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Large-scale distributed antenna systems with many access points (APs) thatserve the users by coherent joint transmission is being considered for5G-and-beyond networks. The technology is called Cell-free Massive MIMO and canprovide a more uniform service level to the users than a conventional cellulartopology. For a given user set, only a subset of the APs is likely needed tosatisfy the users' performance demands, particularly outside the peak traffichours. To find achieve an energy-efficient load balancing, we minimize thetotal downlink power consumption at the APs, considering both the transmitpowers and hardware dissipation. APs can be temporarily turned off to reducethe latter part. The formulated optimization problem is non-convex but,nevertheless, a globally optimal solution is obtained by solving amixed-integer second-order cone program. Since the computational complexity isprohibitive for real-time implementation, we also propose two low-complexityalgorithms that exploit the inherent group-sparsity and the optimized transmitpowers in the problem formulation. Numerical results manifest that ouroptimization algorithms can greatly reduce the power consumption compared tokeeping all APs turned on and only minimizing the transmit powers. Moreover,the low-complexity algorithms can effectively handle the power allocation andAP activation for large-scale networks.

Joint Power Allocation and Load Balancing Optimization for Energy-Efficient Cell-Free Massive MIMO Networks