Khái niệm cốt lõi
Integrating fluidic antenna technology into mobile edge computing networks optimizes system performance by leveraging mobility to enhance channel conditions and reduce delays.
Tóm tắt
In the evolving environment of mobile edge computing (MEC), optimizing system performance is crucial. The integration of fluidic antenna (FA) technology offers a new approach to address this challenge. A proposed FA-enabled MEC scheme aims to minimize total system delay by optimizing computation offloading and antenna positioning. An alternating iterative algorithm based on the interior point method and particle swarm optimization (IPPSO) is introduced. Numerical results show significant improvements in transmission rates and reductions in delays compared to traditional fixed antenna positions. The combination of FA with emerging technologies like reconfigurable intelligent surfaces and massive MIMO opens new possibilities in wireless communication design.
Recent studies have highlighted the potential of FA technology in improving spectral efficiency, reducing transmit power, and optimizing signal quality. The proposed FA-enabled MEC scheme dynamically optimizes antenna positions and computing resource allocation to enhance service quality. The communication model considers uplink transmission from users to the BS, incorporating received signals, channel matrices, power scaling matrices, and noise components. Computation offloading models are explored for local training tasks and model parameter uploads to the MEC server.
The problem formulation focuses on minimizing total latency through joint optimization of offloading ratio, CPU frequency, and antenna positioning. An IPPSO-based alternating iterative algorithm is proposed for optimal solutions. Numerical results demonstrate fast convergence rates and reduced total latency compared to baseline schemes with fixed antenna positions.
Thống kê
Number of FAs at the BS: 4
Number of users: 3
Carrier wavelength: 0.1 m
Transmit power for each user: 30 dBm
Trích dẫn
"Studies explored the basic principles of FA technology, such as a new spatial block correlation model for FA systems."
"The proposed IPPSO algorithm exhibits robust convergence properties."
"The integration of FA technology into MEC systems utilizes the mobility of FAs within a local domain at the BS."