Joint Optimization for Over-the-Air Computation in AF Relay-Assisted Cognitive Radio Networks

This paper investigates the over-the-air computation (AirComp) in a cognitive radio (CR) data network, which contains a primary network, a secondary network, and an amplify-and-forward (AF) relay. There are sensors in each network that transmit data to their corresponding access point (AP). The aim...

Full description

Saved in:
Bibliographic Details
Published inIEEE transactions on vehicular technology Vol. 73; no. 10; pp. 15809 - 15814
Main Authors Yao, Junteng, Jin, Ming, Wu, Tuo, Li, Quanzhong, Wong, Kai-Kit
Format Journal Article
LanguageEnglish
Published New York IEEE 01.10.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Online AccessGet full text
ISSN0018-9545
1939-9359
DOI10.1109/TVT.2024.3409366

Cover

More Information
Summary:This paper investigates the over-the-air computation (AirComp) in a cognitive radio (CR) data network, which contains a primary network, a secondary network, and an amplify-and-forward (AF) relay. There are sensors in each network that transmit data to their corresponding access point (AP). The aim of the AF relay is to improve the computation performance of the two networks. We study the sum mean-square-error (MSE) minimization problem, named as SMSE-min problem, subject to the transmit power constraints at the AF relay and the sensors in the two networks. It is not trivial to obtain the optimal solution of the formulated non-convex problem due to the coupled optimization variables. We propose an alternating optimization algorithm for alternatively optimizing four sub-problems about the aggregation beamforming at two APs, transmit scaling factors at the sensors, and the AF matrix at the relay, and obtain the locally optimal solution, where the closed-form solution can be obtained in each sub-problem. Numerical results show the superior sum MSE performance of our proposed scheme.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2024.3409366