Related papers: Vector Quantized-Aided XL-MIMO CSI Feedback with C…
Multi-antenna or multiple-input multiple-output (MIMO) technique can significantly improve the efficiency of radio frequency (RF) signal enabled wireless energy transfer (WET). To fully exploit the energy beamforming gain at the energy…
Wireless foundation models promise transformative capabilities for channel state information (CSI) processing across diverse 6G network applications, yet face fundamental challenges due to the inherent dual heterogeneity of CSI across both…
Wi-Fi gesture recognition based on Channel State Information (CSI) is challenged by high-dimensional noise and resource constraints on edge devices. Prevailing end-to-end models tightly couple feature extraction with classification,…
Large AI models (LAMs) have shown strong potential in wireless communication tasks, but their practical deployment remains hindered by latency and computational constraints. In this work, we focus on the challenge of integrating LAMs into…
Sparse signals, encountered in many wireless and signal acquisition applications, can be acquired via compressed sensing (CS) to reduce computations and transmissions, crucial for resource-limited devices, e.g., wireless sensors. Since the…
Multi-antenna precoding effectively mitigates the interference in wireless networks. However, the precoding efficiency can be significantly degraded by the overhead due to the required feedback of channel state information (CSI). This paper…
Base station cooperation improves the sum-rates that can be achieved in cellular systems. Conventional cooperation techniques require sharing large amounts of information over finite-capacity backhaul links and assume that base stations…
Massive MIMO has been regarded as one of the key technologies for 5G wireless networks, as it can significantly improve both the spectral efficiency and energy efficiency. The availability of high-dimensional channel side information (CSI)…
Accurate and low-overhead channel state information (CSI) feedback is essential to boost the capacity of frequency division duplex (FDD) massive multiple-input multiple-output (MIMO) systems. Deep learning-based CSI feedback significantly…
Multiuser multiple-input multiple-output (MIMO) systems are a prime candidate for use in massive connection density in machine-type communication (MTC) networks. One of the key challenges of MTC networks is to obtain accurate channel state…
Extremely large-scale multiple-input multiple-output (XL-MIMO) systems are a key technology for future wireless networks, but the large array aperture naturally creates a hybrid-field (HF) propagation regime in which far-field (FF)…
In frequency-division duplexing (FDD) multiple-input multiple-output (MIMO) systems, obtaining accurate downlink channel state information (CSI) for precoding is vastly challenging due to the tremendous feedback overhead with the growing…
Deep learning based channel state information (CSI) feedback in frequency division duplex systems has drawn much attention in both academia and industry. In this paper, we focus on integrating the Type-II codebook in the beyond…
CSI feedback is an important problem of Massive multiple-input multiple-output (MIMO) technology because the feedback overhead is proportional to the number of sub-channels and the number of antennas, both of which scale with the size of…
Future sixth-generation (6G) systems are expected to leverage extremely large-scale multiple-input multiple-output (XL-MIMO) technology, which significantly expands the range of the near-field region. While accurate channel estimation is…
Recent advancements in information technology and the widespread use of the Internet have led to easier access to data worldwide. As a result, transmitting data through noisy channels is inevitable. Reducing the size of data and protecting…
Video Snapshot Compressive Imaging (SCI) aims to use a low-speed 2D camera to capture high-speed scene as snapshot compressed measurements, followed by a reconstruction algorithm to reconstruct the high-speed video frames. State-of-the-art…
Channel state information (CSI) acquisition is essential for the base station (BS) to fully reap the beamforming gain in intelligent reflecting surface (IRS)-aided downlink communication systems. Recently, [1] revealed a strong correlation…
This paper presents a novel compressed sensing (CS) approach to high dimensional wireless channel estimation by optimizing the input to a deep generative network. Channel estimation using generative networks relies on the assumption that…
For massive multiple-input multiple-output (MIMO) systems operating in frequency-division duplex mode, downlink channel state information (CSI) acquisition will incur large overhead. This overhead is substantially reduced when sparse…