Research On Precoding Technology For Millimeterwave Mobile Communication Systems Combined With Quantum Computing

Quantum computing,due to its high parallelism,can reduce the complexity of classical algorithms and maintain consistent computational accuracy compared to classical algorithms.It has become a key research direction both domestically and internationally.Quantum computing has applications in various fields and has quantum advantages.This thesis mainly combines quantum computing technology to design precoding schemes for millimeter wave large-scale Multiple Input Multiple Output(MIMO)systems.Firstly,two digital precoding schemes combining quantum computing in millimeter wave large-scale MIMO systems were proposed.First,combined with the digital precoding scheme of the variable component sub eigenvalue solver,the problem is transformed into the expectation of solving the system’s Hamiltonian and its corresponding Quantum state by using the variational quantum eigenvalue solver with the goal of maximizing the system’s reachability and speed,and a parametric trial wave function is prepared on the Quantum machine learning platform,and then combined with the optimization algorithm of classical machine learning,A set of optimal parameters is trained to update the parameterized Quantum circuit,so that the intrinsic Quantum state can be obtained,and then the optimal precoding matrix can be obtained through measurement.Secondly,in combination with the digital precoding scheme of the Harrow Linear system(HHL)algorithm,in order to solve the high complexity problem of traditional zero forcing precoding due to the pseudo inverse operation of the channel matrix in large-scale MIMO,this scheme combines the part with high computational complexity with quantum computing,and uses the high parallelism of quantum computing to reduce the computational complexity.After verification and analysis,the proposed digital precoding scheme has exponential acceleration and similar performance compared to classical algorithms,but has computational complexity advantages.Secondly,a hybrid precoding scheme combining variational quantum singular value estimation(VQSVD)algorithm is proposed for a partially connected millimeter wave large-scale MIMO system.First,the scheme aims to maximize the equivalent channel gain to obtain the optimal analog precoding matrix.Then,in the digital precoder part,an improved algorithm combined with the variational quantum singular value estimation algorithm is proposed,which transforms the Singular value decomposition into an optimization problem,which is trained by the quantum classical hybrid optimizer to obtain the hybrid precoding matrix.After analyzing the complexity of the algorithm,the proposed hybrid precoding scheme combined with the variational quantum singular value estimation algorithm has lower complexity.This paper verifies and analyzes the proposed algorithm and the classical algorithm on Google’s tensorflow quantum Quantum machine learning platform,and the precoding scheme proposed in this paper has certain performance advantages over the classical algorithm.