| 摘要: | 傳統無線通訊網路主要聚焦於資訊傳輸，然而隨著自動駕駛、智慧交通等應
用興起，高精準度感測與高速率通訊的整合問題成為關鍵。隨著使用毫米波等高頻段的感測，雖然能夠提供更高精準度的感測能力，但其訊號也容易受到建築物、障礙物等等的遮蔽而發生嚴重衰減，導致出現覆蓋盲區與感測精度下降。可重構智慧表面 (Reconfigurable Intelligent Surface, RIS) 因為其低功耗與元件上可調控的反射相位，能有效建立視距 (Line of Sight, LoS) 路徑，因此利用 RIS 輔助整合感測與通訊 (Integrated Sensing and Communication, ISAC) 成為熱門的主題。在本研究中探討由一個多天線發射基地台 (TX)、一個多天線接收基地台 (RX)、兩個 RIS、多個單天線通訊用戶 (User)、多個單天線感測目標 (Target) 組成的雙 RIS 輔助 ISAC 的問題，其中發射基地台由兩個子陣列 (subarray) 組成，分別發射感測與通訊訊號，並透過兩個 RIS 分別對目標進行感測以及對用戶提供通訊。在考慮感測性能克萊姆-饒歐界 (Cramér-Rao bound, CRB) 限制、發射總功率限制、RIS 單
位模量 (Unit-modulus) 限制下，聯合設計發射波束成形 (Beamforming) 與 RIS 反射相位的最佳化問題，並將此最佳化問題拆解為兩個子問題，並利用連續凸逼近 (Successive Convex Approximation, SCA) 與交替優化 (Alternative Optimization, AO) 求解，透過優化發射波束成形與 RIS 的反射相位能有效降低通訊用戶間、感測與通訊雙方的干擾，實現最大化通訊用戶總速率。;Traditional wireless communication networks primarily focus on information transmission. However, with the rise of applications such as autonomous driving and intelligent transportation systems, the integration of high-precision sensing and high-rate communication has become a critical challenge. Although sensing at high-frequency bands, such as millimeter-wave (mmWave), provides superior resolution, signals are highly susceptible to severe attenuation caused by blockages from buildings and other obstacles, leading to coverage dead zones and degraded sensing accuracy. Reconfigurable Intelligent Surfaces (RIS), characterized by low power consumption and tunable reflection phases, can effectively establish line-of-sight (LoS) paths. Consequently, RIS assisted Integrated Sensing and Communication (ISAC) has emerged as a prominent research topic.
This thesis investigates an dual-RIS assisted ISAC system comprising a multi-antenna transmitter (TX), a multi-antenna receiver (RX), two RIS, multiple single-antenna communication users, and multiple single-antenna sensing targets. The TX is equipped with two subarrays dedicated to transmitting sensing and communication signals, respectively. These signals are reflected by two RIS to perform target sensing and provide communication services to users independently. Under constraints including the Cramér-Rao Bound (CRB) for sensing performance, total transmit power limits, and unit-modulus constraints of the RIS elements, we formulate a joint optimization problem for transmit beamforming and RIS reflection phases. The formulated problem is decomposed into two sub-problems and solved using Successive Convex Approximation (SCA) and Alternative Optimization (AO) techniques. By optimizing the transmit beamforming and RIS reflection phases, the proposed scheme effectively mitigates interference among communication users as well as the mutual interference between sensing and communication functionalities, thereby maximizing the system′s sum-rate. |
