2026
Who should connect to whom?
Optimizing Spectral Efficiency through User Clustering in User-centric Cell-free Massive MIMO Environment for 6G Wireless Network
Pooya Hejazi · Masoud Sabaei
Journal of Communications and Networks · 28(1), pp. 30–39
The research collection
Selected publications
Four studies of how networks use their resources.
Explore the question, the method, and the evidence.
4 publications shown
2026
What can a receiver learn from fewer pilots?
Pilot-Efficient Channel Estimation for 6G MU-mMIMO Using LS Initialization and GAN-Augmented CNN Refinement
Pooya Hejazi · Masoud Sabaei · Ali Hajmahmoudi
Journal of Communications and Networks · 28(3), pp. 401–408
2020
Where should a network keep a second copy?
A novel approach for energy- and memory-efficient data loss prevention to support Internet of Things networks
Pooya Hejazi · Gianluigi Ferrari
International Journal of Distributed Sensor Networks · 16(6)
2016
When should a storage strategy change?
An adaptive hybrid schema for data-centric storage in wireless sensor networks
Pooya Hejazi
International Journal of Distributed Sensor Networks · 12(10)
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Themes in the source record
A connected research landscape.
The themes below describe subject matter; they are not separate claims of published results.
Learning for wireless systems
User-centric cell-free massive MIMO, user clustering, radio-resource allocation and pilot-efficient channel estimation using least squares, CNN/U-Net and GAN-assisted training.
Source: supplied AI portfolio · pp. 7, 8
Distributed sensor data
Data-centric storage, distributed collection and dissemination, replication, data-loss prevention, energy use and memory availability in wireless sensor and IoT networks.
Source: supplied academic CV · pp. 5, 6, 8
Streaming dimensionality reduction
Doctoral research activity on dimensionality reduction for high-dimensional streaming data using CUR.
Source: supplied academic CV · p. 6
Fairness in resource allocation
Research on fairness in allocating network resources and improving their distribution among users.
Source: supplied academic CV · p. 6
Network service orchestration
Research on service orchestration and provisioning in software-defined networks using network-function virtualization.
Source: supplied academic CV · p. 6
Data-intensive AI systems
Applied design work on data provenance, entity matching, retrieval, human-feedback analysis, tool-connected agents and response comparison.
Source: supplied AI portfolio · pp. 2, 3, 4, 5, 6, 7
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Learning for wireless systems
User-centric cell-free massive MIMO, user clustering, radio-resource allocation and pilot-efficient channel estimation using least squares, CNN/U-Net and GAN-assisted training.
Read the source-grounded account →