Wireless Information And Energy Transfer In Multi-Antenna Systems

Inspired by the green communication trend of next-generation wireless networks, wireless information and energy transfer, which can decode information and harvest energy simultaneous-ly, was proposed and has attracted more and more attention of researchers. On one hand, MIMO combined with WIET can improve the system performance and reduce the energy consumption effectively, which meets the necessity of the develop of communication. On the other hand, co-channel interference has become the bottleneck for the system performance with the increase of wireless terminals and frequency reuse. However, co-channel interference can increase the har-vested energy. Thus, the study of wireless information and energy in interference-limited situation is of great significance.First, this paper exploits the benefit of massive MIMO for wireless information and energy transfer in the presence of external interference, which has two-sided effects, i.e., interfering with the information decoding and benefiting the energy harvesting. As a result, instead of using all antennas, this paper adopt a part of antennas to mitigate the external interference. Especially, this paper partition the antennas into two subsets, one for information decoding and the other for energy harvesting. Thus, there exists a fundamental tradeoff between information decoding and energy harvesting. This paper analyzes the R-E tradeoff in the presence of interference and obtain the achievable R-E regions for massive MIMO with either a ZF or MMSE receiver. Due to the NP-hard property of the antenna partition, a low-complexity algorithm is proposed to maximize the data rate while guaranteeing a minimum harvested energy. Furthermore, this paper introduces a massive MIMO relay into WIET, so as to further improve the performance of two-hop WIET. It is found that the SNR of the low-complexity algorithm is at least an approximable half of the optimal SNR in both the single-hop and two-hop cases.Second, an opportunistic wireless information and energy transfer relaying scheme is pro-posed for sustainable cooperative relaying, in which the relay nodes are powered only by their independent harvested energy to forward the desired information to the destination. Thus there exists an inherent tradeoff between the ID and the EH for forwarding. This paper analyzes the tradeoff and formulates an optimization problem on joint EH/ID receive mode selection and trans-mit power control for the relay nodes. By Lagrangian optimality, the optimal solution in oppor-tunistic relay and power control is obtained. Due to the NP-hard property of the EH/ID mode selection, a low-complexity algorithm is proposed by relaxation for EH/ID mode selection. This paper further investigates the energy cooperation among sustainable cooperative relay nodes. Due to different harvested energy at the relay nodes, effective energy cooperation can benefit the energy efficiency, but suffer from practical energy loss when achieving energy cooperation. By solving the problem using Lagrangian duality, the optimal energy cooperation policy is obtained for the relay nodes and further discuss its two-level waterfilling structure. Then this paper derives the op-timal and low-complexity EH/ID mode selecting algorithm with the two-level waterfilling energy cooperation policy.Lastly, the stochastic geometry is adopted to model wireless information and energy transfer in relay-assisted mobile networks, where there are random pairs of source-destination. The com-munication between source and destination is built by EH-enabled relays, which use PS to decode information and harvest energy simultaneously. Different to the single-source-single-destination situation, the distribution of interference is determined by the policy each relay used. Moreover, the policy is affected by the distribution of the interference in return. To solve this problem, an con-vex optimization is formulated and Lagrangian duality is used. With the proposed power splitting and power allocation algorithm, the optimal relaying strategy is obtained to maximize the network throughput.