"RTR_CSM"
收藏DataCite Commons2026-04-28 更新2026-05-03 收录
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https://ieee-dataport.org/documents/rtrcsm
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资源简介：
"This letter investigates the joint beamforming design for ISAC-enabled UAV systems, aiming to optimize the trade-off between communication sum rate (SR) and sensing Cram\u00e9r-Rao lower bound (CRLB) under stringent size, weight, and power (SWaP) constraints. Departing from traditional relaxation methods, we propose a Riemannian trust-region algorithm on the complex sphere manifold (RTR-CSM). The problem is reformulated as a tractable quadratic surrogate, with a finite-difference approximated Hessian constructing the trust-region subproblem, solved via truncated conjugate gradient to avoid expensive exact second-order derivations and matrix inversions. Simulations show that RTR-CSM achieves near-optimal performance and converges significantly faster than state-of-the-art benchmarks (e.g., over 5\u00d7 faster than the Riemannian-based IRO-CSM and 14\u00d7 faster than SCA), making it highly suitable for resource-constrained UAV-enabled ISAC beamforming."
提供机构：
IEEE DataPort
创建时间：
2026-04-28
