Integrated sensing, communication, and computation (ISCC) enables next-generation wireless networks to perform environmental perception while processing massive data under stringent quality-of-service (QoS) requirements. Energy consumption is a crucial indicator for the ISCC system design. However, accounting for energy heterogeneity in ISCC system design is an open problem. Specifically, battery-constrained user equipments (UEs) and energy-abundant access points (APs) require fundamentally different energy allocation strategies based on device computational capabilities, battery states, and QoS constraints. In this paper, we introduce a nonconvex energy cost minimization problem by considering a user-specific energy cost ratio coefficient that explicitly balances UE-AP energy consumption according to heterogeneous device energy states. To efficiently address this problem, a double-loop framework combining successive convex approximation and alternating direction method of multipliers is also developed. Numerical results demonstrate that the proposed scheme significantly outperforms the fixed offloading baselines (full offloading, full local and half offloading) in terms of the total energy cost. In particular, the proposed scheme achieves up to $25-47.6\%$ energy cost reduction at moderate latency constraints over fixed offloading baselines, thereby supporting time-sensitive applications. Moreover, this work provides an effective solution for energy-efficient and QoS-aware 6G ISCC systems serving diverse devices with conflicting energy priorities.
Kai Dong, Lei Wang, S. Vorobyov et al.· IEEE Transactions on Wireles...· 0 citations
Space–air–ground integrated networks (SAGINs) break through the coverage and capacity limitations of terrestrial networks, providing seamless, high-bandwidth, and highly reliable communication services in remote areas. For end-to-end transmission in the Internet of Things (IoT), the store-and-forward architecture transmits data packets in a best-effort way, resulting in unpredictable latency. The exclusive occupation of links by flows leads to a significant drop in resource utilization. To satisfy deterministic end-to-end communication, this article proposes a quality-of-service (QoS)-aware end-to-end transmission architecture for SAGINs. It comprises two core types of links: access links assisted by high-altitude platforms (HAPs) and backhaul links built around the low-Earth orbit (LEO) satellite. End-to-end flows will be allocated time slots and transmitted hop-by-hop within a single frame to meet deterministic QoS requirements. In this architecture, an optimization problem is designed to maximize the number of successfully scheduled flows with different QoS requirements. To solve the non-deterministic polynomial hard (NP-hard) mixed-integer nonlinear program in dynamic scheduling scenarios, a joint access and transmission heuristic algorithm is proposed. Specifically, to ensure efficient transmission and improve resource utilization, concurrent end-to-end flows are first processed with conflict filtering, followed by hop-by-hop scheduling with the priority based on the least number of required time slots. The simulation results show that, compared to other baseline schemes, the proposed scheme achieves a significant improvement in scheduling performance.
Chen-Yan Lei, Yong Niu, Zhu Han et al.· IEEE Internet of Things Jour...· 0 citations
Uncrewed aerial vehicles (UAVs) integrated with integrated sensing and communication (ISAC) technology have emerged as a compelling platform for sixth-generation (6G) wireless networks, leveraging three-dimensional mobility to perform simultaneous sensing and communication (S&C) across applications ranging from disaster response to airspace monitoring. While the field has advanced rapidly, existing surveys have not sufficiently characterized UAV-specific design challenges nor the cross-cutting trade-offs governing practical deployment. To bridge this gap, this survey provides a systematic review across six interconnected domains—channel estimation (CE) and beam tracking, throughput maximization, weighted sum rate (WSR) and sensing co-optimization, delay and age of information (AoI) minimization, energy efficiency (EE), and PLS—each supported by a structured comparative table covering over 80 methodologies. The survey concludes with a research roadmap addressing propagation modeling, platform dynamics, imperfect channel state information (CSI) robustness, energy-AoI-security co-design, and standardization, providing a structured foundation for future 6G UAV-ISAC research.
Manzoor Ahmed, Syed Tariq Shah, A. A. Nasir et al.· IEEE Open Journal of the Com...· 1 citation
Nowadays, split federated learning (SFL) has emerged as an effective paradigm for enabling privacy-preserving collaborative intelligence across heterogeneous devices with limited computation. However, SFL incurs significant communication overhead in wireless networks due to the uplink transmission of high-dimensional smashed data, which degrades network efficiency. To mitigate the communication bottleneck, we propose a prototype-based SFL framework ProtoSFL. Specifically, each selected client computes local prototypes for observed classes and uploads them to the server. Based on the received prototypes, the server derives global prototypes and optimizes a weighted objective that combines classification loss with prototype alignment loss. The server then updates the model accordingly and returns personalized prototype gradients to the clients. Simulation results verify the effectiveness of ProtoSFL in reducing communication overhead, achieving a substantial reduction in uplink communication, while maintaining competitive testing accuracy under various heterogeneous data settings compared with SFL baselines.