Towards Load-Balanced Clustered Cell-Free Networking: A Tight Relaxation Approach

Clustered cell-free networking that dynamically decomposes a network into multiple subnetworks is emerging as a promising solution to the cell-edge problem in mobile communication systems. Maximizing the minimum subnetwork sum ergodic capacity is of great importance for balancing the loads of different subnetworks. Such a load-balanced clustered cell-free networking problem was proposed recently, yet still lacks efficient algorithms due to its complicated objective function and combinatorial nature. Recognizing these challenges, this paper proposes a tight relaxation method to equivalently transform the original problem into a continuous one that shares the same optimal solution. The relaxed problem is a nonconvex-linear minmax problem, which can be solved by finding its Nash equilibrium. We then propose an alternating gradient projection (AGP) algorithm to effectively tackle it, with a guaranteed convergence. Simulation results show that our approach significantly outperforms the existing benchmarks.