Global network coordination in densified wireless access networks through integer linear programming

Network densification with universal resources reuse is regarded as a possible solution to increase capacity and deal with the “1000x” mobile data challenge in future 3GPP radio access networks. Interference is the major performance limitation is such networks, and global coordination of coexisting transmissions comprises the technology enabler for achieving high performance levels. In this work we consider large distributed networks of low-cost infrastructure nodes, such as small-cells or simply access points. We explore optimal and efficient strategies for selecting the serving access point for each user (access point/user pairing) and tuning the transmission power per communication link, in order to achieve uniform quality-of-service levels across the whole network. For this purpose, we reformulate the original intractable joint pairing and power optimization problem, leveraging the powerful integer linear programming optimization framework. We also propose lower-complexity coordination algorithms by decoupling the pairing and power allocation sub-problems. We evaluate the proposed algorithms performance in large dense access networks and we demonstrate how to guarantee specific rates over increased user population by infrastructure densification and network resources coordination.