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电力通信异构多网共存网络发现与识别算法
引用本文:吴维农,韩培培,冯文江,唐 夲.电力通信异构多网共存网络发现与识别算法[J].计算机工程与应用,2016,52(11):131-135.
作者姓名:吴维农  韩培培  冯文江  唐 夲
作者单位:1.国网重庆市电力公司 信通分公司,重庆 401123 2.重庆大学 通信工程学院,重庆 400044
摘    要:电力无线通信网支撑用户量大面广、业务高并发、运行环境复杂,表现为异构多网混合共存。为了支持智能电力终端动态选择网络接入,必须首先执行网络发现与识别。针对TD-LTE无线通信专网、WiMAX无线通信专网、智能电网邻域网和230 MHz电力无线专网异构多网共存场景,提出一种融合物理层信号时频特征和MAC层协议特征的网络识别算法。该算法结合改进的窗口滑动能量检测和多周期特性加权循环平稳特征检测执行网络发现与识别。仿真结果表明,该算法能有效识别异构的多种电力无线通信网络。

关 键 词:异构多网共存  网络发现与识别  能量检测  循环平稳特征检测  

Networks discovery and identification algorithm for heterogeneous multi-networks coexistence in power communications
WU Weinong,HAN Peipei,FENG Wenjiang,TANG Tao.Networks discovery and identification algorithm for heterogeneous multi-networks coexistence in power communications[J].Computer Engineering and Applications,2016,52(11):131-135.
Authors:WU Weinong  HAN Peipei  FENG Wenjiang  TANG Tao
Affiliation:1.ICT Branch of Chongqing Electric Power Corp., Chongqing 401123, China 2.College of Communication Engineering, Chongqing University, Chongqing 400044, China
Abstract:Electric power wireless communication network supports enormous quantity wide users, high concurrent services, and complex operating environment, which is represented as heterogeneous networks with different complementary cover scope coexistences. In order to support intelligent power terminals to select access network, network discovery and identification must be performed firstly. Based on TD-LTE, WiMAX, Smart Grid NAN and 230 MHz heterogeneous networks coexistence scenario, a network identification algorithm is proposed by integrating physical signal time-frequency characteristics with MAC layer protocol characteristics to discover and identify coexisting wireless networks. This algorithm combines the modified window-sliding energy detection with cyclostationary feature detection to execute network discovery and identification, and multicycle characteristics are used in cyclostationary feature detection to improve the signal identification precision. The simulation results show that the proposed algorithm can effectively identify various heterogeneous cognitive wireless networks.
Keywords:heterogeneous multi-networks coexistence  network discovery and identification  energy detection  cyclostationary feature detection  
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