Integrated sensing and communication (ISAC) enables simultaneous communication and environmental sensing in unmanned aerial vehicle (UAV) networks, but its performance is constrained by the physical antenna aperture and residual self-interference (SI) in full-duplex (FD) sensing. To address these issues, we propose a shared-aperture ISAC architecture in which a sparse co-prime array (CPA) is embedded in a uniform linear array (ULA) grid for FD sensing, while the remaining antenna positions support time-division duplexing (TDD) communication. We characterize the sensing performance through an order-wise Cramer-Rao bound (CRB) analysis, showing that the CPA achieves a stronger asymptotic sensing gain than the partitioned ULA benchmark in both single-target and nondegenerate multi-target scenarios. We further reveal a space-time sampling tradeoff under the same physical aperture. Based on the proposed architecture, we formulate a non-convex joint resource allocation problem that maximizes the weighted downlink-uplink sum rate by jointly designing the sensing transmit covariance, downlink precoder, and uplink receive beamformers under sensing accuracy, BS transmit-power, communication QoS, and residual SI constraints. An alternating-optimization-based algorithm is developed. Simulations demonstrate consistent performance gains over the considered baselines and confirm the complementary benefits of the CPA virtual aperture and sensing covariance optimization.
Jing Zhang, Yuxi Liu, Jiayi Sun et al.· 0 citations
Emerging technologies including wireless power transfer (WPT), integrated sensing and communication (ISAC), and fluid antennas (FAs), have significantly advanced the capabilities and performance of modern satellite communication systems. This paper investigates an FA-assisted integrated sensing, communication, and power transfer (ISCPT) framework for low Earth orbit (LEO) satellite networks, which operates in two phases: 1) an energy-transfer and target-sensing phase (Phase I), and 2) an information-transmission phase (Phase II). Specifically, in Phase I, a space solar power satellite (SSPS) transmits a dual-functional waveform to simultaneously charge multiple LEO satellites and illuminate a sensing target, while in Phase II, these LEO satellites coordinately serve multiple ground user equipments (UEs) leveraging the harvested energy. We formulate a sum-rate maximization problem subject to the SSPS’s transmit power constraint, LEO satellites’ energy harvesting and sensing requirements, UEs’ information rate demands, and the FAs’ movable regions. To tackle the highly-coupled and non-convex optimization problem, a three-stage alternating optimization (AO) algorithm is proposed, which decomposes it into resource allocation, SSPS-side FA placement, and LEO-side FA placement subproblems. In particular, the resource allocation subproblem is reformulated by adopting the Cauchy–Schwarz inequality and semidefinite relaxation (SDR), and is efficiently tackled via the successive convex approximation method. The two FA placement subproblems are addressed leveraging trust-region-based optimization. Simulation results validate the superior performance gains of the proposed algorithm over seven benchmarks and demonstrate that FAs can enhance multi-functional wireless services by adjusting inter-channel diversity according to service types. Notably, a non-trivial trade-off arises among FAs-enabled multi-functional services requiring distinct channel characteristics, as FAs cannot simultaneously provide optimal channel conditions for all services.
Weihao Mao, Yang Lu, Dong Yang et al.· IEEE Journal on Selected Are...· 1 citation
Integrated sensing and communication (ISAC) under a cell-free (CF) architecture enables seamless connectivity and sensing coverage by allowing multiple distributed access points (APs) to jointly serve users and detect targets, thereby mitigating cell-edge effects and enhancing spatial diversity. However, wideband CF-ISAC also suffers from frequency-selective fading and strong inter-AP interference. To address these challenges, we investigate a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-assisted ISAC framework, which extends full-space coverage and mitigates multiplicative fading and blockage effects. A joint optimization strategy is developed to maximize the weighted ISAC joint rate by jointly optimizing bandwidth and power allocation, receive beamforming, and active STAR-RIS beamforming. To tackle the non-convexity caused by variable coupling and intricate constraints, an efficient alternating optimization algorithm is developed. The original problem is decomposed into several subproblems: first, a closed-form solution for receive beamforming is derived; next, the resource allocation semi-analytical solutions are obtained via Karush-Kuhn-Tucker (KKT) conditions. Subsequently, the active STAR-RIS coefficients are optimized by capitalizing on fractional programming and majorization-minimization (MM) techniques. Finally, simulation results reveal that the proposed scheme achieves a 20.34% weighted ISAC joint-rate gain over the passive scheme, validating its effectiveness in wideband CF-ISAC systems.
Xintong Zhou, Feng Ke, Xiu-Yin Zhang et al.· IEEE Transactions on Communi...· 0 citations
Cell-free massive multiple-input multiple-output (CF mMIMO) requires effective power control, but centralized processing relies on global instantaneous channel state information (CSI) and creates heavy fronthaul load. This letter focuses on low-overhead distributed power control under limited fronthaul capacity. We propose an information bottleneck (IB)-based policy that exchanges compact latent messages instead of raw local observations, and we train it using cluster-based federated learning to keep raw CSI local. The IB penalty provides an explicit information-rate proxy for online coordination, while robustness under imperfect CSI and data locality are evaluated as supporting effects rather than formal guarantees. Simulations show that the proposed method approaches a centralized benchmark with much lower effective overhead and stable behavior under channel estimation errors.
Yukun Ma, Jiayi Zhang, Zih-Yi Liu et al.· IEEE Wireless Communications...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
