A Decentralized Optimization Approach to Backhaul-Constrained Distributed Antenna Systems

It has been shown that multi-cell co-operations in cellular networks, enabling distributed antenna systems and joint signal processing across cell boundaries, can significantly increase system capacity and fairness. In recent work on this topic, we have proposed an optimization framework and algorithm that applies joint detection in the uplink or joint transmission in the downlink, respectively, to only a selected subset of users. This already yields a large extent of capacity and fairness improvements, while requiring only comparatively small backhaul capacity between co-operating base stations, which is usually the main issue connected to distributed antenna systems. In the following paper, we will introduce a novel concept of partitioning a cellular network and its resources into small subsystems, within which the optimization algorithm can be applied in a decentralized way. While each subsystem requires only very limited system knowledge, and joint detection and transmission is constrained to within subsystems, the performance improvements are still promising and approach those of a centralized optimization scheme in scenarios of strongly constrained backhaul.