基于有限反馈机会波束的无线传感器网络  被引量:1

Wireless sensor networks based on finite feedback opportunistic beamforming

在线阅读下载全文

作  者:侯艳丽[1] 苏佳[1] 胡佳伟[2] 

机构地区:[1]河北科技大学信息科学与工程学院,河北石家庄050026 [2]中国电子科技集团公司第五十四研究所,河北石家庄050081

出  处:《传感器与微系统》2014年第2期57-60,共4页Transducer and Microsystem Technologies

基  金:河北省教育厅高等学校科学研究计划资助项目(Z2012144)

摘  要:无线传感器网络中的传感器要把被监测的数据有效地传输到远端的收集器,且其节点的能量有限,为了提高衰落无线信道中无线传感器网络通信的有效性,提出基于有限反馈机会波束的无线传感器网络,基站设置多天线,传感器节点设置单天线,构成MISO系统,在每一时隙基站选择处于峰值状态的传感器节点进行通信。设置反馈门限,当传感器节点的接收信干噪比大于反馈门限时,对信干噪比进行量化,再将量化电平反馈给基站;否则,无需进行量化和反馈。以吞吐量最大化为原则设定最佳反馈门限和量化电平,在瑞利块衰落信道中对系统进行仿真,结果表明:随着节点数的增加,该系统的反馈数可降至传统模拟反馈的1%以下,大大降低了反馈量,提高了系统的效率和节点能量利用率。Node energy of sensors in wireless sensor networks (WSNs) is limited,in order to effectively transmit the tested data to remote collectors,and to improve the efficiency of WSNs communication in fading wireless channel,a WSNs based on finite feedback opportunistic beamforming (OBF)is proposed.In WSNs,the base station(BS)is equipped with multiple antennas and the sensor node is equipped with a single antenna,which constitutes a MISO system in which the BS selects the sensor node in peak state to communicate in every slot.Set a feedback threshold,receiving signal to interference and noise ratio(SINR) will be quantized and fed back to the BS when SINR is more than the pre-set feedback threshold,otherwise perform no quantization and feedback.The best feedback threshold and quantized levels are chose based on maximizing throughout.The proposed system is simulated in the Rayleigh block-fading channel,and the experimental results show that with the number of nodes increasing,the number of feedbacks of the proposed system will decrease below 1% of traditional analog feedback,so decreases feedback quantities greatly,improve efficiency of the system and node energy utilization.

关 键 词:无线传感器网络 机会波束 反馈门限 量化反馈 系统容量 

分 类 号:TN929.5[电子电信—通信与信息系统]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象