Reinforcement learning for efficient and tuning-free link adaptation

V Saxena, H Tullberg, J Jaldén - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Wireless links adapt the data transmission parameters to the dynamic channel state–this is
called link adaptation. Classical link adaptation relies on tuning parameters that are …

Routing optimization meets Machine Intelligence: A perspective for the future network

B Dai, Y Cao, Z Wu, Z Dai, R Yao, Y Xu - Neurocomputing, 2021 - Elsevier
The future network is expected to support extremely large bandwidth, ultra-low latency or
deterministic delay, extremely high reliability, and massive connectivity for novel forward …

Wi-Fi assisted contextual multi-armed bandit for neighbor discovery and selection in millimeter wave device to device communications

S Hashima, K Hatano, H Kasban… - Sensors, 2021 - mdpi.com
The unique features of millimeter waves (mmWaves) motivate its leveraging to future,
beyond-fifth-generation/sixth-generation (B5G/6G)-based device-to-device (D2D) …

Reinforcement learning for delay sensitive uplink outer-loop link adaptation

P Kela, T Höhne, T Veijalainen… - 2022 Joint European …, 2022 - ieeexplore.ieee.org
Link adaptation (LA)–selecting the modulation and coding scheme (MCS)–is the process
where the transmission format is adjusted to prevailing channel conditions, to achieve a …

Bayesian link adaptation under a BLER target

V Saxena, J Jaldén - 2020 IEEE 21st International Workshop on …, 2020 - ieeexplore.ieee.org
The optimal modulation and coding scheme (MCS) for wireless transmission depends on
the dynamic wireless channel state. Hence, wireless link adaptation relies on periodically …

Recent Advances in Data-driven Intelligent Control for Wireless Communication: A Comprehensive Survey

W Huo, H Yang, N Yang, Z Yang, J Zhang… - arXiv preprint arXiv …, 2024 - arxiv.org
The advent of next-generation wireless communication systems heralds an era
characterized by high data rates, low latency, massive connectivity, and superior energy …

Reinforcement learning based link adaptation in 5G URLLC

S Praveen, J Khan, L Jacob - 2021 8th International …, 2021 - ieeexplore.ieee.org
Accurate link adaptation in 5G is a major challenge as it supports a wide range of services,
including ultra-reliable low-latency communication (URLLC). URLLC has very strict latency …

Towards more reliable deep learning-based link adaptation for WiFi 6

M Hussien, MFA Ahmed, G Dahman… - ICC 2021-IEEE …, 2021 - ieeexplore.ieee.org
The problem of selecting the modulation and coding scheme (MCS) that maximizes the
system throughput, known as link adaptation, has been investigated extensively, especially …

A Contextual Multi-Armed Bandit approach for NDN forwarding

Y Mordjana, B Djamaa, MR Senouci… - Journal of Network and …, 2024 - Elsevier
Abstract Named Data Networking (NDN) is a promising Internet architecture that aims to
supersede the current IP-based architecture and shift the host-centric model to a data-centric …

AMC with a BP-ANN scheme for 5G enhanced mobile broadband

LS Chen, WH Chung, Y Chen, SY Kuo - IEEE Access, 2020 - ieeexplore.ieee.org
In 5G enhanced mobile broadband (eMBB), applications that require high spectral efficiency
and transmission speeds employ adaptive modulation and coding (AMC) technology. Such …