# Joint Channel Estimation and Computation Offloading in Fluid Antenna-assisted MEC Networks

arXiv: https://arxiv.org/abs/2509.19340 · HTML: https://mlsanity.com/paper/2509.19340/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 15 of its 51 references that are in the map.
- First posted on arXiv 16 Sep 2025.

## Builds on (most cited first, 15 of 15)

- [Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments](https://mlsanity.com/paper/1706.02275/) (2017)
- [Accurate Image Super-Resolution Using Very Deep Convolutional Networks](https://mlsanity.com/paper/1511.04587/) (2015)
- [Restricting the Flow: Information Bottlenecks for Attribution](https://mlsanity.com/paper/2001.00396/) (2020)
- [Group-based Sparse Representation for Image Restoration](https://mlsanity.com/paper/1405.3351/) (2014)
- [Fluid Antenna Systems](https://mlsanity.com/paper/2005.11561/) (2020)
- [Movable Antennas for Wireless Communication: Opportunities and Challenges](https://mlsanity.com/paper/2306.02331/) (2023)
- [Compressed Sensing Based Channel Estimation for Movable Antenna Communications](https://mlsanity.com/paper/2306.04333/) (2023)
- [Successive Bayesian Reconstructor for Channel Estimation in Fluid Antenna Systems](https://mlsanity.com/paper/2312.06551/) (2023)
- [Channel Estimation for Movable Antenna Communication Systems: A Framework Based on Compressed Sensing](https://mlsanity.com/paper/2312.06969/) (2023)
- [Fluid Antenna for Mobile Edge Computing](https://mlsanity.com/paper/2403.11806/) (2024)
- [Movable Antenna Enhanced Wireless Sensing Via Antenna Position Optimization](https://mlsanity.com/paper/2405.01215/) (2024)
- [Fluid Antenna Relay Assisted Communication Systems Through Antenna Location Optimization](https://mlsanity.com/paper/2404.00628/) (2024)
- [Channel Estimation and Reconstruction in Fluid Antenna System: Oversampling is Essential](https://mlsanity.com/paper/2405.15607/) (2024)
- [Movable Antenna Enabled Near-Field Communications: Channel Modeling and Performance Optimization](https://mlsanity.com/paper/2409.19316/) (2024)
- [Sum Rate Maximization for Movable Antenna Enhanced Multiuser Covert Communications](https://mlsanity.com/paper/2410.09436/) (2024)

## Abstract (arXiv)

With the emergence of fluid antenna (FA) in wireless communications, the capability to dynamically adjust port positions offers substantial benefits in spatial diversity and spectrum efficiency, which are particularly valuable for mobile edge computing (MEC) systems. Therefore, we propose an FA-assisted MEC offloading framework to minimize system delay. This framework faces two severe challenges, which are the complexity of channel estimation due to dynamic port configuration and the inherent non-convexity of the joint optimization problem. Firstly, we propose Information Bottleneck Metric-enhanced Channel Compressed Sensing (IBM-CCS), which advances FA channel estimation by integrating information relevance into the sensing process and capturing key features of FA channels effectively. Secondly, to address the non-convex and high-dimensional optimization problem in FA-assisted MEC systems, which includes FA port selection, beamforming, power control, and resource allocation, we propose a game theory-assisted Hierarchical Twin-Dueling Multi-agent Algorithm (HiTDMA) based offloading scheme, where the hierarchical structure effectively decouples and coordinates the optimization tasks between the user side and the base station side. Crucially, the game theory effectively reduces the dimensionality of power control variables, allowing deep reinforcement learning (DRL) agents to achieve improved optimization efficiency. Numerical results confirm that the proposed scheme significantly reduces system delay and enhances offloading performance, outperforming benchmarks. Additionally, the IBM-CCS channel estimation demonstrates superior accuracy and robustness under varying port densities, contributing to efficient communication under imperfect CSI.