arXiv subjects

Weijiang Zhao

Publications and source records attributed to Weijiang Zhao.

6 recordsLinked to original sources

arXiv2026

Exact Degrees of Freedom of Spatially Sparse MIMO Channels Without Prior CSI

We characterize the degree of freedom (DoF) of a point-to-point blockwise memoryless channel without prior channel state information (CSI), with a fixed number $K$ of propagation paths, where the transmitter (Tx) and the receiver (Rx) are equipped with nonuniform linear arrays (NULAs) of $N_t$ and $N_r$ antennas, respectively. The positions of array elements are fixed, known, pairwise distinct, and need not be equally spaced. The uniform linear array (ULA) is a special case. In each block of length $T$, the continuous angles of arrival (AoAs), angles of departure (AoDs), and independent complex Gaussian path gains are redrawn. Both Tx and Rx know the state distributions but are not given the current realizations before transmission. The receiver may estimate the channel from reference signals or decode without explicit channel estimation, with reference symbols counted in $T$ and their energy counted against the power constraint. Under the aforementioned model, we show that the DoF is $1-\frac{1}{T}$ for $K=1$, and $K(1-\frac{3}{2T})$ for $K \geq 2$, when $N_r\ge K+1$, $N_t\ge\max\{K,2\}$, and $T\ge K$. The analytical results are further demonstrated by their applications to the DoF tradeoff analysis in integrated sensing and communication (ISAC). For more general array structures, an achievability result is established, while the converse remains open in general.

cs.IT↗

arXiv2026

Auto-correlation Function Keying

We propose ACFK: Auto-correlation Function Keying, a new integrated sensing and communication (ISAC) waveform that carries random communication data while directly controlling the peak sidelobe level (PSL) of the periodic auto-correlation function (P-ACF). In contrast to existing works aiming at controlling the expected sidelobe level (ESL), which fails to characterize realization-specific sidelobe behaviors, we formulate a mutual information maximization problem under PSL and power constraints, and show that a continuous ACF-domain uniform distribution is asymptotically optimal at high signal-to-noise ratio (SNR) over quasi-static frequency-flat channels. Motivated by this principle, ACFK maps finite-constellation symbols onto auto-correlation function (ACF)-domain sidelobes and uses independent phase symbols to exploit the remaining degrees of freedom. The resulting waveform enables exact control of the nominal P-ACF, which coincides with the actual P-ACF when the power spectral non-negativity condition is satisfied. We further analyze the non-negativity violation probability and bound the corresponding peak sidelobe level ratio (PSLR) degradation. A reference ISAC transceiver and its high-SNR approximate bit error rate (BER) analysis are also provided. Numerical results show that ACFK achieves stronger PSLR control, and improved weak-target detection performance, than a generalized probabilistic amplitude shaping (PAS) baseline at similar data rate and BER.

cs.IT↗

arXiv2026

Input Distribution Design for Ranging-Oriented OFDM-ISAC Systems Under Frequency-Selective Fading

The implementation of the \ac{isac} feature in \ac{6g} networks is most likely to be based on the framework of \ac{ofdm}. Input distribution design, or constellation design, is a crucial technique in \ac{ofdm}-\ac{isac} systems enabling a favorable balance between communication rate and sensing performance. In this treatise, we propose a computationally efficient input distribution design approach for \ac{ofdm}-\ac{isac} under frequency-selective channels, following the theoretical framework of capacity distortion. We highlight that under practical sensing constraints, the optimal strategy is to treat the kurtosis of constellations as a resource, and allocate it appropriately over subcarriers.

cs.IT↗

arXiv2026

Physics-Informed Uncertainty Enables Reliable AI-driven Design

Inverse design is a central goal in much of science and engineering, including frequency-selective surfaces (FSS) that are critical to microelectronics for telecommunications and optical metamaterials. Traditional surrogate-assisted optimization methods using deep learning can accelerate the design process but do not usually incorporate uncertainty quantification, leading to poorer optimization performance due to erroneous predictions in data-sparse regions. Here, we introduce and validate a fundamentally different paradigm of Physics-Informed Uncertainty, where the degree to which a model's prediction violates fundamental physical laws serves as a computationally-cheap and effective proxy for predictive uncertainty. By integrating physics-informed uncertainty into a multi-fidelity uncertainty-aware optimization workflow to design complex frequency-selective surfaces within the 20 - 30 GHz range, we increase the success rate of finding performant solutions from less than 10% to over 50%, while simultaneously reducing computational cost by an order of magnitude compared to the sole use of a high-fidelity solver. These results highlight the necessity of incorporating uncertainty quantification in machine-learning-driven inverse design for high-dimensional problems, and establish physics-informed uncertainty as a viable alternative to quantifying uncertainty in surrogate models for physical systems, thereby setting the stage for autonomous scientific discovery systems that can efficiently and robustly explore and evaluate candidate designs.

cs.LG↗

arXiv2023

A Surrogate-Assisted Extended Generative Adversarial Network for Parameter Optimization in Free-Form Metasurface Design

Metasurfaces have widespread applications in fifth-generation (5G) microwave communication. Among the metasurface family, free-form metasurfaces excel in achieving intricate spectral responses compared to regular-shape counterparts. However, conventional numerical methods for free-form metasurfaces are time-consuming and demand specialized expertise. Alternatively, recent studies demonstrate that deep learning has great potential to accelerate and refine metasurface designs. Here, we present XGAN, an extended generative adversarial network (GAN) with a surrogate for high-quality free-form metasurface designs. The proposed surrogate provides a physical constraint to XGAN so that XGAN can accurately generate metasurfaces monolithically from input spectral responses. In comparative experiments involving 20000 free-form metasurface designs, XGAN achieves 0.9734 average accuracy and is 500 times faster than the conventional methodology. This method facilitates the metasurface library building for specific spectral responses and can be extended to various inverse design problems, including optical metamaterials, nanophotonic devices, and drug discovery.

cs.LG↗

arXiv2014

The discharge characteristics of the DUHOCAMIS with a high magnetic bottle-shaped field

For the purpose to produce high intensity, multiply charged metal ion beams, the DUHOCAMIS (dual hollow cathode ion source for metal ions) was derived from the hot cathode Penning ion source combined with the hollow cathode sputtering experiments in 2007. It was interesting to investigate the behavior of this discharge geometry in a stronger magnetic bottle-shaped field. So a new test bench for DUHOCAMIS with a high magnetic bottle-shaped field up to 0.6 T has been set up at Peking University, on which have been made primary experiments in connection with discharge characteristics of the source. The experiments with magnetic fields from 0.13 T to 0.52 T have shown that the magnetic flux densities are very sensitive to the discharge behavior: discharge curves and ion spectra. It has been found that the slope of discharge curves in a very wide range can be controlled by changing the magnetic field as well as regulated by adjusting cathode heating power. On the other hand, by comparison of discharge curves between dual hollow cathode discharge (DHCD) mode and PIG discharge mode, it was found a much stronger magnetic effect occurred on DHCD mode. In this paper, the new test bench with ion source structure is described in detail; and main experimental results are presented and discussed, including the effects of cathode heating power and magnetic flux density on discharge characteristics, also the ion spectra. The effects of the magnetic field on the source operating are emphasized, and a unique behavior of the DUHOCAMIS operating in the high magnetic field is expected and discussed especially.

physics.acc-ph↗