  The uplink sum-throughput of distributed massive
multiple-input-multiple-output (mMIMO) networks depends majorly on Access point
(AP)-User Equipment (UE) association and power control. The AP-UE association
and power control both are important problems in their own right in distributed
mMIMO networks to improve scalability and reduce front-haul load of the
network, and to enhance the system performance by mitigating the interference
and boosting the desired signals, respectively. Unlike previous studies, which
focused primarily on addressing these two problems separately, this work
addresses the uplink sum-throughput maximization problem in distributed mMIMO
networks by solving the joint AP-UE association and power control problem,
while maintaining Quality-of-Service (QoS) requirements for each UE. To improve
scalability, we present an l1-penalty function that delicately balances the
trade-off between spectral efficiency (SE) and front-haul signaling load. Our
proposed methodology leverages fractional programming, Lagrangian dual
formation, and penalty functions to provide an elegant and effective iterative
solution with guaranteed convergence. Extensive numerical simulations validate
the efficacy of the proposed technique for maximizing sum-throughput while
considering the joint AP-UE association and power control problem,
demonstrating its superiority over approaches that address these problems
individually. Furthermore, the results show that the introduced penalty
function can help us effectively control the maximum front-haul load.
