A Novel Joint Precoding and Association Optimization Framework for C-RANs with Restricted Fronthauls

Joint optimization of associations and precoders in wireless communication networks has become a crucial problem, due to the growing density of network infrastructure and users. Furthermore, network operators continue to show interest in improved energy efficiency and less power consumption. Due to the non-convex structure of the joint optimization problem, current methods and solvers struggle to offer satisfactory solutions. In the present paper, we provide a novel approach for joint optimization of the precoders and associations in a cooperative network with limited fronthaul capacity links. The proposed joint optimization method provides an iterative approximation of the original problem in the form of a mixed integer quadratic program (MIQP), solved via off the shelf numerical solvers. The second contribution of our work is a distributed hybrid association strategy, which serves as an alternative to the joint optimization framework. The performance of both methods is evaluated, suggesting that the proposed joint optimization framework can be used as a benchmark for other heuristic methods, due to its better performance and higher complexity. Meanwhile, the hybrid association strategy is deemed suitable for a distributed implementation in less computationally advanced networks.