اشتراک محتوا با استفاده از ارتباطات D2D بر روی شبکه 5G‌

چکیده مقاله :

توسعه سریع سخت‌افزار هوشمند و اینترنت اشیا و همچنین ظهور برنامه‌های کاربردی متنوع، منجر به افزایش بی‌سابقه ترافیک داده موبایل شده و بنابراین باید کارایی استفاده از منابع شبکه و پهنای باند به طور مؤثری بهبود یابد. در حال حاضر فناوری ارتباطی دستگاه به دستگاه (D2D) با فراهم‌کردن ارتباط مستقیم تجهیزات ارتباطی می‌تواند ابزار مؤثری برای تکمیل شبکه‌های G5 ارائه دهد که نتیجه استفاده از آن کاهش بار روی شبکه‌ G5 و افزایش کیفیت خدمات است. در این زمینه یکی از مسائل اصلی، نحوه مدیریت منابع ارتباطی و انتخاب پیوندهای ارتباطی است. ما در این مقاله مسئله چگونگی مدیریت لینک‌های ارتباطی D2D برای انتقال محتوا بین تجهیزات ارتباطی را بررسی و آن را به صورت یک مسئله بهینه‌سازی خطی دودویی مدل می‌کنیم. برای حل این مسئله روشی بر اساس نظریه بازی پیشنهاد می‌کنیم که در آن با در نظر گرفتن تجهیزات کاربر حاوی فایل‌های مورد نظر برای انتقال به عنوان بازیکن، یک بازی پتانسیل دقیق طراحی و سپس برای رسیدن به نقطه تعادل نش یک الگوریتم یادگیری توزیع‌شده پیشنهاد می‌گردد. نتایج شبیه‌سازی کارایی مناسب الگوریتم پیشنهادی را تأیید می‌کنند.

چکیده انگلیسی :

The rapid development of intelligent hardware, Internet of Things (IoT), and the emergence of various applications has led to an unprecedented increase in mobile data traffic. Therefore, the efficiency of network resource utilization and bandwidth needs to be improved effectively. Currently, Device-to-Device (D2D) communication technology can provide an effective tool for enhancing 5G networks by enabling direct communication between devices. The use of D2D communication can reduce the load on the 5G network and improve service quality. One of the main issues in this regard is how to manage communication resources and select communication links. In this article, we examine the problem of managing D2D communication links for content transmission between communication devices and formulate it as a binary linear optimization problem. To solve this problem, we propose a method based on game theory, where considering user devices containing the desired files for transmission as players, we design an exact potential game and then propose a distributed learning algorithm to reach a Nash equilibrium. Simulation results confirm the satisfactory performance of the proposed algorithm.

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