Pre-Decoding Design And Energy Efficiency Research Based On Energy Harvesting In Multi-User MIMO System

Energy harvesting is one of the key technologies to solve the energy consumption problem and achieve Green Communication. With energy supplied from energy harvesting, not only does it reduce traditional energy consumption, for some battery unchangeable equipment, it also improves system stability. Multiple-Users Multiple-Input and Multiple-Output technology can effectively improve the utilization of system space and spectrum resources, and enhance the reliability of the transmission link. Researching the system that combines these two technologies has profound practical significance to the development of wireless communication. In view of this, this paper mainly discusses the pre-coding algorithm and energy efficiency optimization problem based on two kinds of EH MU-MIMO systems, wireless ad hoc network and cognitive radio networks around two core points of energy harvesting and system throughput. Two aspects as follow constitute our main content:(1) Pre-coding design in wireless Ad Hoc network: All users in system are equipped with multi antennas, and have an opportunity relay, the more energy harvested, the more to help the source node forwarding information. Under the premise of source node's rate limited, the relay uses the remaining energy for its own information transmission. Since there are multi users at the terminal, in order to make sure the user can decode their own information, pre-coding design needed at the transmitter. This paper designs an optimal beamforming matrix and uses semidefinite relaxation(SDR) algorithm to solve the optimal problem, to maximize the system rate. Taking into account the optimal solution with a high degree of complexity, we design two suboptimal pro-coding programs which are called singular value decomposition and block diagonalization for comparison the performance. Through simulation, optimization and suboptimal solutions were compared in performance.(2) Energy efficiency optimization in cognitive radio network: Cognitive users are worked under underlay spectrum access mode. The cognitive users harvest energy form base station and hybrid access point in the first slot. Under the premise of interference below the restricted areas where are required by main users, in the second slot, cognitive users transmit signals with the harvested energy. In order to meet all the communication demands of users, and energy use efficiency can be maximized. We proposed an energy cooperation program for each cognitive users. With KKT conditions and water-filling algorithm to get the optimum transmission power for each cognitive user, that all the cognitive users will meet their minimum rate requirement, and improving system energy efficiency and throughput. The simulation demonstrates the energy cooperation strategy can improve the system performance effectively.