Multicell cooperative processing with limited backhaul traffic is studied for cellular uplinks. Aiming at reduced backhaul overhead, a sparse multicell linear receive-filter design problem is formulated. Both unstructured distributed cooperation and clustered cooperation, in which base station groups are formed for tight cooperation, are considered. Dynamic clustered cooperation, where the sparse equalizer and the cooperation clusters are jointly determined, is solved via alternating minimization based on spectral clustering and group-sparse regression. Furthermore, decentralized implementations of both unstructured and clustered cooperation schemes are developed for scalability, robustness, and computational efficiency. Extensive numerical tests verify the efficacy of the proposed methods.
Bibliographical noteFunding Information:
This work was supported in part by the NSF grants 1247885, 1343248, 1423316, 1442686, 1508993, 1509040; and ARO grant W911NF-15-1-0492.
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- Coordinated multi-point
- decentralized algorithms
- multicell cooperation