MAC protocol identification using support vector machines for cognitive radio networks
MAC protocol identification using support vector machines for cognitive radio networks
复制标题
DOI：
10.1109/mwc.2014.6757897
复制
发表时间：
2014-03
影响因子：
12.9
通讯作者：
Sanqing Hu;Yu-dong Yao;Zhuo Yang
中科院分区：
文献类型：
--
作者：
Sanqing Hu;Yu-dong Yao;Zhuo Yang
认知无线电被认为是解决无线通信频谱稀缺问题的潜在解决方案。在CR中，考虑到外部无线电环境的当前状态，未许可的网络用户（次要用户）能够动态地/自适应地访问频率信道。在本文中，我们研究了认知 MAC 中应用的介质访问控制协议识别。 MAC 协议识别使 CR 用户能够感知和识别任何现有传输（主要或次要用户）的 MAC 协议类型。 CR 用户将使用识别结果自适应地改变其传输参数，以提高频谱利用率，并最大限度地减少对主要用户和其他次要用户的潜在干扰。 MAC协议识别也有利于实现异构CR网络之间的通信。在本文中，我们考虑了四种MAC协议，包括TDMA、CSMA/CA、纯ALOHA和时隙ALOHA，并提出了一种基于机器学习技术的MAC识别方法。进行计算机模拟来评估MAC识别性能。
Cognitive radio is regarded as a potential solution to address the spectrum scarcity issue in wireless communication. In CR, an unlicensed network user (secondary user) is enabled to dynamically/adaptively access the frequency channels considering the current state of the external radio environment. In this article, we investigate the medium access control protocol identification for applications in cognitive MAC. MAC protocol identification enables CR users to sense and identify the MAC protocol types of any existing transmissions (primary or secondary users). The identification results will be used by CR users to adaptively change their transmission parameters in order to improve spectrum utilization, as well as to minimize potential interference to primary and other secondary users. MAC protocol identification also facilitates the implementation of communications among heterogeneous CR networks. In this article, we consider four MAC protocols, including TDMA, CSMA/CA, pure ALOHA, and slotted ALOHA, and propose a MAC identification method based on machine learning techniques. Computer simulations are performed to evaluate the MAC identification performance.