Numerical results demonstrate that the proposed RSMA-enabled integrated direct localization and covert communication framework for fronthaul-constrained C-RAN outperforms SDMA and fixed-scheduling baselines, especially under stringent fronthaul and covertness constraints.
Abstract
Integrated sensing and communication (ISAC) in cloud radio access networks (C-RANs) provides a promising architecture for cooperative sensing and secure transmission in future sixth-generation (6G) networks. However, achieving covert communication in such systems is challenging due to stringent covertness requirements, severe multi-user interference, multi-static sensing constraints, and finite fronthaul capacity. In this paper, we propose a rate-splitting multiple access (RSMA)-enabled integrated direct localization and covert communication framework for fronthaul-constrained C-RAN. In the proposed design, the RSMA common stream acts as an overt public signal, while the private streams convey covert information to legitimate users. A dedicated sensing/artificial-noise beamformer is jointly designed to support multi-static direct localization and shape the received energy profile at the warden. We formulate a sum covert rate maximization problem by jointly optimizing common-rate allocation, BS-stream scheduling, communication precoding, and sensing beamforming under covertness, sensing accuracy, transmit power, and fronthaul constraints. To solve the resulting mixed-integer non-convex problem, we develop an iterative algorithm based on continuous relaxation, semidefinite relaxation, linear matrix inequalities, and successive convex approximation. We further establish the convergence behavior of the proposed algorithm and characterize its computational burden. Numerical results demonstrate that the proposed scheme outperforms SDMA and fixed-scheduling baselines, especially under stringent fronthaul and covertness constraints.
Satellite-terrestrial integrated networks with simultaneous wireless information and power transfer (SWIPT) provide wide-area connectivity and sustainable service support, but they also face serious security challenges due to the broadcast nature of satellite links and the possibility that an energy receiver may act as potential eavesdropper. To address this issue, this paper proposes a secure precoding design for a high-altitude platform (HAP)-assisted rate-splitting multiple access (RSMA) architecture under a quasi-static transmission model. Specifically, a cooperative direct and relay transmission (CDRT) framework is developed, in which the HAP assists the satellite transmission to improve the physical layer security for multi-user SWIPT services. By assuming the energy receiver near the target user as potential eavesdropper, we formulate a sum secrecy rate maximization problem subject to energy harvesting and transmit power constraints. To transform the original nonconvex optimization problem into a tractable convex problem, we employ techniques such as first-order Taylor expansion approximation, rank-one constraint relaxation, successive convex approximation, and semidefinite relaxation. Numerical results demonstrate that the proposed CDRT-RSMA scheme significantly outperforms conventional non-orthogonal and time-division multiple access schemes in terms of security performance.
Mengyan Huang, Xingwang Li, Chengjun Jiang et al.· IEEE Journal on Selected Are...· 0 citations
A cross-layer end-to-end (E2E) resource orchestration framework for green CF-mMIMO ISAC systems with distributed multi-target detection is developed and a fundamental implementation trade-off is revealed: FIS provides lower detector-processing complexity and higher detection performance, whereas PIS substantially reduces fronthaul requirements.
Z. Behdad, Ozlem Tuugfe Demir, Ki Won Sung et al.· arXiv.org· 0 citations
In this paper, we investigate the covert communication performance and sensing performance of integrated sensing and communication (ISAC) systems enhanced by simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS). A novel non-orthogonal multiple access (NOMA) enabled covert framework is proposed, where the covert transmission can be enhanced by eliminating the interference of public signals and sensing signals at the covert user. The large system analytic estimation is employed to effectively decouple the correlation of the warden’s channel fading gains and derive a closed-form expression for the minimum average detection error probability of the warden. Both sensing and covert rate optimization problems are investigated through jointly designing base station transmit beamforming and STAR-RIS passive beamforming. To optimize sensing performance, we aim at minimizing the Cramér-Rao bound (CRB) while satisfying the covert rate requirement. Conversely, when maximizing the covert rate, the CRB is incorporated as a constraint in the sensing. To address these challenging optimization problems, an iterative algorithm based on penalty methods and semidefinite programming are proposed to obtain the transmit beamforming and the beamforming of STAR-RIS. Simulation results indicate that the CRB and covert rate of the proposed ISAC systems, assisted by STAR-RIS and NOMA, outperform the ISAC systems enhanced by orthogonal multiple access and conventional RIS.
Zheng Yang, Haoyang Li, Gaojie Chen et al.· IEEE Transactions on Wireles...· 0 citations
Integrated sensing and communication (ISAC) enables future wireless networks to perform sensing and communication (S&C) over a shared waveform. In multistatic ISAC systems, however, the sensing receivers do not know the realizations of transmitted data symbols, making it challenging to exploit communication signals for sensing. In this paper, we propose a data-aided framework for target localization with two receiver strategies, namely statistical data-aided sensing and joint data-aided sensing and decoding, where the former marginalizes the random unknown data symbols and the latter reuses the reliably decoded data symbols as known virtual pilots. Under orthogonal frequency division multiplexing (OFDM) signaling, we derive the performance limits for target localization in both strategies and adopt the achievable ergodic data rate as the communication metric. Then, we formulate a joint time-allocation and transmit data-covariance design problem for target localization under communication constraints, which characterizes the joint S&C bound and quantifies the sensing gain provided by data symbols. In addition, we develop two target localization algorithms that implement the proposed data-aided receiver processing, and extend the framework to finite-alphabet signaling. Simulation results validate theoretical analysis and the effectiveness of the proposed data-aided schemes.
An unmanned aerial vehicle (UAV)-enabled ISAC system employing rate-splitting multiple access (RSMA) and a joint beamforming and trajectory optimization framework is investigated and results demonstrate that the proposed algorithm significantly improves the achievable system downlink rate.
Shunxuan Wang, Qi Zhu· Italian National Conference...· 0 citations
Spectrally efficient frequency-division multiplexing (SEFDM) is an attractive waveform to improve communication spectral efficiency by compressing the subcarrier spacing, yet its use for integrated sensing and communication (ISAC) poses a fundamental sensing challenge. Specifically, the intentional loss of subcarrier orthogonality generates SEFDM-induced intercarrier interference (S-ICI), which combines with Doppler-induced ICI (D-ICI) from moving targets to blur range--velocity maps and severely degrade sensing accuracy. Building on multi-user multi-input-multi-output (MIMO) SEFDM systems, this paper develops a model-driven ISAC framework that supports spectrally efficient multi-user communication while mitigating both S-ICI and D-ICI in sensing. To this end, an intercarrier interference mitigation network (IMNet) is proposed, which exploits the distinct physical structures of the two interferences. A bank of Doppler correction filters first compensates the velocity-dependent D-ICI over multiple Doppler hypotheses, and an axial-attention network subsequently suppresses the residual D-ICI and the long-range S-ICI to recover reliable sensing signals. To further improve range and velocity estimation accuracy, IMNet with local refinement (IMNet-LR) is proposed, which performs maximum-likelihood refinement with nuisance projection around the IMNet detections to achieve sub-cell precision without an exhaustive global search. Simulation results show that IMNet-LR achieves near-maximum-likelihood range and velocity estimation accuracy with more than three orders of magnitude lower execution time compared to conventional detection methods.
Hyeonho Noh· 0 citations
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