01
Semantic-aware
networking
Using the meaning and correlation of data to guide wireless access, reduce redundant transmissions, and balance utilization with fairness.
Explore this directionDOCTORAL RESEARCHER RUB
Hamid RezaMazandarani.
At the intersection of AI
and wireless networking.
I study how artificial intelligence can make wireless networks more adaptive, efficient, and semantic-aware.
Ruhr University Bochum · Bochum, Germany
01 Semantic communication
02 Adaptive learning
03 Edge intelligence
01 / ABOUT
Intelligence,
across the network.
I am a doctoral researcher at Ruhr University Bochum, working at the intersection of artificial intelligence and wireless networking.
My research focuses on semantic-aware multiple access, learning-based resource allocation, and the orchestration of AI services at the network edge. I explore how distributed agents can adapt to changing environments while making efficient use of communication and computing resources.
My work brings together deep reinforcement learning, continual learning, and the structure of information itself—from correlations between users’ observations to the demands of generative AI workloads.
ACADEMIC BACKGROUND
2016
M.Sc. · Computer Systems Networking
Isfahan University of Technology
2013
B.Sc. · Telecommunications Engineering
Ferdowsi University of Mashhad
02 / RESEARCH DIRECTIONS
Networks that learn.
Communication that matters.
Three connected themes, from spectrum access to intelligent service delivery.
Semantic-aware
02
Adaptive learning
for wireless access
Designing reinforcement-learning agents that adapt to heterogeneous, non-stationary wireless environments through continual learning.
Explore this direction03
Edge AI
orchestration
Coordinating communication and computing resources for generative AI and vehicular services under latency and energy constraints.
Explore this direction03 / SELECTED WORK
Publications.
Selected papers and preprints, 2023–2026. PDF links open author manuscripts; publication status is shown for each entry.
Showing 8 of 8 selected publications
202601
A Semantic-Aware Multiple Access Scheme Leveraging Spatial Redundancy for Uplink-Dominant Network Services
IEEE Transactions on Network and Service Management · 2026
Research summary
PRISM uses inter-user data redundancy to guide distributed spectrum access, balancing fairness, spectrum use, and energy efficiency with multi-agent deep reinforcement learning.
202602
Exploiting Overlapping Fields of View for Redundancy-Aware Uplink Transmission in Vehicular 6G
arXiv:2606.31715 · 2026
Research summary
A two-phase approach combines vehicle-to-vehicle sharing and selective uplink transmission to avoid sending redundant visual information from overlapping fields of view.
202603
Energy Efficient Orchestration in Multiple-Access Vehicular Aerial-Terrestrial 6G Networks
IEEE Transactions on Vehicular Technology · 2026
Research summary
Hierarchical reinforcement learning coordinates UAV trajectories, multiple access, and service placement to improve energy efficiency and support latency-sensitive vehicular applications.
202504
Adaptive Multiple Access and Service Placement for Generative Diffusion Models
IEEE Global Communications Conference (GLOBECOM) · 2025
Research summary
LEARN-GDM jointly considers wireless access and the placement of diffusion-model denoising blocks across edge nodes, accounting for communication costs and inference latency.
202505
A Novel Multiple Access Scheme for Heterogeneous Wireless Communications Using Symmetry-Aware Continual Deep Reinforcement Learning
IEEE Transactions on Machine Learning in Communications and Networking · 2025
Research summary
A symmetry-aware continual-learning mechanism adapts a deep reinforcement learning access protocol to changing wireless environments while accounting for coexistence and fairness.
202406
Semantic Revolution From Communications to Orchestration for 6G: Challenges, Enablers, and Research Directions
IEEE Network · 2024
Research summary
The KB-MANO framework connects knowledge-base management with network and computing resources, exploring how semantic communication can be supported at the orchestration layer.
202407
A Semantic-Aware Multiple Access Scheme for Distributed, Dynamic 6G-Based Applications
IEEE Wireless Communications and Networking Conference (WCNC) · 2024
Research summary
SAMA-D3QL incorporates correlations between users’ data into distributed spectrum-access decisions, combining semantic awareness with multi-agent deep reinforcement learning.
202308
Self-Sustaining Multiple Access with Continual Deep Reinforcement Learning for Dynamic Metaverse Applications
IEEE International Conference on Metaverse Computing, Networking and Applications (MetaCom) · 2023
Research summary
Continual learning helps a double deep Q-learning agent respond to changing numbers of active users in multi-channel wireless access environments.
No publications match these filters. Try another keyword or choose All.
This is a selected list, not a complete publication record. See Google Scholar for the wider list.
04 / OPEN RESOURCES
From papers
to practice.
Public code and reading resources connected to my research.
SAMA-D3QL
The implementation accompanying our WCNC 2024 paper on semantic-aware multiple access for distributed, dynamic 6G applications.
Awesome-SemCom
A curated reading list on semantic and task-oriented communications, with a focus on resource allocation and orchestration.
05 / RESEARCH UPDATES
Recent
developments.
PREPRINT UPDATE
Rethinking redundant vehicular transmissions.
Updated manuscript on overlapping fields of view and redundancy-aware uplink transmission in vehicular 6G.
Read the paperAUTHOR MANUSCRIPT ONLINE
PRISM: semantic awareness at the access layer.
Our manuscript on spatial-redundancy-aware multiple access is available on arXiv and marked as accepted by IEEE Transactions on Network and Service Management.
Read the paperJOURNAL PUBLICATION
Energy-efficient orchestration for vehicular 6G.
Joint UAV trajectory planning, multiple access, and service placement in IEEE Transactions on Vehicular Technology.
Read the paper06 / CONTACT
Let’s connect.
For research discussions, questions about my work,
or opportunities to collaborate.