Transceiver and irs optimization design method of air computing system under non-ideal csi

Abstract

The invention discloses a transceiver and an IRS optimization design method of an air computing system under non-ideal CSI, which comprises the following steps: (1) According to the uncertainty domain of CSI, the error of CSI is solved under the worst case of MSE at the receiving end and the receiving end is calculated. (2) Remove the constant modulus constraint of the IRS phase, and aim at minimizing the MSE at the receiving end, and fix the transmit power t of each sensor k and the combination coefficient m at the receiving end to optimize the reflection phase vector v of the IRS k ; (3) The reflection phase vector v of the fixed IRS k , optimize the transmit power t of each sensor k and the combination coefficient m of the receiving end; (4) repeat steps (2)-(3) until the MSE iteration convergence of the receiving end; (5) the reflection phase vector v of the IRS k Perform constant modulus constraints. The invention can reduce the receiving error of the system under the non-ideal CSI condition under the condition that the total transmission power is limited.

Description

Technical field [0001] The present invention relates to the field of communications, to transceivers and IRS optimization design methods of transceivers and IRS under-air computing systems under non-ideal CSI. Background [0002] Internet of Things (IoT) services are in full swing and touch every aspect of people's lives. As the most prominent feature of the current information high-speed era, the amazing growth of massive data is of vital significance to the Internet of Things. On the one hand, the number of IoT smart devices is increasing, making data collection more difficult. On the other hand, the information fusion of massive amounts of data, or what we call data aggregation, is more challenging for the low spectral efficiency and high latency of billions of sensors. [0003] To solve this problem, the researchers have proposed a promising solution that utilizes the over-the-air computing (AirComp) of the superposition characteristics of wireless multiple access channels (M...

AI Technical Summary

Problems solved by technology

[0006] In order to solve complex non-convex problems, the present invention obtains the closed-form solution of the robust problem and the joint design of the transmission power of each sensor, the combination coefficient of the receiving end and the IRS phase by using an efficient alternate optimization algorithm and KKT conditions

Images