Results 51 to 60 of about 656 (174)

Hyperparameter‐Free Maximum Versoria Criterion Based Channel‐State Acquisition for mmWave Hybrid MIMO With Hardware Impairments

IET Communications, Volume 20, Issue 1, January/December 2026.
This paper addresses channel estimation in mmWave (millimetre wave) hybrid MIMO (multiple‐input multiple‐output) systems impaired by residual transceiver hardware nonidealities, modelled as additive non‐Gaussian noise via Bussgang decomposition. A hyperparameter‐free maximum Versoria criterion (MVC)‐based channel estimator is proposed, featuring a ...
Rangeet Mitra, Sandesh Jain, K. Venkateswaran, Rajat Kumar, Vimal Bhatia, Ondrej Krejcar   +5 more
wiley   +1 more source

Design of full-connected hybrid precoding based on an equivalent channel in millimeter-wave massive MIMO system

Dianxin kexue, 2021
In order to improve the performance of hybrid precoding scheme based on fully connected structure in millimeter-wave massive MIMO system, a hybrid precoding scheme based on an equivalent channel with two-step design method was proposed.Firstly, the ...
Haiyan CAO, Zhiyao MA, Yingjuan ZHI, Renqing LIU, Fangmin XU, Xin FANG   +5 more
doaj   +2 more sources

Regularised Hyper Parameter Bi Level Optimisation With Continual Learning Based Deep Neural Network for Beamforming in Ultra‐Wide Band System

IET Communications, Volume 20, Issue 1, January/December 2026.
This research proposes a Regularised Hyperparameter Bilevel Optimisation with Continual Learning‐based Deep Neural Network (RHBO‐CLDNN) for beamforming in an Ultra‐Wide Band (UWB) system. The RHBO ensures the hyperparameter efficiency at both upper and lower levels, which allows DNN to fine‐tune the unique characteristics of the UWB system, which leads
Pradeep Kumar Siddanna, Bidare Divakarachari Parameshachari, Dharmanna Shivappa Lamani   +2 more
wiley   +1 more source

Channel Estimation and Hybrid Precoding for Millimeter-Wave MIMO Systems: A Low-Complexity Overall Solution

IEEE Access, 2017
To enable multi-stream transmission and increase the achievable rate, a hybrid digital/analog precoding structure is usually adopted in millimeter-wave (mmWave) MIMO systems.
Zhenyu Xiao, Pengfei Xia, Xiang-Gen Xia
doaj   +1 more source

Near‐Field 3D Stochastic Channel Modelling and Performance Analysis for Cooperative STAR‐RIS Systems With Cylindrical Transmit Arrays

IET Communications, Volume 20, Issue 1, January/December 2026.
This paper develops a near‐field three‐dimensional geometry‐based stochastic channel model for cooperative STAR‐RIS systems equipped with cylindrical transmit arrays at the base station. The proposed model captures spherical wavefront propagation effects and coupled azimuth‐elevation characteristics under realistic near‐field conditions.
Antwi Owusu Agyeman, Tweneboah‐Koduah Samuel, Ruhiya Abubakar, Martin Alabi Mensah, Emmanuel Atebawone, Anim Frederick Oturoku   +5 more
wiley   +1 more source

Computationally Efficient Deep Learning Inference for High‐Rate Beamforming in Millimeter‐Wave Internet of Vehicles

IET Communications, Volume 20, Issue 1, January/December 2026.
ABSTRACT Millimeter‐wave (mmWave) Internet‐of‐Vehicles (IoV) communications rely on large antenna arrays to combat severe path loss and to provide high beamforming gains. However, practical vehicular deployments often adopt analog or hybrid beamforming with constant‐modulus constraints, leading to a highly non‐convex joint beamforming design problem ...
Haowen Zheng, Zihan Li, Jianxin Dai, Haifeng Tang, Xinyi Hui   +4 more
wiley   +1 more source

Deep Reinforcement Learning‐Enabled QoS‐Aware Adaptive Modulation for Visible Light‐Infrared Communication Systems

IET Communications, Volume 20, Issue 1, January/December 2026.
To address the challenges of channel sensitivity and reliability in aircraft cabin environments, this paper proposes a reinforcement learning‐assisted bidirectional communication system utilizing visible light for the downlink and infrared for the uplink. By combining an improved, resource‐efficient LMMSE algorithm for channel estimation with RL‐driven
Lei Xiao, Quanyi Cheng, Baolin Lai, Xiaodong Liu, BuGao Liu, Junyi Du   +5 more
wiley   +1 more source

Deep Reinforcement Learning‐Based Power Control Optimisation for Maximising Energy Efficiency in mmWave User‐Centric Cell‐Free Massive MIMO

IET Communications, Volume 20, Issue 1, January/December 2026.
The multi‐agent Deep Reinforcement Learning (DRL)‐based uplink power control algorithm significantly improves energy efficiency using multi‐agent Deep Deterministic Twin Policy Gradient (MATD3) with dynamic clustering. The Proposed algorithm outperforms single‐agent DRL and classical methods.
Dramane Diarra, Heywood Ouma Absaloms, Philip Kibet Langat   +2 more
wiley   +1 more source

Decentralized Hybrid Precoding for Massive Mu-Mimo Isac

ICC 2025 - IEEE International Conference on Communications
Integrated sensing and communication (ISAC) is a very promising technology designed to provide both high rate communication capabilities and sensing capabilities. However, in Massive Multi User Multiple-Input Multiple-Output (Massive MU MIMO-ISAC) systems, the dense user access creates a serious multi-user interference (MUI) problem, leading to ...
Jun Zhu, Yin Xu 0001, Dazhi He, Haoyang Li 0004, Yunfeng Guan 0001, Wenjun Zhang 0001   +5 more
openaire   +2 more sources

Hybrid LISA Precoding for Multiuser Millimeter-Wave Communications [PDF]

IEEE Transactions on Wireless Communications, 2018
Millimeter-wave (mmWave) communications plays an important role for future cellular networks because of the vast amount of spectrum available in the underutilized mmWave frequency bands. To overcome the huge free space omnidirectional path loss in those frequency bands, the deployment of a very large number of antenna elements at the base station is ...
Wolfgang Utschick, Christoph Stöckle, Michael Joham, Jian Luo 0001   +3 more
openaire   +2 more sources