Research On Key Technologies In 5G Millimeter Wave Massive MIMO Communication Systems

With the rapid development of portable broadband mobile devices and the advent of Internet big data era,5g communication system will face higher spectral efficiency,higher data rate,lower delay and other requirements.Millimeter wave(mmWave)band has abundant available bandwidth,which can provide a large number of new spectrum resources to meet the challenges of ultra-high data rate,massive connectivity of massive number of devices and the exponential growth in traffic.However,mm Wave signal communication has huge path loss.To solve this problem,researchers combined millimeter wave technology with massive MIMO technology.Due to the short wavelength of mmWave,the size of its corresponding antenna element is very small,which is conducive to the deployment of large-scale antenna array in the limited physical space.Large scale antenna array can provide enough beam gain to overcome the path loss,and realize the complementary advantages of the two technologies.MmWave massive MIMO mainly uses hybrid precoding technology to combat multipath fading and achieve high spectral efficiency and high energy efficiency.This technology divides the traditional full digital precoding into high-dimensional analog precoding and low-dimensional digital precoding,which greatly reduces the hardware cost and power consumption introduced by the radio frequency links in the system.In this paper,the key technologies of 5G mm Wave massive MIMO communication system are studied.Aiming at improving the spectral efficiency and energy efficiency of the system,this paper proposes a family of spectral-efficient hybrid precoding schemes suitable for rank-deficient channel,and designs an energy-efficient hybrid precoding scheme with a low complexity.Besides,considering the high energy consumption of large-scale users and the computing delay limitation of mobile users in mm Wave communication systems,this paper also studies the power allocation scheme for mm Wave massive MIMO-NOMA system and the resource allocation scheme in mmWave-NOMA system based on mobile edge computing(MEC).The main work of this paper is summarized as follows:1.A family of efficient iterative matrix factorization algorithms for rank-deficient equivalent baseband MIMO channel(EBMC)are proposed.The hybrid precoding designs based on full-rank channel are extended to the rank-deficient channel under poor propagation conditions.Firstly,a hybrid precoding scheme based on a non-sparse baseband matrix design is proposed,which approximates the performance of the fully digital precoder by utilizing an alternate optimization strategy.Secondly,a hybrid precoding scheme based on sparse baseband matrix is proposed by combining the successive interference cancellation technique with the alternate optimization strategy,which can further improve system throughput and reduce computational complexity.Simulation results show that the proposed hybrid precoding scheme based on sparse baseband matrix performs better than other recently proposed hybrid precoding schemes with partially connected structures when the number of data streams equals to the number of radio frequency chains.2.A hybrid precoding structure based on an energy-efficient adaptive switch-inverter network is proposed,which solves the problems of high energy consumption and high cost of phase shifters faced by traditional hybrid precoding structures.Moreover,a multiuser adaptive coordinate update algorithm is proposed for the hybrid precoding design problem of this new structure.Simulation results verify that the proposed design can achieve better energy efficiency than other recently proposed hybrid precoding schemes when the number of users is small.The proposed design can achieve a better trade-off between the system sum-rate and hardware energy consumption.3.An energy-efficient hybrid precoding design and power allocation strategy for the multi-user mm Wave massive MIMO-NOMA system are proposed to maximize the energy efficiency of the system.Specifically,the fully-connected hybrid precoding structure and the partially-connected hybrid precoding structure are considered,respectively.For these two structures,the finite resolution analog precoder is realized through a low-power switches and inverters(SI)network.In the mm Wave massive MIMO-NOMA system,multi-users are first grouped according to their channel correlation and gain difference.On this basis,the hybrid precoding schemes are proposed for the hybrid precoding structures with low-power SI network.Then,a power allocation problem is formulated to maximize the energy efficiency of the system,subject to per-group' power constraints and per-user's QoS constraints.In order to solve the non-convex problem with high-dimensional variables,a sub-optimal solution with a two-stage power allocation strategy is proposed.Simulation results show that the proposed mmWave-NOMA scheme can achieve higher energy efficiency than the existing schemes.4.An energy-efficient hybrid precoding and resource allocation strategy for the mobile edge computing(MEC)network based on millimeter-wave massive MIMO-NOMA is proposed.Edge computing technology is used to offload part of the tasks of mobile devices to the mm Wave massive MIMO base station,reducing the calculation delay and energy consumption of mobile users.Firstly,the computational offloading model of the uplink massive MIMO-MEC network is established,and the energy consumption and offloading delay of the computational offloading in MEC network are analyzed.Then,the uplink hybrid precoding,computing resource allocation and power allocation are jointly designed to minimize the total energy consumption of all mobile users.Considering the NP difficulty of the joint optimization problem,the sum-energy minimization problem is solved in two stages.In the first stage,the analog precoding matrix and the digital precoding matrix of hybrid precoding are designed.In the second stage,the joint optimization problem of computing resource allocation and power allocation is designed to reduce the sum-energy of all mobile users,and an iterative optimization algorithm is proposed to solve the non-convex problem.The simulation results show that the proposed NOMA-based computational offloading scheme significantly improves the energy efficiency of the multi-user MEC system compared with other benchmark schemes.