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Concatenated Cluster Delay Line Channel Modelling in Ris-Assisted 6G Wireless Communication Systems

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A Cluster Delay Line (CDL) is an advanced, more realistic, and accurate wireless channel model as per 3GPP standards, particularly for mmWave frequency bands. In simulating a complex multipath wireless signal propagation, CDL channel model represents scattered multipath signals as into logical groups called 'clusters' of delayed versions. The multipath signals are from different reflecting surfaces where each signal with a specific delay. In this paper, we generate a 6 G waveform and transmit through a reconfigurable intelligent surfaces (RIS)-assisted channel and evaluate the received signal strength along with its signal constellation. It models the two channels using CDL channels, i.e. between base station (BS) to RIS and RIS to user equipment (UE). In the absence of line of sight (LOS) path, the RIS-assisted channel is simulated using CDL channel model and an algorithm is proposed to control and optimize the phase of individual reflecting elements of RIS through iterative process. This work also models RIS scattering losses and channel path losses with stochastic models. The received signal-to-noise ratio (SNR) and the path loss are evaluated at 4 GHz-42 GHz frequency bands for different modulation schemes.

Original languageEnglish
Title of host publicationProceedings of 3rd International Conference on Machine Learning and Autonomous Systems, ICMLAS 2026
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1502-1507
Number of pages6
ISBN (Electronic)9798331574574
DOIs
Publication statusPublished - 2026
Event3rd International Conference on Machine Learning and Autonomous Systems, ICMLAS 2026 - Bangkok, Thailand
Duration: 11-03-202613-03-2026

Publication series

NameProceedings of 3rd International Conference on Machine Learning and Autonomous Systems, ICMLAS 2026

Conference

Conference3rd International Conference on Machine Learning and Autonomous Systems, ICMLAS 2026
Country/TerritoryThailand
CityBangkok
Period11-03-2613-03-26

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Control and Optimization
  • Health Informatics
  • Computer Science Applications
  • Information Systems and Management

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