A Recommendation System Approach for Interference-Robust Sensor Subset Selection

• URL: http://arxiv.org/abs/2608.11143v1
• Date: Tue, 11 Aug 2026 17:01:44 GMT
• Title: A Recommendation System Approach for Interference-Robust Sensor Subset Selection
• Abstract summary: We propose a recommendation-system-inspired framework for sensor-subset selection.<n>We show that the proposed method can improve accuracy by around 20% over the RSSI baseline.
• Score: 8.37368990705541
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This paper develops a method for sensor-subset selection for tracking. Prior work showed that low-cost acoustic Received Signal Strength Indicator (RSSI) measurements can be used to recommend subsets of sensor nodes whose expensive sensing modalities, such as cameras, can achieve high tracking accuracy. While efficient, RSSI-based approaches are challenged by acoustic interference. We propose a recommendation-system-inspired framework that instead leverages frequency-band acoustic features and a Two-Tower Multi-Layer Perceptron (MLP) architecture to efficiently score candidate sensor subsets. Experimental results on outdoor vehicle-tracking deployments show that the proposed method can improve accuracy by around 20\% over the RSSI baseline while maintaining the low computational overhead required for real-time selective sensing.

Related papers

• AmbSentry: Mitigating Sensing Eavesdropping in ISAC Systems by Harnessing Ambient IoT Devices [60.083979780396014]
  Integrated sensing and communication (ISAC) has emerged as a pivotal paradigm for 6G networks.<n>This paper proposes AmbSentry, an ISAC system that prevents the leakage of sensing information to sensing eavesdroppers.
  arXiv  Detail & Related papers  (2026-08-12T08:42:05Z)
• AmbShield: Enhancing Physical Layer Security with Ambient Backscatter Devices against Eavesdroppers [69.56534335936534]
  AmbShield is an AmBD-assisted PLS scheme that leverages naturally distributed AmBDs to simultaneously strengthen the legitimate channel and degrade eavesdroppers'<n>In AmbShield, AmBDs are exploited as friendly jammers that randomly backscatter to create interference at eavesdroppers, and as passive relays that backscatter the desired signal to enhance the capacity of legitimate devices.
  arXiv  Detail & Related papers  (2026-01-14T20:56:50Z)
• UAV Individual Identification via Distilled RF Fingerprints-Based LLM in ISAC Networks [60.16924915676577]
  Unmanned aerial vehicle (UAV) individual (ID) identification is a critical security surveillance strategy in low-altitude integrated sensing and communication (ISAC) networks.<n>We propose a novel dynamic knowledge distillation (KD)-enabled wireless radio frequency fingerprint large language model (RFF-LLM) framework for UAV ID identification.<n>Experiment results show that the proposed framework achieves 98.38% ID identification accuracy with merely 0.15 million parameters and 2.74 ms response time.
  arXiv  Detail & Related papers  (2025-08-18T03:14:44Z)
• Anti-Jamming Sensing with Distributed Reconfigurable Intelligent Metasurface Antennas [11.159180009266489]
  The sensing accuracy of traditional RF sensing methods is often affected by adverse propagation channels from the transmitter to the receiver, such as fading and noise.<n>In this paper, we propose employing distributed Reconfigurable Intelligent Meta Antennas (RIMSA) to detect the presence and location of objects.<n>We introduce a deep reinforcement learning (DRL) algorithm aimed at calculating the optimal beamforming patterns and a neural network aimed at converting received signals into sensing outcomes.
  arXiv  Detail & Related papers  (2025-08-07T01:33:38Z)
• Rydberg Atomic Quantum Receivers for Classical Wireless Communications and Sensing: Their Models and Performance [78.76421728334013]
  Rydberg atomic quantum receivers (RAQRs) are an eminent solution for detecting the electric field of radio frequency (RF) signals.<n>We introduce the RAQR to the wireless community by presenting an end-to-end reception scheme.<n>We then develop a corresponding equivalent baseband signal model relying on a realistic reception flow.
  arXiv  Detail & Related papers  (2024-12-07T06:25:54Z)
• High-Quality and Full Bandwidth Seismic Signal Synthesis using Operational GANs [13.94568670805613]
  We propose a novel, high-quality, and full bandwidth seismic signal synthesis by transforming the signal acquired from an inferior sensor. We employ 1D Operational Generative Adversarial Networks (Op-GANs) with novel loss functions to achieve this. The proposed method is extensively evaluated over the Simulated Ground Motion (SimGM) benchmark dataset.
  arXiv  Detail & Related papers  (2024-07-06T08:07:23Z)
• CoSS: Co-optimizing Sensor and Sampling Rate for Data-Efficient AI in Human Activity Recognition [5.215675032361843]
  Recent advancements in Artificial Neural Networks have significantly improved human activity recognition using multiple time-series sensors. While employing numerous sensors with high-frequency sampling rates usually improves the results, it often leads to data inefficiency and unnecessary expansion of the ANN. We introduce a pragmatic framework for data-efficient utilization in HAR tasks, considering the optimization of both sensor modalities and sampling rate simultaneously.
  arXiv  Detail & Related papers  (2024-01-03T22:04:40Z)
• A distributed neural network architecture for dynamic sensor selection with application to bandwidth-constrained body-sensor networks [53.022158485867536]
  We propose a dynamic sensor selection approach for deep neural networks (DNNs) It is able to derive an optimal sensor subset selection for each specific input sample instead of a fixed selection for the entire dataset. We show how we can use this dynamic selection to increase the lifetime of a wireless sensor network (WSN) by imposing constraints on how often each node is allowed to transmit.
  arXiv  Detail & Related papers  (2023-08-16T14:04:50Z)
• LoRD-Net: Unfolded Deep Detection Network with Low-Resolution Receivers [104.01415343139901]
  We propose a deep detector entitled LoRD-Net for recovering information symbols from one-bit measurements. LoRD-Net has a task-based architecture dedicated to recovering the underlying signal of interest. We evaluate the proposed receiver architecture for one-bit signal recovery in wireless communications.
  arXiv  Detail & Related papers  (2021-02-05T04:26:05Z)
• Deep Networks for Direction-of-Arrival Estimation in Low SNR [89.45026632977456]
  We introduce a Convolutional Neural Network (CNN) that is trained from mutli-channel data of the true array manifold matrix. We train a CNN in the low-SNR regime to predict DoAs across all SNRs. Our robust solution can be applied in several fields, ranging from wireless array sensors to acoustic microphones or sonars.
  arXiv  Detail & Related papers  (2020-11-17T12:52:18Z)
• Optimal control for quantum detectors [0.0]
  We find the optimal quantum control to detect an external signal in the presence of background noise using a quantum sensor. For white background noise, the optimal solution is the simple and well-known spin-locking control scheme. Results show that an optimal detection scheme can be easily implemented in near-term quantum sensors without the need for complicated pulse shaping.
  arXiv  Detail & Related papers  (2020-05-12T18:15:59Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.