Related Experiment Video
Updated: May 20, 2026
06:34
A Single-Channel and Non-Invasive Wearable Brain-Computer Interface for Industry and Healthcare
Published on: July 7, 2023
MEC-enabled load balancing framework for DFA-IRS aided wearable healthcare networks
Jarallah Alqahtani1, Ashu Taneja2, Nayef Alqahtani3
1Computer Science Department, College of Computer Science and Information Systems, Najran University, Najran, 61441, Saudi Arabia.
Scientific Reports
|May 18, 2026
Summary
This study introduces double-faced active intelligent reflecting surfaces (IRSs) to enhance mobile edge computing (MEC) for wearable devices, overcoming power and processing limitations for reliable task offloading.
Area of Science:
- Wireless communication networks
- Mobile edge computing
- Wearable electronics
Background:
- Wearable devices face limitations in power and processing, hindering complex computations.
- Intelligent Reflecting Surfaces (IRSs) offer a promising solution to resource constraints in wireless networks.
Purpose of the Study:
- To propose a wearable electronics network utilizing Double-Faced Active (DFA) IRSs for efficient mobile edge computing (MEC) task offloading.
- To develop a resource utilization (RU) algorithm for device-DFA-IRS association and optimize DFA-IRS phase shifts.
Main Methods:
- A novel network architecture employing DFA-IRSs for simultaneous reflection and transmission with active amplification.
- Development of a resource utilization (RU) algorithm for device-DFA-IRS association.
- Optimization of DFA-IRS phase shifts to maximize system performance.
Main Results:
- The proposed DFA-IRS aided system achieves an average sum rate of 8.2 bps/Hz with specific parameters (N=120, 20dBm transmit power).
- An improvement of 5.80% in average sum rate is observed compared to random phase shifts.
- Performance comparison with conventional IRS, SFA-IRS, and STAR-IRS demonstrates the superiority of the DFA-IRS approach.
Conclusions:
- DFA-IRS technology significantly enhances the performance of MEC-based task offloading in wearable networks.
- The proposed system offers a viable solution for reliable and efficient computation for resource-constrained wearable devices.
- The network architecture has potential applications in personalized healthcare and other advanced wireless services.
Related Concept Videos
01:19Distributed Loads
Distributed loads are a common type of load that engineers and scientists encounter in various practical situations. Distributed loads often refer to a type of load spread over a surface or a structure and can be modeled as continuous force per unit area.
For example, consider a bookshelf filled with books stacked vertically adjacent to each other. The weight of the books is evenly distributed over the length of the shelf. As a result, the pressure at different locations on the surface of the...
For example, consider a bookshelf filled with books stacked vertically adjacent to each other. The weight of the books is evenly distributed over the length of the shelf. As a result, the pressure at different locations on the surface of the...
01:20Integrated Healthcare System
An integrated healthcare system (IHS) is a set of organizations that provides for or arranges to provide coordinated and continuous service to a defined population. The IHS takes responsibility for that particular population's health status and outcome, both clinically and fiscally. An integrated healthcare system is a well-organized, well-coordinated, and collaborative network. The integrated delivery system is a network that connects different healthcare providers to deliver organized,...
01:21Distributed Loads: Problem Solving
Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...