Backhaul-constrained multi-cell cooperation using compressive sensing and spectral clustering

Multi-cell cooperative processing with limited backhaul traffic is considered for cellular uplinks. To parsimoniously select a set of cooperating base stations, a sparse multi-cell receive-filter is obtained through convex optimization using compressive sensing techniques. Clustered cooperation is also considered, where sparsity is promoted on inter-cluster feedback. A joint equalizer design and dynamic partitioning problem is formulated and solved using an iterative spectral clustering approach. Numerical tests verify the efficacy of proposed methods.