2026· IEEE Transactions on Communications· Vol 74, pp. 12720-12737· 0 citations· 43 references
Abstract
Distinct from conventional integrated sensing and communication (ISAC) techniques, breakthroughs in LoRa-aided ISAC achieve hardware-unified sensing and communication capabilities for low-power devices. By combining such a novel technology with wireless power transfer (WPT), it yields wireless powered sensing and communication networks (WPSCNs). Information fusion, a widely adopted technique in such networks, relies heavily on the fresh fused information for effective system decision-making. However, age of information (AoI) is ineffective for measuring freshness of fused information. To tackle this dilemma, a novel metric, age of sensing (AoS), is introduced. Specifically, we study timeliness of a WPSCN, where a fusion center (FC) wirelessly powers sensing nodes (SNs) to collect sensing information from the SNs for generating fused information. Moreover, the impact of multi-cycle sensing on the AoS is first explored in the WPSCNs. We also adopt the adaptive transmission strategy for flexibly reducing the transmission duration. After obtaining a closed-form of the average AoS, it is then minimised by optimising WPT duration, multi-cycle sensing strategy and the SN locations. Ultimately, the numerical results validate the accuracy of our theoretical analysis. The effect of multi-cycle sensing and the superiority of adaptive transmission strategy are also demonstrated. Our findings offer valuable insights for analysing and improving the fusion system timeliness, and provide a theoretical foundation for the practical deployment of the WPSCNs.
The integration of artificial intelligence (AI), reconfigurable intelligent surfaces (RIS), and integrated sensing and communication (ISAC) is emerging as a key enabler for intelligent, adaptive, and efficient wireless networks in the 6G era. This survey provides a comprehensive and well-structured overview of how AI is revolutionizing RIS-assisted ISAC by enabling dynamic, data-driven control over the radio environment. Through intelligent configuration of RIS, AI facilitates real-time adaptation of signal propagation paths, enhances sensing resolution, and ensures robust communication performance across diverse and dynamic network conditions. The discussion is organized across two major domains: terrestrial networks (TNs) and non-terrestrial networks (NTNs). In TNs, we examine four critical directions: (i) improving EE, (ii) strengthening security, (iii) achieving high sensing accuracy and low communication latency via joint optimization, and (iv) maximizing throughput. In NTN domain, especially within UAV-based platforms, we explore AI-RIS frameworks that support coordinated sensing and communication, reinforce link security in mobile and unpredictable environments, and enhance aerial network capacity through real-time RIS tuning. By bridging both terrestrial and aerial applications, this survey highlights how AI-driven RIS control enables environment-aware, low-latency, and secure ISAC operations. Finally, we identify and analyze key challenges such as managing trade-offs between sensing and communication, generalizing AI models across varied network scenarios, and ensuring scalable, low-complexity real-time deployment. The work concludes with forward-looking insights into future research directions essential for realizing robust and intelligent RIS-assisted ISAC architectures in 6G and beyond.
Shabeer Ahmad, Jinli Zhang, Manzoor Ahmed et al.· Journal of King Saud Univers...· 0 citations
In recent years, as the development of wireless communication technologies and the increase in smart devices rapidly, the shortage of spectrum resources has become the important issue for future wireless communication systems. Cognitive Radio (CR) enabled spectrum utilization through Dynamic Spectrum Access (DSA) which allowing unlicensed users to access licensed spectrum without interference. Cooperative Spectrum Sensing (CSS) which is an important part of cognitive radio systems to improve the sensing reliability by allowing multiple nodes shared sensing results and made a joint decision. In practical scenarios, CSS systems always faced several non-ideal data issues which include noise uncertainty, data missing, transmission errors, hardware impairments, and synchronization problems. These problems will distort sensing statistics, to reduce the detection probability, increase false alarm probability, and reduce the benefit of gain from cooperative. Therefore, this paper investigates how non-ideal data affects CSS systems and reviews several representative methods, including adaptive threshold detection, robust detection methods, data recovery techniques, synchronization correction, and uncertainty-aware fusion. The comparison results indicate that robust and intelligent cooperative methods can provide better sensing performance than traditional energy detection method under practical non-ideal conditions, especially in terms of detection probability, false alarm control, and overall system robustness. In addition, this paper discusses potential future research directions for intelligent cooperative sensing and explores the emerging technology such as potential influence of 6G networks and IoT, which may influence the development of CSS system.
Zhihan Yao· Applied and Computational En...· 0 citations
A unified technical perspective is provided on current standardization choices, their implementation tradeoffs, and the open challenges shaping network-grade sensing by connecting the evolving 3GPP architecture and radio studies across 5G-Advanced and 6G.
Experimental findings indicate that TFL achieves quicker convergence and delivers a superior weighted ISAC utility for users, alongside improved communication and sensing performance, and a more potent blend of communication-sensing advantages compared to per-cell learning, standard federated learning, privacy-compromising federated learning, and mobility-aware federated learning approaches.
Jillella Venkateswara Rao· Journal of Intelligent Decis...· 0 citations
Integrated sensing and communications (ISAC) is emerging as a major architectural direction for next-generation wireless systems. By jointly designing environmental sensing and wireless data transmission within a unified framework, ISAC offers the potential for simultaneous gains in spectral efficiency, hardware reuse, energy efficiency, and situational awareness. This paper provides a comprehensive research roadmap for ISAC, tracing its evolution from radar–communication coexistence to dual-function radar–communication architectures, networked sensing infrastructures, and perceptive sixth-generation (6G) wireless networks. The survey is organized around five pillars: information-theoretic foundations, physical-layer design, networked operation, enabling platform technologies, and application domains. It further examines emerging regimes and deployment extensions that challenge conventional assumptions, including near-field operation, terahertz systems, AI-native transceivers, reconfigurable and digital-twin-assisted environments, low-power and backscatter-based sensing, and non-terrestrial ISAC. Across these topics, the paper identifies open gaps, formulates a unified set of grand research challenges, reviews representative prototype and measurement-oriented studies, and outlines both near-term deployment paths and longer-horizon transformative directions. The goal is to provide a coherent reference and roadmap for the continued development of ISAC as a foundation for future wireless, sensing, and cyber-physical systems.
I. F. Akyildiz, Shih-Chun Lin· IEEE Access· 0 citations
In recent years, integrated sensing and communication (ISAC) has attracted significant attention towards future cellular networks. Currently, various works have demonstrated sensing performance in existing wireless communication systems. Most of the demonstrations are based on passive type due to the radio regulatory. However, because of the difficulty in access to the communication protocol stacks in commercial cellular systems, the evaluation of the cellular communication signals for semi-cooperative passive ISAC is limited. In this paper, a semi-cooperative passive ISAC system is developed with open-source 5G framework and software-defined radio devices. And the performance is experimentally evaluated by utilizing the physical layer information of actual 5G signals from the developed system. In this system, communication is established with 5G signals and physical layer information are obtained and extracted for analysis. The performance of the system is verified by conducting experiments under several communication scenarios including the synchronization, pinging, and data transmission. Different physical layer information is collected, and the propagation characteristics are analyzed by a multi-path configuration. The experiment results demonstrated that variable bandwidths were utilized for different communication scenarios and the multipath was successfully detected with two different approaches. These results show that the developed system is promising for semi-cooperative passive ISAC in wider application fields
Unknown authors· 0 citations
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