Positional Attention-based Graph Neural Network for Learning Permutation Non-equivariant Wireless Policies
This paper proposes a novel positional attention-based GNN to learn permutation nonequivariant policies efficiently, and employs the proposed GNN to learn the policies, where the embedding function is designed based on the channel covariance matrix.