Key Technology Research In Heterogeneous Network With Massive MIMO

Potential key technologies in the next generation wireless communication system may include Massive MIMO,heterogeneous network,full duplex,millimeter wave,and so on.In this paper,we mainly investigate the beamforming technology in heterogeneous network with Massive MIMO.The optimization objectives contain two aspects,which are energy efficiency and physical layer security,respectively.The beamforming design strategy is firstly investigated to optimize the energy efficiency in the scenario where the macro base station is configured with Massive MIMO,while dense small cells are deployed in the macro cell.The beamforming method for improving energy efficiency is studied from two aspects: minimizing the system power consumption and maximizing the users' sum rate.The first part studies the optimization problem of minimizing the system power consumption with the requirements of quality of service.This optimization problem was transformed into a convex optimization problem.In the second part,the optimization problem of maximizing users' sum rate is studied with the total consumption power constraint.This problem is transformed into the form of geometric programming by approximation method,which could be solved by the iteration method.Then,in the Massive MIMO scenario with the existence of eavesdroppers,the physical layer secure capacity is optimized through beamforming.The macro base station is configured with Massive MIMO and each legitimate user is wiretapped by an eavesdropper.The secrecy rate is defined as the difference between the rate of the legitimate user and the rate of its corresponding eavesdropper.The optimization objective is to maximize the sum of all users' security rates by beamforming design.The original problem is transformed into a convex optimization problem through the approximation method based on semi-definite positive relaxation and Taylor expansion.The sum secrecy rate performance can be enhanced by the iterative method.The convergence of the iterative scheme is proved,and the simulation results verify the effectiveness of the proposed algorithm.A sub-optimal power allocation scheme with low complexity is also proposed in this paper.