激光杂志
激光雜誌
격광잡지
LASER JOURNAL
2014年
10期
102-107
,共6页
裴祥喜%崔炳德%李珉%周志敏
裴祥喜%崔炳德%李珉%週誌敏
배상희%최병덕%리민%주지민
无线传感器网络%比特错误率%干扰检测%差异化思想%错误率估计方法
無線傳感器網絡%比特錯誤率%榦擾檢測%差異化思想%錯誤率估計方法
무선전감기망락%비특착오솔%간우검측%차이화사상%착오솔고계방법
Wireless sensor network%Bit Error%Rate (BER)%interference%detection differentia%error estimation method
由于无线传感器网络中干扰检测的性能依赖于比特错误率(Bit Error Rate, BER)估计的准确性,而现有的比特错误率估计方法或者难以实现,或者准确性差。针对这个问题,本文提出了采用差异化思想来提高比特错误率估计准确度的方法DEE(Differentiated Error Estimation)。其主要是发送方在数据包中插入具有不同估错能力的多级估错位,并随机均匀地分布所有估错位。接收方借助BER与奇偶校验失败概率的理论关系来估计BER。同时,DEE利用BER非均匀分布特征来优化各级估错位的能力,提高出现概率高的BER的估计准确度,以降低平均估计误差。实验结果表明,与现有方法EEC相比,DEE可将估计误差平均减少约44%。当估错冗余较低时,DEE可将估计误差减少约68%。
由于無線傳感器網絡中榦擾檢測的性能依賴于比特錯誤率(Bit Error Rate, BER)估計的準確性,而現有的比特錯誤率估計方法或者難以實現,或者準確性差。針對這箇問題,本文提齣瞭採用差異化思想來提高比特錯誤率估計準確度的方法DEE(Differentiated Error Estimation)。其主要是髮送方在數據包中插入具有不同估錯能力的多級估錯位,併隨機均勻地分佈所有估錯位。接收方藉助BER與奇偶校驗失敗概率的理論關繫來估計BER。同時,DEE利用BER非均勻分佈特徵來優化各級估錯位的能力,提高齣現概率高的BER的估計準確度,以降低平均估計誤差。實驗結果錶明,與現有方法EEC相比,DEE可將估計誤差平均減少約44%。噹估錯冗餘較低時,DEE可將估計誤差減少約68%。
유우무선전감기망락중간우검측적성능의뢰우비특착오솔(Bit Error Rate, BER)고계적준학성,이현유적비특착오솔고계방법혹자난이실현,혹자준학성차。침대저개문제,본문제출료채용차이화사상래제고비특착오솔고계준학도적방법DEE(Differentiated Error Estimation)。기주요시발송방재수거포중삽입구유불동고착능력적다급고착위,병수궤균균지분포소유고착위。접수방차조BER여기우교험실패개솔적이론관계래고계BER。동시,DEE이용BER비균균분포특정래우화각급고착위적능력,제고출현개솔고적BER적고계준학도,이강저평균고계오차。실험결과표명,여현유방법EEC상비,DEE가장고계오차평균감소약44%。당고착용여교저시,DEE가장고계오차감소약68%。
The performance of interference detection in wireless sensor network depends on the performance of bit error rate (BER) estimation, however, the existed BER estimation methods are either too complicate to imple-ment or with low precision. To solve the problem, differentia error estimation (DEE) method is proposed to enhance the precision of BER. The main idea is to insert multi-level error estimation bits that with different error estimation ability, which are random and uniformly distributed, into the sender’s packets. And the receivers estimate the BER by using the relation between the BER and parity check. Meanwhile, DEE optimizes the ability of error estimation bit of each level by making use of BER’s feature of non-uniform distribution, to enhance the estimate precision of BER with higher probability and lower the average estimation error. The experiments shows that, compared with the error estimating coding (EEC) method, the average estimation error decreases 44%, and the estimation error decreas-es as much as 68%when the redundancy is decreased.