq. (17).

Step 1.4. Update the wolf’s position by using the Eq. (18).

Step 2. Update the best three wolves’ positions: , ,

.

Step 3. Check the terminate criterion: If or , set the final joint support set and terminate

the iteration. Otherwise, set and go to the next iteration.

Output: Estimate the joint signal by using the Eq. (13).