Optimizing Spectrum Trading in Cognitive Mesh Network Using Machine Learning
المؤلفون المشاركون
Agarwal, Anjali
Alsarhan, Ayoub
المصدر
Journal of Electrical and Computer Engineering
العدد
المجلد 2012، العدد 2012 (31 ديسمبر/كانون الأول 2012)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2012-08-22
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
العلوم الهندسية و تكنولوجيا المعلومات
تكنولوجيا المعلومات وعلم الحاسوب
الملخص EN
In a cognitive wireless mesh network, licensed users (primary users, PUs) may rent surplus spectrum to unlicensed users (secondary users, SUs) for getting some revenue.
For such spectrum sharing paradigm, maximizing the revenue is the key objective of the PUs while that of the SUs is to meet their requirements.
These complex contradicting objectives are embedded in our reinforcement learning (RL) model that is developed and implemented as shown in this paper.
The objective function is defined as the net revenue gained by PUs from renting some of their spectrum.
RL is used to extract the optimal control policy that maximizes the PUs’ profit continuously over time.
The extracted policy is used by PUs to manage renting the spectrum to SUs and it helps PUs to adapt to the changing network conditions.
Performance evaluation of the proposed spectrum trading approach shows that it is able to find the optimal size and price of spectrum for each primary user under different conditions.
Moreover, the approach constitutes a framework for studying, synthesizing and optimizing other schemes.
Another contribution is proposing a new distributed algorithm to manage spectrum sharing among PUs.
In our scheme, PUs exchange channels dynamically based on the availability of neighbor’s idle channels.
In our cooperative scheme, the objective of spectrum sharing is to maximize the total revenue and utilize spectrum efficiently.
Compared to the poverty-line heuristic that does not consider the availability of unused spectrum, our scheme has the advantage of utilizing spectrum efficiently.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Alsarhan, Ayoub& Agarwal, Anjali. 2012. Optimizing Spectrum Trading in Cognitive Mesh Network Using Machine Learning. Journal of Electrical and Computer Engineering،Vol. 2012, no. 2012, pp.1-12.
https://search.emarefa.net/detail/BIM-480973
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Alsarhan, Ayoub& Agarwal, Anjali. Optimizing Spectrum Trading in Cognitive Mesh Network Using Machine Learning. Journal of Electrical and Computer Engineering No. 2012 (2012), pp.1-12.
https://search.emarefa.net/detail/BIM-480973
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Alsarhan, Ayoub& Agarwal, Anjali. Optimizing Spectrum Trading in Cognitive Mesh Network Using Machine Learning. Journal of Electrical and Computer Engineering. 2012. Vol. 2012, no. 2012, pp.1-12.
https://search.emarefa.net/detail/BIM-480973
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-480973
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر