In this paper, we develop a partner selection protocol for enhancing the network lifetime in cooperative wireless networks. The case-study is the cooperative relayed transmission from fixed indoor nodes to a common outdoor access point. A stochastic bivariate model for the spatial distribution of the fading parameters that govern the link performance, namely the Rician K-factor and the path-loss, is proposed and validated by means of real channel measurements. The partner selection protocol is based on the real-time estimation of a function of these fading parameters, i.e., the coding gain. To reduce the complexity of the link quality assessment, a Bayesian approach is proposed that uses the site-specific bivariate model as a-priori information for the coding gain estimation. This link quality estimator allows network lifetime gains almost as if all K-factor values were known. Furthermore, it suits IEEE 802.15.4 compliant networks as it efficiently exploits the information acquired from the receiver signal strength indicator. Extensive numerical results highlight the trade-off between complexity, robustness to model mismatches and network lifetime performance. We show for instance that infrequent updates of the site-specific model through K-factor estimation over a subset of links are sufficient to at least double the network lifetime with respect to existing algorithms based on path loss information only.
Real-World Deployment of Cloud-based Autonomous Mobility Systems for Outdoor and Indoor Environments
Department of Mechanical and Mechatronics Engineering, University of Waterloo（滑铁卢大学机械与机电工程系）；Technology Partnerships and Innovations, Rogers Communications, Canada Inc.（罗杰斯通讯加拿大有限公司技术伙伴关系与创新部）；Mechanical Engineering Department, University of Alberta（阿尔伯塔大学机械工程系）
Wireless-Friendly Window Position Optimization for RIS-Aided Outdoor-to-Indoor Networks based on Multi-Modal Large Language Model
Department of Electronic and Electrical Engineering, the University of Sheffield（电子与电气工程系，谢菲尔德大学）；Department of Computer Science and Technology, University of Cambridge（计算机科学与技术系，剑桥大学）；Brunel University London（伦敦布鲁内尔大学）；School of Information and Electronic Engineering, Zhejiang Gongshang University（信息与电子工程学院，浙江工商大学）；Design & Health Lab, Department of Architecture, Built Environment and Construction Engineering, Politecnico di Milano（设计与健康实验室，建筑、环境与土木工程系，米兰理工学院）；Department of Computer Science, Brunel University London（计算机科学系，伦敦布鲁内尔大学）；The State Key Laboratory of Synthetical Automation for Process Industries and The College of Information Science and Engineering, Northeastern University（过程工业综合自动化国家重点实验室和信息科学与工程学院，东北大学）；Centre for Wireless Innovation, Queen’s University of Belfast（无线创新中心，贝尔法斯特女王大学）
