This paper introduces phase-to-primitive decomposition to enable Monte Carlo tree search (MCTS) on in-memory computing (IMC) systems, achieving significant energy efficiency and performance improvemen…

The paper proposes CLASP, an end-to-end system with IMC acceleration for continual learning on edge platforms, addressing challenges of noisy computation and poor support for resource-efficient traini…

This paper analyzes direction-of-arrival estimation using a tunable receive-side lossless reciprocal MiLAC combiner for antenna arrays and shows it can achieve the digital Cramér-Rao bound with fewer…

This paper proposes a vision-assisted OFDM-ISAC framework that fuses wireless and visual modalities to resolve ambiguity in multi-target scenarios and achieve better localization and delay performance…

The paper proposes a highly reconfigurable 256x128 in-memory computing array that significantly improves efficiency and performance for analog computing by introducing novel components for ADC, weight…

This paper proposes CoSMIC, a framework for semantic integrated sensing and communication (ISAC) that embeds semantic information into waveforms while maintaining covertness and sensing fidelity.

The paper proposes a novel radar-centric signaling design using index modulation and phase coding over FMCW chirps to simultaneously achieve robust physical layer security for data and enhance sensing…

This paper analyzes the privacy challenges posed by Integrated Sensing and Communication (ISAC) in 6G networks by classifying sensitive data into three levels (location, behavioral, and physiological)…

A neural network called DMSNet is proposed for multi-target sensing in multi-band integrated sensing and communication systems, improving accuracy, reducing errors, and decreasing runtime.

This paper reviews the core mechanisms of Wi-Fi 8, focusing on enhancements at the PHY and MAC layers, and explores the potential role of integrated millimeter-wave technology. It conducts system-leve…

This paper surveys how integrating Edge Computing, Machine Learning, and Deep Learning can enhance the security and resilience of complex Internet of Vehicles (IoV) networks.

This tutorial-style review focuses on kinematics of inertial measurement units (IMUs) for human motion capture and introduces methods to determine adequate formulations for sensor measurements.

The paper proposes the Communicating Finite Automata (CFA) abstraction and a framework for component program refactoring in large language model inference services, achieving significant speedup and r…

This paper proposes a Fisher information density (FID)-constrained trajectory sharing scheme for robot collision avoidance under GDPR regulations, achieving better privacy-utility tradeoff than fixed-…

This paper compares the performance of open-loop and closed-loop filters in inertial navigation systems using simulations.

This paper surveys information-theoretic approaches to secure Integrated Sensing and Communication (ISAC), providing a comprehensive review of models, security formulations, and fundamental limits.

This paper proposes a hybrid TRP-UE sensing mechanism for Integrated Sensing and Communication (ISAC) systems to improve network-based sensing performance in challenging indoor factory environments.

TimeMark proposes a trustworthy time watermarking framework that uses cryptographic techniques and error-correcting codes to achieve 100% accurate recovery of the generation time from AIGC, resisting…

IstGPT introduces a novel LLM-based framework for real-time, fine-grained anomaly detection in complex industrial cyber-physical systems, achieving state-of-the-art performance across multiple benchma…