{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T15:09:50Z","timestamp":1782745790442,"version":"3.54.5"},"reference-count":22,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2024,4,12]],"date-time":"2024-04-12T00:00:00Z","timestamp":1712880000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Students\u2019 Platform Innovation and Entrepreneurship Training Program Support Project","award":["202310300022Z"],"award-info":[{"award-number":["202310300022Z"]}]},{"name":"National Students\u2019 Platform Innovation and Entrepreneurship Training Program Support Project","award":["62101277"],"award-info":[{"award-number":["62101277"]}]},{"name":"National Nature Science Foundation of China","award":["202310300022Z"],"award-info":[{"award-number":["202310300022Z"]}]},{"name":"National Nature Science Foundation of China","award":["62101277"],"award-info":[{"award-number":["62101277"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In this paper, we consider an integrated sensing, communication, and computation (ISCC) system to alleviate the spectrum congestion and computation burden problem. Specifically, while serving communication users, a base station (BS) actively engages in sensing targets and collaborates seamlessly with the edge server to concurrently process the acquired sensing data for efficient target recognition. A significant challenge in edge computing systems arises from the inherent uncertainty in computations, mainly stemming from the unpredictable complexity of tasks. With this consideration, we address the computation uncertainty by formulating a robust communication and computing resource allocation problem in ISCC systems. The primary goal of the system is to minimize total energy consumption while adhering to perception and delay constraints. This is achieved through the optimization of transmit beamforming, offloading ratio, and computing resource allocation, effectively managing the trade-offs between local execution and edge computing. To overcome this challenge, we employ a Markov decision process (MDP) in conjunction with the proximal policy optimization (PPO) algorithm, establishing an adaptive learning strategy. The proposed algorithm stands out for its rapid training speed, ensuring compliance with latency requirements for perception and computation in applications. Simulation results highlight its robustness and effectiveness within ISCC systems compared to baseline approaches.<\/jats:p>","DOI":"10.3390\/s24082489","type":"journal-article","created":{"date-parts":[[2024,4,12]],"date-time":"2024-04-12T11:09:20Z","timestamp":1712920160000},"page":"2489","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Robust Offloading for Edge Computing-Assisted Sensing and Communication Systems: A Deep Reinforcement Learning Approach"],"prefix":"10.3390","volume":"24","author":[{"given":"Li","family":"Shen","sequence":"first","affiliation":[{"name":"School of Computer Science, Nanjing University of Information Science and Technology, Nanjing 210044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bin","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer Science, Nanjing University of Information Science and Technology, Nanjing 210044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaojie","family":"Zhu","sequence":"additional","affiliation":[{"name":"Division of Computer Science, King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,4,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1109\/MNET.011.2300046","article-title":"Task-Oriented Integrated Sensing, Computation and Communication for Wireless Edge AI","volume":"37","author":"Xing","year":"2023","journal-title":"IEEE Netw."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2085","DOI":"10.1109\/JSAC.2022.3157389","article-title":"Joint MIMO Precoding and Computation Resource Allocation for Dual-Function Radar and Communication Systems with Mobile Edge Computing","volume":"40","author":"Ding","year":"2022","journal-title":"IEEE J. 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