Abstract
The system is proposed study the coexistence of a self-sustainable Internet of Things (IoT) uplink and a radar sharing the same spectrum, assisted by a reconfigurable intelligent surface. The system is proposed formulate a joint design that maximizes uplink throughput while guaranteeing radar detection reliability by co-optimizing RIS phase shifts, the radar signal covariance, and frame time allocation under practical unit-modulus, power, and sensing constraints. Leveraging Lagrangian duality and Karush–Kuhn–Tucker conditions, The system is proposed derive a closed-form scheduler for per-device time allocation, with the wireless-energy phase obtained through a Lambert–W based expression. The remaining variables are handled by an alternating-optimization framework that iteratively solves convex subproblems for the radar (with semidefinite relaxation and rank-one recovery) and updates the RIS via unit-modulus projection, yielding monotonic ascent and reliable convergence in practice.Extensive simulations against conventional baselines (no RIS, random phases, fixed schedul ing, and single-module ablations) show substantial throughput gains that scale with RIS size through passive beamforming, alongside improved detection performance under comparable power budgets. Robustness analyses covering phase quantization, channel-state uncertainty, and threshold selection, together with measured runtime and a transparent reproducibility protocol, demonstrate a favorable accuracy and efficiency trade-off . Overall, this work provides a unified optimization and implementation favorable accuracy and efficiency trade-off blueprint for RIS assisted IoT–radar coexistence and offers practical guidelines on RIS sizing, power budgeting, and low-overhead online operation for integrated sensing and communications.
| Date of Award | 15 Jul 2026 |
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| Original language | English |
| Awarding Institution |
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| Supervisor | C.F. Kwong (Supervisor) & Zheng Chu (Supervisor) |