Research On Wireless Channel Prediction Algorithm Based On Quantum Singular Value Estimation Method

Since the beginning of the 21 st century,the research on quantum computing has attracted wide attention.The advantages of quantum computing have enabled many scholars to apply it to various fields in the information age.Quantum computation can effectively improve the efficiency of classical algorithms.Recently,researchers have applied quantum computing to the field of traditional communication and realized the classical communication signal processing method with lower time complexity.So there is a new implementation scheme in the field of wireless communication based on quantum computing.In this paper,we first study the basic principles of quantum mechanics,three kinds of quantum gates: single quantum gate,controlled quantum gate and universal quantum gate,the graphic representation of the quantum circuit and the difference from the classic circuit diagram are analyzed.Several basic quantum algorithms and their corresponding circuit diagrams are also studied,including Hamiltonian simulation,quantum Fourier transform,phase estimation and quantum swap test.These studies are the theoretical basis of the algorithms for channel prediction in wireless communication systems.In the following research,the classical channel prediction algorithm is implemented in quantum computing,which uses the characteristics of quantum superposition state and quantum high parallelism computing to accelerate the channel prediction algorithm in time,and the prediction performance is consistent with the classical algorithm.Then,aiming at the problem of high computational complexity of channel prediction algorithm in classical wireless communication systems,a quantum ELM algorithm based on quantum singular value estimation algorithm is proposed.The thesis studies the extreme learning machine algorithm and the applicable channel model.Then we studied the memory model of binary tree data.And quantum singular value estimation algorithm.And quantum singular value estimation algorithm.This paper mainly applies the principle and procedure of the quantum singular value estimation algorithm,and analyzes the performance and complexity of the algorithm.Finally,the ELM channel prediction algorithm based on quantum computing is proposed and the specific steps are given and the time complexity of the algorithm is analyzed.Aiming at the problem of high computational complexity of AR channel prediction algorithm in wireless communication system,this paper proposes a wireless channel AR prediction algorithm based on quantum computation,that is quantum autoregressive model channel prediction algorithm.The channel prediction algorithm of quantum autoregressive model proposed in this paper optimizes the high complexity part of AR algorithm through quantum linear system algorithm.In this paper,we first apply the quantum singular value estimation algorithm to the quantum linear system algorithm,thus avoiding the necessary conditions for other quantum linear system algorithms.Then the proposed quantum linear system is applied to AR channel prediction algorithm.Finally,the principle and steps of quantum linear system algorithm and quantum AR prediction algorithm are studied.The performance and complexity of the algorithm are analyzed and the time complexity of the algorithm is compared.Compared with classical algorithms,quantum algorithms can perform polynomial-level acceleration,and under certain conditions,they can have exponential acceleration.Therefore,compared with classical algorithms,quantum algorithms have a significant reduction in complexity without loss of algorithm performance.