信号处理
We improve the accuracy of the GN Polynomial Closed-Form Model (PCFM) by incorporating the spectral NLI PSD and the coherent accumulation along the link. The proposed model is capable of accurately evaluating the NLI over any rectangular…
Aero-optic effects due to turbulence can reduce the effectiveness of transmitting light waves to a distant target. Methods to compensate for turbulence typically rely on realistic turbulence data, which can be generated by i) experiment,…
Conventional mobile networks, including both localized cell-centric and cooperative cell-free networks (CCN/CFN), are built upon rigid network topologies. However, neither architecture is adequate to flexibly support distributed integrated…
We present zea (pronounced ze-yah), a Python package for cognitive ultrasound imaging that offers a flexible, modular, and differentiable pipeline for ultrasound data processing. Additionally, it includes a collection of pre-defined models…
Emerging sixth-generation wireless systems are increasingly heterogeneous, with compatibility across diverse configurations, ubiquitous coverage, and expanded functionalities. Although deep learning has substantially benefited wireless…
Conventional radar segmentation research has typically focused on learning category labels for different moving objects. Although fundamental differences between radar and optical sensors lead to differences in the reliability of predicting…
In this paper, a green learning (GL)-based precoding framework is proposed for simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-aided millimeter-wave (mmWave) MIMO broadcasting systems. Motivated by…
Surgical resection is the primary treatment option for brain tumor patients, but it carries the risk of postoperative cognitive impairments. This study investigates how tumor-induced alterations in presurgical neural dynamics relate to…
Modeling signals as linear combinations of atoms from a dictionary is ubiquitous in modern signal processing. In the finite-dimensional setting, whenever atoms depend nonlinearly upon unknown parameters, the signal model is said to be…
This paper studies location privacy in uplink MIMO systems, where a user equipment seeks to spoof the angular signature observed by a single base station performing localization. We propose a blind analog precoder design that manipulates…
As global fossil fuel reserves diminish, there's a growing impetus for nations to transition towards renewable energy sources. Sri Lanka, for instance, aims to generate 70% of its electricity from renewable sources by 2030. Achieving this…
We investigate multi-objective adaptive beamformer design strategies for non-invasive microwave hyperthermia. Our focus is to address the challenges of maintaining focused power deposition in desired locations while reducing unwanted…
Time Series Foundation Models (TSFMs) advance generalization and data efficiency in time series forecasting by unified large-scale pretraining. But TSFMs remain lacking when adapting to specific downstream forecasting tasks for two reasons.…
AI-enhanced interference rejection in radio frequency (RF) transmissions has recently attracted interest because deep learning approaches trained on both the signal of interest (SOI) and the signal mixture (SOI plus interference) can…
This paper investigates the fundamental limits of integrated sensing and communication (ISAC) systems with 1-bit receiver quantization. We analyze a Gaussian fading ISAC channel with separate communication and monostatic sensing links,…
Non-line-of-sight (NLOS) sensing has the potential to enable use cases like intrusion detection in occluded areas, increasing the value provided by Integrated Sensing and Commu- nications (ISAC) in future 6G cellular networks. In this…
Inter-satellite-link-enabled low-Earth-orbit (LEO) satellite constellations are evolving toward networked architectures that support constellation-level cooperation, enabling multiple satellites to jointly serve user terminals through…
Cell-free massive multiple-input multiple-output (MIMO) is a key technology for next-generation wireless systems. The integration of cell-free massive MIMO within the open radio access network (O-RAN) architecture addresses the growing need…
We develop a new class of distance-aware error bounds that tightly characterize the approximation error of spline neural networks. Our bottom-up approach analyzes the error bound of each neuron (a spline) and then extends it to the full…
The proliferation of capable and efficient machine learning (ML) models marks one of the strongest methodological shifts in signal processing (SP) in its nearly 100-year history. ML models support the development of SP systems that…