{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T05:23:36Z","timestamp":1787289816795,"version":"build-2736575974"},"reference-count":40,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2026,8,19]],"date-time":"2026-08-19T00:00:00Z","timestamp":1787097600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62473052"],"award-info":[{"award-number":["62473052"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"award":["62473052"],"award-info":[{"award-number":["62473052"]}],"id":[{"id":"https:\/\/ror.org\/01h0zpd94","id-type":"ROR","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100011202","name":"State Key Laboratory of Catalysis","doi-asserted-by":"publisher","award":["241-HF-D09-01"],"award-info":[{"award-number":["241-HF-D09-01"]}],"id":[{"id":"10.13039\/501100011202","id-type":"DOI","asserted-by":"publisher"}]},{"award":["241-HF-D09-01"],"award-info":[{"award-number":["241-HF-D09-01"]}],"id":[{"id":"https:\/\/ror.org\/04wsvdt21","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>After infrastructure disruption, an emergency wireless controller must meet urgent communication demand and preserve resources for later periods. We propose Scarcity-Coefficient Gated Projection Reinforcement Learning (SCGP-RL). It jointly selects total planning-layer activation and a regional capacity upper-bound vector. Scarcity and urgent-demand evidence shape the activation intent. Scalar and capped-simplex projections enforce the coupled action constraints. A planning capacity unit (PCU) is defined as a calibratable service-capacity quantum. In the common constrained evaluation, SCGP-RL reduced the unmet urgent-demand score from 0.6643 for Projected CPO to 0.4919. It also satisfied all the executed hard constraints. Component tests show that the urgent-demand gate drives rapid service response and that the marginal demand-relief estimate provides a smaller benefit. Binding-condition tests show that the power, backhaul, and node-health mechanisms protect the resources they represent.<\/jats:p>","DOI":"10.3390\/s26165248","type":"journal-article","created":{"date-parts":[[2026,8,19]],"date-time":"2026-08-19T11:04:12Z","timestamp":1787137452000},"page":"5248","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Scarcity-Coefficient Gated Projection Reinforcement Learning for Planning-Layer Capacity Activation in Emergency Wireless Networks"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-2139-4102","authenticated-orcid":false,"given":"Jingxiang","family":"Ma","sequence":"first","affiliation":[{"name":"School of Automation, Beijing Institute of Technology, Beijing 100081, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ping","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Automation, Beijing Institute of Technology, Beijing 100081, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5734-3157","authenticated-orcid":false,"given":"Hongbin","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Automation, Beijing Institute of Technology, Beijing 100081, China"},{"name":"Marine Science and Technology Domain, Beijing Institute of Technology, Zhuhai 519088, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guiping","family":"Lu","sequence":"additional","affiliation":[{"name":"Marine Science and Technology Domain, Beijing Institute of Technology, Zhuhai 519088, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2984-734X","authenticated-orcid":false,"given":"Youzhi","family":"Zhang","sequence":"additional","affiliation":[{"name":"Centre for Artificial Intelligence and Robotics, Hong Kong Institute of Science & Innovation, Chinese Academy of Sciences, Hong Kong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,8,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Wang, Q., Li, W., Yu, Z., Abbasi, Q., Imran, M., Ansari, S., Sambo, Y., Wu, L., Li, Q., and Zhu, T. 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