Low Complexity Distributed Game for Joint Power and Beamforming Selection in MIMO Ad Hoc Network

Recently, joint beamforming and power adaptation algorithms have received interest in MIMO Ad hoc networks. Cooperative and non-cooperative games have been suggested with a view to minimize mutual interference within each node, under receiver Signal-to-Interference and Noise Ratio (SINR) constraint. The optimum transmit beamformers can be chosen through a predefined codebook in order to decrease the entire power, by using a cooperative fashion (Potential game), for cluster-based-Network topology. Thus, Bit Error Rate (BER) and power can be minimized and convergence rate can be increased (the steady-state spot i.e. Nash Equilibrium) of beamformer games to enhance the whole system performance (i.e. Data Rate), can be guaranteed throughout the iterations, taking into account the receiver nodes minimum requirement QoS (SINR threshold) in intelligent system computational design. The presented simulation results verify theoretical analysis and prove the Enhancement of the Co-Operative Power Minimization Algorithm (ECOPMA) for cooperative game, Reinforcement Learning based Power allocation and Beamformer Algorithm (RLPBA) for non-cooperative one, with its efficient power adjustment and optimal beamforming selection, will have less overhead rate and BER in comparison with the previous methods (beamforming selection and power adaption techniques) for cooperative and non-cooperative game-theoretical approach and the centralized (optimal) solutions in small-scale Ad hoc node pairs.