相关论文: Scalable Cross-Attention Transformer for Cooperati…
This paper focuses on a typical uplink transmission scenario over multiple-input multiple-output multiple access channel (MIMO-MAC) and thus propose a multi-user learnable CSI fusion semantic communication (MU-LCFSC) framework. It…
Combined with space-time coding, the orthogonal frequency division multiplexing (OFDM) system explores space diversity. It is a potential scheme to offer spectral efficiency and robust high data rate transmissions over frequency-selective…
In this letter, we analyze the performance of mixed coherent and non-coherent transmissions approach, which can improve the performance of cell-free multiple-input multiple-output orthogonal frequency division multiplexing (CF mMIMO-OFDM)…
The Transformer architecture aggregates input information through the self-attention mechanism, but there is no clear understanding of how this information is mixed across the entire model. Additionally, recent works have demonstrated that…
We consider a MIMO interference channel in which the transmitters and receivers operate in frequency-division duplex mode. In this setting, interference management through coordinated transceiver design necessitates channel state…
Given the rapid development of 3D scanners, point clouds are becoming popular in AI-driven machines. However, point cloud data is inherently sparse and irregular, causing significant difficulties for machine perception. In this work, we…
Integrated sensing and communication (ISAC) has been envisioned as a solution to realize the sensing capability required for emerging applications in wireless networks, while efficiently utilizing the available spectral, hardware and energy…
The Single Carrier-Frequency Division Multiple Access (SC-FDMA) is a transmission technique used in the uplink of Long Term Evolution (LTE) and 5G systems, as it is characterized by reduced transmitted signal envelope fluctuations in…
We develop a pragmatic multi-user (MU) massive multiple-input multiple-output (MIMO) channel model tailored to the THz band, encompassing factors such as molecular absorption, reflection losses and multipath diffused ray components. Next,…
Uplink sensing is still a relatively unexplored scenario in integrated sensing and communication which can be used to improve positioning and sensing estimates. We introduce a pilot-based maximum likelihood, and a maximum a posteriori…
True-time delayers (TTDs) are popular analog devices for facilitating near-field wideband beamforming subject to the spatial-wideband effect. In this paper, an adaptive TTD configuration is proposed for short-range TTDs. Compared to the…
The dominant sequence transduction models are based on complex recurrent or convolutional neural networks in an encoder-decoder configuration. The best performing models also connect the encoder and decoder through an attention mechanism.…
This paper considers coordinated linear precoding in downlink multicell multiuser orthogonal frequency-division multiple access (OFDMA) network. A less-complex, fast and provably convergent algorithm that maximizes the weighted sum-rate…
Multivariate time series (MTS) analysis prevails in real-world applications such as finance, climate science and healthcare. The various self-attention mechanisms, the backbone of the state-of-the-art Transformer-based models, efficiently…
Machine learning (ML) can be used in various ways to improve multi-user multiple-input multiple-output (MU-MIMO) receive processing. Typical approaches either augment a single processing step, such as symbol detection, or replace multiple…
Transformers have achieved remarkable success across diverse domains, but their monolithic architecture presents challenges in interpretability, adaptability, and scalability. This paper introduces a novel modular Transformer architecture…
How to reduce the pilot overhead required for channel estimation? How to deal with the channel dynamic changes and error propagation in channel prediction? To jointly address these two critical issues in next-generation transceiver design,…
Transformer-based models have brought a radical change to neural machine translation. A key feature of the Transformer architecture is the so-called multi-head attention mechanism, which allows the model to focus simultaneously on different…
Inter-cell interference (ICI) suppression is critical for multi-cell multi-user networks. In this paper, we investigate advanced precoding techniques for coordinated multi-point (CoMP) with downlink coherent joint transmission, an effective…
Distributed machine learning (ML) over wireless networks hinges on accurate channel state information (CSI) and efficient exchange of high-dimensional model updates. These demands are governed by channel coherence time and bandwidth, which…