Artificial Intelligence Based Model for Channel Status Prediction: A New Spectrum Sensing Technique for Cognitive Radio

• 作者: Palanaindavar Venkateswaran Rabindranath Nandi Sandhya Pattanayak
• 来源期刊: 通讯、网络与系统学国际期刊(英文)
• 学科: 工学
• 关键词: ANN COGNITIVE RADIO SPECTRUM SENSING COGNITIVE Engine
• 年，卷（期）: 2013,（3）
• 页码范围: 139-148
• 页数: 10页
• 分类号: TN92

摘要

The recent phenomena of tremendous growth in wireless communication application urge increasing need of radio spectrum, albeit it being a precious but natural resource. The recent technology under development to overview the situation is the concept of Cognitive Radio (CR). Recently the Artificial Intelligence (AI) tools are being considered for the topic. AI is the core of the cognitive engine that examines the external and internal environment parameters that leads to some postulations for QoS improvement. In this article, we propose a new Artificial Neural Network (ANN) model for detection of a spectrum hole. The model is trained with some pertinent features over a channel like SNR, channel capacity, bandwidth efficiency etc. The channel capacity status could be identified in a quantized index form . Some simulation results are presented.