Transceiver Optimization For Simultaneously Wireless Information And Power Transfer In Large Scale MIMO

Nowadays, large scale MIMO technology play a key role in next generation of wireless communication system (5G) which are supported by industry. Meanwhile there exists a contradiction between the significant progress of mobile devices’ performance and experience and the obvious battery life dilemma under traditional chemical structure. So system capacity and battery life becomes the two consideration for5G. In this paper, we study the transceiver optimization algorithm of simultaneously wireless information and power transfer. Detailed study items are depicted as below:1. Multi-Input-Multi-Output(MIMO) technologies and precoding metrics. The basic system model, channel characters and benefits of large scale MIMO are analyzed.2. Transceiver design of SWIFT system with global optimization. With several information devices(ID) and single energy harvest(EH) units, our transceiver could optimized system capacity while satisfies energy harvesting request. The fundamental idea is to utilize an equivalent transform of target function to a weighted MMSE problem which could be solved by convex theory and iteration method. We combine the constraint sets into one formation to obtain a low complexity, linear search suboptimal solution.3. The SWIPT transceiver design of multi ID and multi EH are studied. With two new ideas namely energy charging precoding matrix and virtual sectors, the multi EH situation is transformed to weighted MMSE optimization problem under multi virtual cells environment. Simulation results prove that such design could achieve a good performance under large scale MIMO system. For a massive MIMO system with many ID, a user selection scheme is designed to allocate UE to virtual cells effectively with low complexity.4. The system simulation platform is constructed and our proposed algorithm above is verified seriously.