Cognitive Decomposition of Wireless Networks
نویسندگان
چکیده
Abstract— In this paper, we provide a framework for a fundamental study of the communication limits of networks of cognitive devices. It is shown that all communication in a network of cognitive and non-cognitive devices can be cast into competitive, cognitive and cooperative behaviors. An achievable rate region for the cognitive radio channnel (which captures the most fundamental form of cognition – vertical spectrum sharing), is presented.
منابع مشابه
طراحی لایه- متقاطع برای کنترل ازدحام، مسیریابی و زمان‌بندی در شبکه‌های بی‌سیم ad-hocبا در نظر‌گرفتن توان الکتریکی گره‌ها
Abstract Ad hoc Wireless Networks, are networks formed by a collection of nodes through radio. In wireless networking environment, formidable challenges are presented. One important challenge is connection maintenance mechanism for power consumption. In this paper, a multi-objective optimal design is considered for ad-hoc networks which address the electrical power of nodes effects on cross-l...
متن کاملThe Role of Packet Tracer in Learning Wireless Networks and Managing IoT Devices
Wireless networks, Internet of Things (IoT), Internet of Everything (IoE), and smart homes have become extremely important terms in our present-day life. Most of the buildings, companies, institutions, and even homes depend onthese technologies for interaction, communication, automation, and everything surrounding humans. To understand the advanced topics in wireless networks and IoT devi...
متن کاملSpectrum Sensing Data Falsification Attack in Cognitive Radio Networks: An Analytical Model for Evaluation and Mitigation of Performance Degradation
Cognitive Radio (CR) networks enable dynamic spectrum access and can significantly improve spectral efficiency. Cooperative Spectrum Sensing (CSS) exploits the spatial diversity between CR users to increase sensing accuracy. However, in a realistic scenario, the trustworthy of CSS is vulnerable to Spectrum Sensing Data Falsification (SSDF) attack. In an SSDF attack, some malicious CR users deli...
متن کاملRule-based joint fuzzy and probabilistic networks
One of the important challenges in Graphical models is the problem of dealing with the uncertainties in the problem. Among graphical networks, fuzzy cognitive map is only capable of modeling fuzzy uncertainty and the Bayesian network is only capable of modeling probabilistic uncertainty. In many real issues, we are faced with both fuzzy and probabilistic uncertainties. In these cases, the propo...
متن کاملAn Adaptive Congestion Alleviating Protocol for Healthcare Applications in Wireless Body Sensor Networks: Learning Automata Approach
Wireless Body Sensor Networks (WBSNs) involve a convergence of biosensors, wireless communication and networks technologies. WBSN enables real-time healthcare services to users. Wireless sensors can be used to monitor patients’ physical conditions and transfer real time vital signs to the emergency center or individual doctors. Wireless networks are subject to more packet loss and congestion. T...
متن کاملSimulate Congestion Prediction in a Wireless Network Using the LSTM Deep Learning Model
Achieved wireless networks since its beginning the prevalent wide due to the increasing wireless devices represented by smart phones and laptop, and the proliferation of networks coincides with the high speed and ease of use of the Internet and enjoy the delivery of various data such as video clips and games. Here's the show the congestion problem arises and represent aim of the research is t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2006