通信已經從人對人發展到機器對機器。緊迫的問題是傳統的通信算法只是為人對人設計的。此外，蜂窩通信作為工業4.0、無人商店和智慧城市，海量機器通信是不可避免的。蜂巢式中的大規模機器通信也導致更稀缺的頻率資源。值得注意的是，人對人和機器對機器的共存是 6G 和物聯網的關鍵問題之一。這個問題在過去的信號處理中沒有揭示出來，即針對人對人和物聯網設備的存在而進行的發射-接收波束成形設計和功率分配。
頻寬和功率是通信領域的兩個基本問題和有限的資源。即使通信從 1G 發展到 5G 或 6G，這兩個真實問題仍然存在。因此，本論文研究了人對人和物聯網設備共存的約束優化通信問題下的信號處理技術，即頻寬和功率。我們使用凸優化和數值分析方法來處理約束優化問題，包括半定鬆弛、二階錐規劃、二階錐規劃鬆弛和不動點迭代。
本論文將研究面向6G應用的通信和物聯網的協同設計。首先，我們將研究人對人和設備到設備的共存。其次，將討論人對人和機器對機器的共存。第三，本文研究了真實世界的場景，即人對人/設備到設備/機器對機器的共存。仿真將驗證所提出的方法適用於共存問題。此外，所提出的方法比經典的凸優化結果方法具有更低的複雜性。最後，我們在人對人和物聯網設備共存這一新話題中得出結論。

Communication has developed from human-to-human (H2H) to machine-to-machine (M2M). The urgency problem is that the traditional communication algorithm is only designed for H2H. Moreover, massive machine communication is inevitable in cellular communication as industry 4.0, unmanned shop, and smart city. Massive machine communication in cellular also causes more scarce frequency resources. Significantly, the coexistence of H2H and M2M is one of the critical issues in the 6G and IoT. This issue is not revealed in the signal processing in the past, i.e., transmit-receive beamforming design and power allocation for the existence of H2H and IoT devices.
Bandwidth and power are two fundamental issues and limited resources in the communication area. Even though communication develops from 1G to 5G or 6G, these two real issues still exist. Thus, this dissertation studies the signal processing techniques under the constrained optimization communication problem to coexist H2H and IoT devices, i.e., bandwidth and power. We use the convex optimization and numerical analysis methods to deal with the constrained optimization problem, including semidefinite relaxation (SDR), second-order cone programming (SOCP), SOCP relaxation, and fixed-point iteration.
This dissertation will study the codesign of communication and IoT for 6G applications. First, we will investigate the coexistence of H2H and device-to-device (D2D). Secondly, the coexistence of H2H and M2M will be discussed. Third, the real-world scenario is studied in this dissertation, i.e., the coexistence of H2H/D2D/M2M. The simulation will verify the proposed methods suitable for the coexistence issue. Also, the proposed methods have lower complexity than the well-known convex results. Finally, we have the conclusions in this new topic of the coexistence of H2H and IoT devices.

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