انتخاب ایستگاه پایه در شبکه های دو- رده ای فمتوسل با رویکردی مبتنی بر نظریه بازی

محورهای موضوعی : آمار

آزاده پورکبیریان ¹ ( گروه مهندسی کامپیوتر، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران )
مهدی دهقان تخت فولادی ² ( استاد دپارتمان مهندسی کامپیوتر، دانشگاه صنعتی امیرکبیر، تهران، ایران )
اسماعیل زینالی ³ ( استادیار دانشکده مهندسی کامپیوتر و فناوری اطلاعات، واحد قزوین، دانشگاه آزاد اسلامی، قزوین، ایران )
امیرمسعود رحمانی ⁴ ( گروه مهندسی کامپیوتر، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران )

تاریخ دریافت : 1397/08/21 تاریخ پذیرش : 1397/10/29 تاریخ انتشار : 1400/07/01

کلید واژه: Resource Allocation, EXP3 learning algorithm, Quality of Service, Wireless two-tier femtocell networks, Evolutionary game theory,

چکیده مقاله :

تخصیص منابع همواره یکی از چالش‌های اساسی در طراحی شبکه‌های بی‌سیم سلولی بوده است. تخصیص مناسب منابع شبکه که به بیانی دقیق‌تر شامل انتخاب ایستگاه پایه مناسب و تخصیص پهنای باند کافی برای کاربران می‌باشد، نقش مؤثری در کاهش تداخل، تأمین انتظارات و تضمین الزامات کیفیت سرویس کاربر ایفا می‌کند. در این مقاله، رویکردی مبتنی بر چارچوب ریاضی نظریه بازی برای حل مسأله انتخاب ایستگاه پایه در شبکه‌های بی‌سیم دو-رده‌ای فمتوسل ارائه می‌شود. در رویکرد پیشنهادی ، رفتار رقابتی کاربران شبکه برای در اختیار گرفتن منابع مورد نیاز به شکل یک بازی تکاملی فرمول‌بندی می‌شود. در رویکرد پیشنهادی همچنین، احتمال انتخاب یک ایستگاه پایه، محاسبه بار سلولی هر ایستگاه پایه و تجزیه و تحلیل احتمال رد تقاضای کاربر از طرف ایستگاه پایه را محاسبه می‌کنیم. رویکرد پیشنهادی ضمن بیشینه‌سازی نرخ گذردهی شبکه، الزامات کیفیت سرویس کاربران شبکه را نیز تأمین می‌کند. در نهایت، یک الگوریتم غیر متمرکز یادگیر مبتنی بر یادگیری EXP3 برای همگرایی مسأله به تعادل تکاملی به عنوان پاسخ بازی ارائه می‌شود. نتایج شبیه‌سازی نشان می‌دهد که روش پیشنهادی نیازهای کیفیت سرویس کاربران شبکه را تأمین می‌کند و عملکرد مطلوب را به دست می‌آورد.

چکیده انگلیسی:

Resource allocation has always been one of the main challenges in the design of wireless cellular networks. Suitable resource allocation, more specifically that includes suitable base station selection and bandwidth allocation can play an effective role in interference mitigation and users’ quality of service requirement satisfaction. In this paper, a game theoretic approach is proposed to solve the BS selection problem in two-tier wireless femtocell networks. We formulate the competitive behavior of users as evolutionary game theory. We calculate the probability of a user choosing a BS, compute the cell load of each BS, and analyze the demand rejection probability of the user associated with the BS. The proposed approach maximizes network throughput as well as meeting the QoS requirements of the users. Finally, we propose a decentralized learning algorithm based on EXP3 algorithm to achieve the evolutionary equilibrium as the solution of the game. Simulation results show that the proposed approach achieves a desirable performance and guarantees users’ QoS requirements.

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