Secure Massive MIMO network resource configuration method

Abstract

The invention discloses a secure Massive MIMO (Multiple Input Multiple Output) network resource allocation method. The method comprises the following steps: establishing a communication system model; initializing a quantum bald eagle group, obtaining the position of the quantum bald eagle according to a mapping rule, calculating the fitness, and selecting a global optimal quantum position; updating the quantum position of the quantum bare eagle group according to a search evolution rule; updating the quantum position of the quantum bare eagle group through circling evolution; updating the quantum position of the quantum bald eagle group according to a diving rule, obtaining the updated quantum bald eagle position through a mapping rule, calculating the fitness, and updating the global optimal quantum position of the quantum bald eagle group; if the number of iterations is smaller than the maximum number of iterations, returning to the step 3; otherwise, stopping iteration, outputting the global optimal quantum position of the quantum bald eagle group, obtaining the position according to a mapping rule, and obtaining a network resource configuration scheme. According to the method, the resource utilization rate of the system is improved, and the secrecy capacity of the Massive MIMO system is greatly improved.

Description

technical field [0001] The invention relates to a safe Massive MIMO network resource configuration method, in particular to a safe Massive MIMO network resource configuration method based on an intelligent reflection surface, and belongs to the technical field of Massive MIMO safe communication. Background technique [0002] Massive MIMO technology can serve large traffic, high reliability, and low-latency data transmission scenarios, and is an important way to realize 6G communication of the Internet of Everything in the future. However, with the continuous development of wireless communication technology, the access of a large number of smart devices has brought problems such as high operating costs, excessive energy consumption, and uneven network coverage to the communication system. As an emerging cooperative communication method, Intelligent Reflecting Surface (IRS) can adaptively adjust the phase shift of the incident signal to change the reflection transmission gain,...

AI Technical Summary

Problems solved by technology

For Massive MIMO communication scenarios based on intelligent reflective surfaces, Boyu Ning et al published "Terahertz Multi-UserMassive MIMO With Intelligent Reflecting" in "IEEE Transactions on Vehicular Technology" (2021, vol. Surface: Beam Training and Hybrid Beamforming" proposed a channel estimation method for beam training, and analyzed the system capacity, but it did not involve the resource configuration management of the intelligent reflective surface Massive MIMO network, which is likely to cause waste of resources

"Capacity Characterization for Intelligent Reflecting Surface Aided MIMO Communication" published in "IEEE Journal on Selected Areas in Communications" (2020, vol.38, no.8, pp.1823-1838) by Shuowen Zhang et al. proposed an alternate optimization mechanism To improve the capacity of the smart reflector MIMO system, but this mechanism is to allocate system resources in the scenario where the reflection coefficient of the smart reflector is fixed or the transmission covariance matrix is ​​fixed, which limits the performance of the smart reflector and fails to maximize The confidentiality capacity of the system, in view of the openness and sharing of the wireless channel, there is a risk of being easily attacked and eavesdropped by other malicious devices, and the information security transmission of its network users has a large room for improvement

[0004] At present, the research on the secure Massive MIMO communication network based on intelligent reflectors is still in its infancy, and there are few related documents. Through comparison with the existing literature, no secure Massive MIMO network resource allocation method identical to the present invention has been found.

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