Power Allocation for Wireless Powered MIMO Transmissions with Non-Linear RF Energy Conversion Models

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We study a radio frequency(RF) wireless energy transfer(WET) enabled multiple input multiple output(MIMO) system. A time slotted transmission pattern is considered. Each slot can be divided into two phases, downlink(DL) WET and uplink(UL) wireless information transmission(WIT). Since energy conversion efficiency of the energy harvesting circuits are non.linear, the conventional linear model leads to a mismatch for resource allocation. In this paper, the power allocation algorithm considering the practical non.linear energy harvesting circuits is studied. The optimization problem is formulated to maximize the energy efficiency of system with multiple constraints, i.e., the transmission power, the received power and the minimum harvested energy, which is a non.convex problem. We transform the objective function from fractional form into an equivalent objective function in subtractive form and provide an iterative power allocation algorithm to achieve the optimal solution. Numerical results show that our proposed algorithm with the non.linear RF energy conversion models can achieve much better performance than the algorithm with the conventional linear model. We study a radio frequency (RF) wireless energy transfer (WET) enabled multiple input multiple output (MIMO) system. Each slot can be divided into two phases, downlink (DL) WET and uplink Since energy conversion efficiency of the energy harvesting circuits are non. linear, the conventional linear model leads to a mismatch for resource allocation. In this paper, the power allocation algorithm considering the practical non. linear energy harvesting circuits is studied. The optimization problem is formulated to maximize the energy efficiency of the system with multiple constraints, ie, the transmission power, the received power and the minimum harvested energy, which is a non .convex problem. form into an equivalent objective function in subtractive form and provide an iterative power allocation algorithm to achieve the optimal solution. Numerical resul ts show that our proposed algorithm with the non. linear RF energy conversion models can achieve much better performance than the algorithm with the conventional linear model.
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