전파 오류가 높은 센서 네트워크를 위한 적응적 FEC 알고리즘

An Adaptive FEC Algorithm for Sensor Networks with High Propagation Errors

  • 발행 : 2003.12.01

초록

전파(propagation) 오류가 빈번한 무선 이동 네트워크에서는 전송 성능을 향상하기 위해 FEC(Forward Error Correction)알고리즘을 채택한다. 그러나 정적인 FEC방식은 연속적으로 변화하는 전파 오류율에 알맞은 정정 코드(check code)를 적용하지 못해 성능이 저하된다. 본 논문에서는 변화하는 무선 채널의 전파 오류율에 따라 FEC의 정정도를 알맞게 결정하는 링크 계층용 적응적 FEC기법인 FECA(FEC-level Adaptation)를 제안한다. FECA는 오류율이 높고, 오류율이 천천히 변화하는 무선 환경에 알맞은 알고리즘이다. 일례로 전파 간섭이 있는 환경에서 센서(sensor) 네트워크는 평균 오류율이 $10^{-6}$이상이며 오류율이 평균 수백 밀리초 이상 지속되는 것으로 관찰되었다. FECA는 분석적인 무선채널 시뮬레이션과 패킷 트레이스 기반(trace-driven) 시뮬레이션에서 정적 FEC 알고리즘에 비해 최대 15%이상 성능을 향상하였다.

To improve performance over noisy wireless channels, mobile wireless networks employ forward error correction(FEC) techniques. The performance of static FEC algorithms, however, degrades by poorly matching the overhead of their correction code to the degree of the fluctuating underlying channel error. This paper proposes an adaptive FEC technique called FECA(FEC-level Adaptation), which dynamically tunes FEC strength to the currently estimated channel error rate at the data link layer. FECA is suitable for wireless networks whose error rate is high and slowly changing compared to the round-trip time between two communicating nodes. One such example network would be a sensor network in which the average bit error rate is higher than $10^{-6}$ and the detected error rate at one time lasts a few hundred milliseconds on average. Our experiments show that FECA performs 15% in simulations with theoretically modeled wireless channels and in trace-driven simulations based on the data collected from real sensor networks better than any other static FEC algorithms.

키워드

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