Related papers: Sim2Real Deep Transfer for Per-Device CFO Calibrat…
The next generation wireless communication networks are required to support high-mobility scenarios, such as reliable data transmission for high-speed railways. Nevertheless, widely utilized multi-carrier modulation, the orthogonal…
Complete awareness of the wireless environment, crucial for future intelligent networks, requires sensing all transmitted signals, not just the strongest. A fundamental barrier is estimating the target signal when it is buried under strong…
Distributing Transformer inference across embedded edge devices can alleviate individual memory and compute constraints, yet practical benefits on real hardware remain unclear: prior work relies largely on simulations that overlook…
In orthogonal-frequency division multiplexing (OFDM) systems, carrier and sampling frequency offsets (CFO and SFO, respectively) can destroy the orthogonality of the subcarriers and degrade system performance. In the literature, Nguyen-Le,…
The proliferation of Internet-of-Things (IoT) devices and cloud-computing applications over siloed data centers is motivating renewed interest in the collaborative training of a shared model by multiple individual clients via federated…
Orthogonal time frequency space (OTFS) modulation stands out as a promising waveform for sixth generation (6G) and beyond wireless communication systems, offering superior performance over conventional methods, particularly in high-mobility…
Orthogonal Frequency Division Multiplexing (OFDM) combined with Multiple-Input Multiple-Output (MIMO) techniques forms the backbone of modern wireless communication systems. While offering high spectral efficiency and robustness,…
Nonlinear effects have been considered as the major limitations in coherent optical (CO) fiber transmission system. DSP based CO receiver with digital backpropagation (DBP) method has recently facilitated the compensation of fiber nonlinear…
Recently, there has been an explosive growth of mobile and embedded applications using convolutional neural networks(CNNs). To alleviate their excessive computational demands, developers have traditionally resorted to cloud offloading,…
The combination of the effects of Doppler frequency shifts (due to mobility) and phase noise (due to the imperfections of oscillators operating at a high carrier frequency) poses serious challenges to Orthogonal Frequency Division…
Channel denoising is a practical and effective technique for mitigating channel estimation errors in multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) systems. However, adapting denoising techniques to…
Efficient real-time disparity estimation is critical for the application of stereo vision systems in various areas. Recently, stereo network based on coarse-to-fine method has largely relieved the memory constraints and speed limitations of…
In frequency-division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems, downlink channel state information (CSI) needs to be sent back to the base station (BS) by the users, which causes prohibitive feedback overhead.…
This paper investigates the impact of carrier frequency offset (CFO) on the performance of different MIMO-OFDM schemes with high spectral efficiency for next generation of terrestrial digital TV. We show that all studied MIMO-OFDM schemes…
In multiple-input multiple-output (MIMO) systems, the high-resolution channel information (CSI) is required at the base station (BS) to ensure optimal performance, especially in the case of multi-user MIMO (MU-MIMO) systems. In the absence…
Machine learning (ML) starts to be widely used to enhance the performance of multi-user multiple-input multiple-output (MU-MIMO) receivers. However, it is still unclear if such methods are truly competitive with respect to conventional…
Unleashing the full potential of massive MIMO in FDD mode by reducing the overhead of CSI feedback has recently garnered attention. Numerous deep learning for massive MIMO CSI feedback approaches have demonstrated their efficiency and…
Extending terrestrial networks into low-altitude airspace is a practical way to support aerial services, and accurate low-altitude radio maps are essential for characterizing terrestrial base station (BS) coverage and guiding system design.…
Orthogonal frequency-division multiplexing (OFDM) is widely used in modern wireless networks thanks to its efficient handling of multipath environment. However, it suffers from a poor peak-to-average power ratio (PAPR) which requires a…
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…