Joint Optimization of Computation and Communication Power in Multi-User Massive MIMO Systems - 2018


With the growing interest within the deployment of massive multiple-input-multiple-output (MIMO) systems and millimeter wave technology for fifth generation wireless systems, the computation power to the whole power consumption ratio is predicted to increase rapidly because of high information traffic processing at the baseband unit. Therefore in this Project, a joint optimization drawback of computation and communication power is formulated for multi-user large MIMO systems with partially-connected structures of radio frequency (RF) transmission systems. When the computation power is taken into account for large MIMO systems, the results of this Project reveal that the energy efficiency of large MIMO systems decreases with increasing the quantity of antennas and RF chains, which is contrary with the conventional energy efficiency analysis results of massive MIMO systems, i.e., only communication power is considered. To optimize the energy potency of multi-user huge MIMO systems, an higher certain on energy efficiency comes. Considering the constraints on partially-connected structures, a suboptimal solution consisting of the baseband and RF precoding matrices is proposed to approach the higher bound on energy potency of multi-user huge MIMO systems. Furthermore, an optimized hybrid precoding with computation and communication power algorithm is developed to appreciate the joint optimization of computation and communication power. Simulation results indicate that the proposed algorithm improves energy and price efficiencies and the maximum power saving is achieved by 76.fifty nine% for multi-user large MIMO systems with partially-connected structures.

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