Numerical results confirm that the proposed hierarchical ISAC architecture simultaneously achieves higher sum throughput and superior sensing accuracy than conventional cell-free ISAC.
Abstract
This paper studies integrated sensing and communications (ISAC) over a hybrid system that seamlessly combines legacy cellular base stations with distributed cell-free (CF) access points (APs). We propose a hierarchical ISAC architecture where a central base station (CBS) serves its near users and simultaneously operates as a monostatic radar for aerial target detection, while distributed APs---many idle under user-centric clustering---act as cost-free bistatic receivers. The CBS jointly handles communication processing and multi-static sensing fusion, reducing fronthaul overhead compared to conventional cell-free ISAC. To achieve this, a five-phase time-division duplexing workflow with precise ISAC role assignment is specified. Closed-form expressions for spectral efficiency and multi-static sensing signal-to-noise ratio analytically characterize the communications--sensing Pareto frontier. Numerical results confirm that the proposed hierarchical design simultaneously achieves higher sum throughput and superior sensing accuracy than conventional cell-free ISAC.
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
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
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
To address the challenges of inter-cell interference/reflection and static clutter, a clutter-aware waveform design for a multi-cell multiple-input multiple-output (MIMO) integrated sensing and communication (ISAC) system is proposed. Various levels of coordination among base stations (BSs) are investigated to enhance target detectability in cluttered environments while maintaining the quality of service (QoS) for communication users. Specifically, two coordination schemes are investigated: 1) coordinated beamforming (CBF), where only channel state information (CSI) is shared, and 2) coordinated multipoint (CoMP), where both CSI and user data are exchanged among BSs. The waveform design problem is formulated as a non-convex optimization that maximizes the radar output signal-to-clutter-plus-interference-plus-noise ratio (SCINR), subject to robust symbol-level QoS and constant-modulus power constraints to ensure uncertainty in shared and estimated CSI. To tackle this problem, the single-ratio SCINR objective is decoupled via Dinkelbach’s transform (or a quadratic transform for multiple-ratio objectives) and reformulated on a Riemannian manifold to accommodate the constant-modulus constraint guarantees a practical peak-to-average-power ratio (PAPR). The resulting problem is further converted into an unconstrained form using the augmented Lagrangian method (ALM) and solved through a Riemannian conjugate gradient (RCG) algorithm. Simulation results demonstrate that the proposed designs achieve superior radar and communication performance compared to baseline schemes that underestimate the effects of multi-cell deployment.
Yves Fidele Aikoun, Gordon Owusu Boateng, Zhao-Jie Wang et al.· IEEE Transactions on Wireles...· 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
In this paper, we investigate the downlink performance of multi-cell RSMA-enabled ISAC networks in which base stations (BSs), communication users, and sensing targets are spatially distributed according to independent Poisson point processes (PPPs). Each BS simultaneously serves multiple users using RSMA while exploiting the common stream as a dual-functional communication and sensing waveform. The users are equipped with FAS that selects the best antenna port to maximize the received signal quality. Closed-form analytical expressions are derived for the ergodic sum-rates by combining stochastic geometry, order statistics, and Laplace-transform-based interference analysis. Furthermore, a tractable approximation for the average radar SINR is developed by characterizing the statistical properties of the common precoder. Leveraging the derived analytical expressions, a low-complexity analytical resource allocation framework is proposed to jointly optimize the RSMA power allocation, the communication-sensing beam tradeoff, and the number of scheduled users while sat- isfying the sensing quality-of-service constraint. Compared with conventional iterative optimization approaches, the proposed analytical design significantly reduces computational complexity while achieving nearly identical communication performance. Simulation results verify the accuracy of the developed analytical expressions and demonstrate substantial improvements in both RSMA sum-rate and sensing performance over conventional transmission schemes.
Abdelhamid Salem, Hana Shamata, Salma M. Elkawafi et al.· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
