摘要
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. A time slotted transmission pattern is consid- ered. 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 op- timization 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.
基金
supported in part by National Natural Science Foundation of China (61372070)
Natural Science Basic Research Plan in Shaanxi Province of China (2015JM6324)
Ningbo Natural Science Foundation (2015A610117)
Hong Kong, Macao and Taiwan Science & Technology Cooperation Program of China (2015DFT10160)
the 111 Project (B08038)
