Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-05-20 Cooperative journals: 《计算机应用研究》
Abstract： Research on energy efficiency optimization of simultaneous wireless information and power transfer in heterogeneous small cellular networks. In order to maximize the energy efficiency of the downlink cellular system by jointly designing transmit beamforming vector and receive power splitting ratio under both small cellular users' communication quality and the collected energy, and the transmission power of the small cell base station constraints. The problem belongs to the nonconvex optimization problem, and the equivalent problem is transformed by the variable substitution, and then the subgradient iteration algorithm based on the Lagrange multiplier is used to solve the problem. The results of computer simulation show that the joint optimization algorithm is simple and effective.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-05-02 Cooperative journals: 《计算机应用研究》
Abstract： This paper investigated an energy-efficient optimization of massive MIMO systems with energy harvesting. The power beacon’s transmit power and energy harvesting time were jointly optimized to maximize the energy efficiency of the uplink massive MIMO systems under the quality of service (QoS) , the power beacon’s transmit power and energy harvesting time constraints. Because the problem was the non-convex optimization problem, it was first transformed to the equivalent optimization problem by fractional programming theory. Then, an energy-efficient power and time allocation algorithm (EPTA) was proposed based on the block coordinate descent (BCD) method to find the power of the power beacon, energy harvesting time and energy efficiency of the system iteratively. Compared with time averaged minimum QoS guaranteed algorithm (TA-QoSA) and throughput maximization based power and time algorithm (TPTA) , the simulation results show that the proposed algorithm improves the energy efficiency of the system under the guarantee of user’s QoS.
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