Intelligent massive MIMO systems for beyond 5G networks: An overview and future trends
Machine learning (ML) which is a subset of artificial intelligence is expected to unlock the
potential of challenging large-scale problems in conventional massive multiple-input …
potential of challenging large-scale problems in conventional massive multiple-input …
A survey on machine learning techniques for massive MIMO configurations: Application areas, performance limitations and future challenges
PK Gkonis - IEEE Access, 2022 - ieeexplore.ieee.org
The deployment of fifth-generation (5G) broadband wireless cellular networks has enabled
the support of highly demanding applications, paving the way towards global broadband …
the support of highly demanding applications, paving the way towards global broadband …
Quantum-inspired machine learning for 6G: Fundamentals, security, resource allocations, challenges, and future research directions
Quantum computing is envisaged as an evolving paradigm for solving computationally
complex optimization problems with a large-number factorization and exhaustive search …
complex optimization problems with a large-number factorization and exhaustive search …
Energy efficiency maximization in RIS-aided cell-free network with limited backhaul
Integrating the reconfigurable intelligent surface in a cell-free (RIS-CF) network is an
effective solution to improve the capacity and coverage of future wireless systems with low …
effective solution to improve the capacity and coverage of future wireless systems with low …
Optimal beamformer design for millimeter wave dual-functional radar-communication based V2X systems
Millimeter wave (MmWave) dual-functional radar-communication (DFRC) technology is
believed to hold the ability to alleviate spectrum congestion and inter-radar interference in …
believed to hold the ability to alleviate spectrum congestion and inter-radar interference in …
Jointly optimized beamforming and power allocation for full-duplex cell-free NOMA in space-ground integrated networks
Q Gao, M Jia, Q Guo, X Gu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Space-ground integrated networks (SGINs) have attracted substantial research interests due
to their wide area coverage capability, where spectrum sharing is employed between the …
to their wide area coverage capability, where spectrum sharing is employed between the …
Joint user clustering, beamforming, and power allocation for mmWave-NOMA with imperfect SIC
This paper investigates the framework of cross-entropy (CE) based clustering and
beamforming for mmWave-non-orthogonal multiple access (NOMA) system taking into …
beamforming for mmWave-non-orthogonal multiple access (NOMA) system taking into …
Deep reinforcement learning for energy efficiency maximization in cache-enabled cell-free massive MIMO networks: Single-and multi-agent approaches
Cell-free massive multiple-input multiple-output (CF-mMIMO) is an emerging beyond fifth-
generation (5G) technology that improves energy efficiency (EE) and removes cell structure …
generation (5G) technology that improves energy efficiency (EE) and removes cell structure …
Multi-user angle-domain MIMO-NOMA system for mmWave communications
Thanks to the high directionality of millimeter-wave (mmWave) channels, angle-domain
beamforming is an appealing technique for multi-user multiple-input multiple-output (MU …
beamforming is an appealing technique for multi-user multiple-input multiple-output (MU …
[HTML][HTML] User clustering in cell-free massive MIMO NOMA system: A learning based and user centric approach
For future wireless communications, Cell-free Massive Multiple-Input Multiple-Output (CF-
mMIMO) systems and Non-orthogonal Multiple Access (NOMA) schemes are considered …
mMIMO) systems and Non-orthogonal Multiple Access (NOMA) schemes are considered …