相关论文: Two-Stage Hierarchical Beam Training for Near-Fiel…
Wideband millimeter-wave and terahertz (THz) systems can facilitate simultaneous data communication with multiple spatially separated users. It is desirable to orthogonalize users across sub-bands by deploying frequency-dependent beams with…
Large antenna arrays can be used to generate highly focused beams that support very high data rates and reduced energy consumption. However, optimal beam focusing requires large amount of feedback from the users in order to choose the best…
Future wireless systems are expected to employ extremely large-scale multiple-input multiple-output (XL-MIMO) arrays at high carrier frequencies, where near-field propagation makes the channel depend jointly on angle and distance. The…
In near-field extremely large-scale multiple-input multiple-output (XL-MIMO) systems, spherical wavefront propagation expands the traditional beam codebook into the joint angular-distance domain, rendering conventional beam training…
Phased arrays, commonly used in IEEE 802.11ad and 5G radios, are capable of focusing radio frequency signals in a specific direction or a spatial region. Beamforming achieves such directional or spatial concentration of signals and enables…
Extremely large-scale multiple-input multiple-output (XL-MIMO) communication aims to further boost the antenna size significantly than current massive MIMO systems, for which conventional far-field assumption with uniform plane wave (UPW)…
In an extra-large scale MIMO (XL-MIMO) system, the antenna arrays have a large physical size that goes beyond the dimensions in traditional MIMO systems. Because of this large dimensionality, the optimization of an XL-MIMO system leads to…
Extremely large-scale arrays (XL-arrays) have emerged as a promising technology for enabling near-field communications in future wireless systems. However, the huge number of antennas deployed pose demanding challenges on the hardware cost…
This letter proposes a linear bandit-based beam training framework for near-field communication under multi-path channels. By leveraging Thompson Sampling (TS), the framework adaptively balances exploration and exploitation to maximize…
The extremely large-scale massive multiple-input multiple-output (XL-MIMO) has the potential to achieve boosted spectral efficiency and refined spatial resolution for future wireless networks. However, channel estimation for XL-MIMO is…
6G networks will need to support higher data rates, high-precision localization, and imaging capabilities. Near-field technologies, enabled by extremely large-scale (XL)-arrays, are expected to be essential physical-layer solutions to meet…
Deep neural networks provide state-of-the-art accuracy for vision tasks but they require significant resources for training. Thus, they are trained on cloud servers far from the edge devices that acquire the data. This issue increases…
Wireless communications with extremely large-scale array (XL-array) correspond to systems whose antenna sizes are so large that conventional modelling assumptions, such as uniform plane wave (UPW) impingement, are longer valid. This paper…
Hybrid beamforming for extremely large-scale multiple-input multiple-output (XL-MIMO) systems is challenging in the near field because the channel depends jointly on angle and distance, and the multiuser interference (MUI) is strong.…
Communication at terahertz (THz) frequency bands is a promising solution for achieving extremely high data rates in next-generation wireless networks. While the THz communication is conventionally envisioned for short-range wireless…
Millimeter wave (mmWave) is an attractive candidate for high-speed mobile communications in the future. However, due to the propagation characteristics of mmWave, beam and and and and alignment becomes a key challenge for serving users with…
As a promising technique, extremely large-scale (XL)-arrays offer potential solutions for overcoming the severe path loss in millimeter-wave (mmWave) and TeraHertz (THz) channels, crucial for enabling 6G. Nevertheless, XL-arrays introduce…
Optimization of hyper-parameters in reinforcement learning (RL) algorithms is a key task, because they determine how the agent will learn its policy by interacting with its environment, and thus what data is gathered. In this work, an…
Massive multiple-input multiple-output (mMIMO) communications are one of the enabling technologies of 5G and beyond networks. While prior work indicates that mMIMO networks employing time division duplexing have a significant capacity…
Extremely large-scale multiple-input multiple-output (XL-MIMO) is a key enabling technology for sixth-generation (6G) communication systems. Nevertheless, the increase in array aperture and signal bandwidth brings new challenges to wideband…