Optimized CNN-based channel estimation for zero-padded uplink OFDMA in 5G new radio over fast-fading channels

Simple item page
dc.contributor.authorMata, Tanairat
dc.contributor.authorBoonsrimuang, Pisit
dc.date.accessioned2026-08-06T10:56:06Z
dc.date.available2026-08-06T10:56:06Z
dc.date.issued2026-07-01
dc.description.abstractThis paper addresses a pilot-assisted channel estimation applicable to the uplink orthogonal frequency-division multiple-access with zero-padding in a 5G new radio. The adjacent uplink subchannels in the frequency domain are allocated separately for each user, and each subchannel assigns the pilot signal independently. This paper proposes a convolutional neural network-based channel estimation, including one-dimensional and two-dimensional architectures, designed to optimize the handling of rapid fading channel variations encountered in high-mobility scenarios. The estimation process leverages the subchannels of each user to enhance accuracy. Simulation results demonstrate the effectiveness of the proposed method in offering a better bit-error rate and a higher transmission data rate than the conventional channel estimation methods under challenging conditions. Finally, this paper discusses the considerable computational complexity of aspects of the lightweight two convolutional neural network architectures.
dc.identifier.citationPhysical Communication, 77, 2026
dc.identifier.doi10.1016/j.phycom.2026.103167
dc.identifier.issn18744907
dc.identifier.other2-s2.0-105039764288
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/18246
dc.sourcePhysical Communication
dc.subject5G new radio
dc.subjectChannel estimation
dc.subjectConvolutional neural network
dc.subjectHigh-mobility scenarios
dc.subjectUplink OFDMA
dc.titleOptimized CNN-based channel estimation for zero-padded uplink OFDMA in 5G new radio over fast-fading channels
dc.typeArticle

Files

Collections

Research