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Found 15 papers, 0 papers with code
Improving SINR Performance Deploying IRS in 6G Wireless Networks
As a consequence, the study evaluated and contrasted the performance of regular miniature cellular connection with IRS-enhanced miniature cellular connection in the 6G radio context in respect to signal to interference plus noise ratio (SINR).
Downlink Received Power Performance Analysis of IRS for 6G Networks
The Internet of Things (IoT) is going to be a few of the most influential and critical role spectators in the post-5G and 6G wireless networking paradigm because IoT is being deployed in a variety of applications and services such as smart towns, smart homes, savvy environment monitoring, smart medical care, smart factories, savvy agri-business, and so on, with the goal of enabling intelligent coordination and efficiency improvement.
Capacity Maximization of the 6G Networks Deploying IRS
The objective of the work is to improve the capacity of the micro cell, i. e., enabling the micro cell base station of a two-tier network to serve an increased number of devices.
Intelligent Reflecting Surfaces Positioning in 6G Networks
The work analyzed the positioning of IRS over the coverage region of micro cell to derive optimal placement location to support cell-edge Internet of Things (IoT) devices with a favorable signal-to-interference plus noise ratio (SINR).
SINR Coverage Enhancement of 6G UAV-Assisted Networks Deploying IRS
The objective of the work is to enhance the signal-to-interference-plus-noise ratio (SINR) coverage probability in UAV-assisted 6G wireless networks.
Analysis of IRS-Assisted NOMA for 6G Wireless Communications
This work modified the reference model by adopting an IRS-specific frequency-distance-dependent path loss model for IRS-NOMA downlink received power and signal-to-interference plus noise ratio (SINR) measurement instead of a typical or conventional distance-dependant path loss model.
Maximization of User Association Deploying IRS in 6G Networks
The objective of this work is to maximize the probability of user association for millimeter-wave (mmWave) carriers in a two-tier 6G network consisting of micro and macro cell tiers.
Intelligent Reflecting Surfaces for the Enhancement of 6G Internet of Things
With the advancement of sensing technologies over the years, it has become critical to ensure the seamless connectivity of the Internet of Things (IoT) gadgets.
IRS for Multi-Access Edge Computing in 6G Networks
Computation offloading in multi-access edge computing (MEC) is an effective paradigm for enabling resource-intensive smart applications.
The Deployment of IRS in UAV-Empowered 6G Networks
The research obtained that the IRSempowered UAV communications model can significantly minimize path loss and maximize the achievable data rate compared to the conventional UAV-assisted model.
Indoor Localization Under Limited Measurements: A Cross-Environment Joint Semi-Supervised and Transfer Learning Approach
Moreover, with only 40% data measurements, the proposed cross-environment approach compensates for data inadequacy and replicates the localization accuracy of the conventional method, CNN, which uses 75% data measurements.
CNN aided Weighted Interpolation for Channel Estimation in Vehicular Communications
IEEE 802. 11p standard defines wireless technology protocols that enable vehicular transportation and manage traffic efficiency.
Modeling of Vertical Dipole Above Lossy Dielectric Half-Space: Characteristic Mode Theory
The proposed formulations have been studied with different heights from the ground plane and are compared with the direct modal solutions to validate its accuracy.
Ultra-Wideband Antenna with MIMO Diversity for 5G Wireless Communication
An eight element, compact Ultra Wideband-Multiple Input Multiple Output (UWB-MIMO) antenna capable of providing high data rates for future Fifth Generation (5G) terminal equipments along with the provision of necessary bandwidth for Third Generation (3G) and Fourth Generation (4G) communications that accomplishes band rejection from 4. 85 to 6. 35 GHz by deploying a Inductor Capacitor (LC) stub on the ground plane is presented.
Indoor Localization for IoT Using Adaptive Feature Selection: A Cascaded Machine Learning Approach
This paper presents a novel method based on a cascaded two-stage machine learning approach for highly-accurate and robust localization in indoor environments using adaptive selection and combination of RF features.
