Khairullah,A.K.Tureli,U.Kivanc,D.Mekatronik / Mechatronics2024-05-252024-05-2520200978-172818233-910.1109/IT-ELA50150.2020.92530982-s2.0-85097780799https://doi.org/10.1109/IT-ELA50150.2020.9253098https://hdl.handle.net/20.500.14517/2515Distributed Joint beamforming and power adaptation algorithms are of interest for MIMO ad hoc networks. Cooperative and non-cooperative games have been presented to decrease interference (mutual) at each sensor node, under receiver signal-to-interference and noise (SINR) constraints. In reduced feedback algorithms, the optimum transmitter node beamformer is selected from a predefined codebook. This paper introduces a cooperative optimal beamformer selection algorithm to minimize the total power consumption for cluster-based network topology under different minimum SINR constraints. The algorithm reduces overhead incurred by 48% and 10% while increasing the convergence rate to the steady-state allocation by 17% and 9% for the cooperative and non-cooperative beamformer selection games, respectively. Simulation results verify the proposed theoretical analysis, and demonstrate the performance of the Enhanced Co-Operative Power Minimization Algorithm (ECOPMA), Reinforcement Learning based Power allocation and Beamformer Algorithm (RLPBA) for the non-cooperative game [1], with state of the art methods and centralized (optimal) solutions as a fair benchmark. © 2020 IEEE.eninfo:eu-repo/semantics/closedAccessBeamformingMIMO Ad hoc networkOverhead RatePotential GameReinforcement LearningSINRConference Object127131