Related papers: Self-supervised Contrastive Learning for 6G UM-MIM…
Beamforming is an essential technology in the 5G massive multiple-input-multiple-output (MMIMO) communications, which are subject to many impairments due to the nature of wireless transmission channel, i.e. the air. The inter-cell…
Contrastive self-supervised learning (CSL) has managed to match or surpass the performance of supervised learning in image and video classification. However, it is still largely unknown if the nature of the representations induced by the…
Hybrid beamforming is vital in modern wireless systems, especially for massive MIMO and millimeter-wave (mmWave) deployments, offering efficient directional transmission with reduced hardware complexity. However, effective beamforming in…
Learning discriminative image representations plays a vital role in long-tailed image classification because it can ease the classifier learning in imbalanced cases. Given the promising performance contrastive learning has shown recently in…
Advancements in 6G wireless technology have elevated the importance of beamforming, especially for attaining ultra-high data rates via millimeter-wave (mmWave) frequency deployment. Although promising, mmWave bands require substantial beam…
Hybrid transceiver design in multiple-input multiple-output (MIMO) Tera-Hertz (THz) systems relying on sparse channel state information (CSI) estimation techniques is conceived. To begin with, a practical MIMO channel model is developed for…
Terahertz (THz) communications are regarded as a pillar technology for the 6G systems, by offering multi-ten-GHz bandwidth. To overcome the huge propagation loss while reducing the hardware complexity, THz ultra-massive (UM) MIMO systems…
Terahertz ultra-massive multiple-input multiple-output (THz UM-MIMO) is envisioned as one of the key enablers of 6G wireless systems. Due to the joint effect of its array aperture and small wavelength, the near-field region of THz UM-MIMO…
Benefiting from the growth of the bandwidth, Terahertz (THz) communication can support the new application with explosive requirements of the ultra-high-speed rates for future 6G wireless systems. In order to compensate for the path loss of…
We propose a robust transceiver design for a covert integrated sensing and communications (ISAC) system with imperfect channel state information (CSI). Considering both bounded and probabilistic CSI error models, we formulate worst-case and…
Recently, terahertz (THz) communication has drawn considerable attention as one of the promising technologies for the future wireless communications owning to its ultra-wide bandwidth. Nonetheless, one major obstacle that prevents the…
Benefiting from tens of GHz of bandwidth, terahertz (THz) communications has become a promising technology for future 6G networks. However, the conventional hybrid beamforming architecture based on frequency-independent phase-shifters is…
Terahertz (THz)-band communications are currently being celebrated as a key technology that could fulfill the increasing demands for wireless data traffic in the upcoming sixth-generation (6G) of wireless communications. Many challenges,…
A dual-robust design of beamforming is investigated in an integrated sensing and communication (ISAC) system.Existing research on robust ISAC waveform design, while proposing solutions to imperfect channel state information (CSI), generally…
Sub-terahertz (sub-THz) multi-user multiple-input multiple-output (MU-MIMO) systems unlock immense bandwidth for 6G wireless communications. However, practical deployment of wireless systems in sub-THz bands faces critical challenges such…
The literature is abundant with methodologies focusing on using transformer architectures due to their prominence in wireless signal processing and their capability to capture long-range dependencies via attention mechanisms. In particular,…
Radio Frequency (RF) device fingerprinting has been recognized as a potential technology for enabling automated wireless device identification and classification. However, it faces a key challenge due to the domain shift that could arise…
Contrastive self-supervised learning has attracted significant research attention recently. It learns effective visual representations from unlabeled data by embedding augmented views of the same image close to each other while pushing away…
Correlation exploitation is essential for efficient multi-user channel estimation (MUCE) in massive MIMO systems. However, the existing works either rely on presumed strong correlation or learn the correlation through large amount of…
Two of the main problems to achieve ultra-reliable low-latency communications (URLLC) are related to instantaneous channel state information (I-CSI) acquisition and the coexistence with other service modes such as enhanced mobile broadband…