Journal of the Institute of Electronics Engineers of Korea TC (대한전자공학회논문지TC)

The Institute of Electronics and Information Engineers (대한전자공학회)
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Retrospective Maximum Likelihood Decision Rule for Tag Cognizance in RFID Networks

RFID 망에서 Tag 인식을 위한 회고풍의 최대 우도 결정 규칙

  • Received : 2010.11.10
  • Published : 2011.02.25
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Abstract

We consider an RFID network configured as a star in which tags stationarily move into and out of the vicinity of the reader. To cognize the neighboring tags in the RFID network, we propose a scheme based on dynamic framed and slotted ALOHA which determines the number of slots belonging to a frame in a dynamic fashion. The tag cognizance scheme distinctively employs a rule for estimating the expected number of neighboring tags, identified as R-retrospective maximum likelihood rule, where the observations attained in the R previous frames are used in maximizing the likelihood of expected number of tags. Simulation result shows that a slight increase in depth of retrospect is able to significantly improve the cognizance performance.

Tag가 reader 주변을 정상적으로 오가는 별 형태의 RFID 망을 고려한다. 이 RFID 망에서 주위의 tag를 인식하기 위해 동적으로 프레임에 속한 슬롯의 수를 결정하는 동적 프레임화 및 슬롯화된 ALOHA 기반의 방식을 제안한다. 이 tag 인식 방식은 특징적으로 주위의 tag의 기대 수를 추정하기 위해 R-회고풍 최대 우도 규칙이라 불리는 규칙을 채택하여 이전 R 개의 프레임에서 얻은 관찰 값을 tag의 기대 수의 우도를 최대화하는 과정에 사용한다. 모의 실험 결과는 회고의 깊이를 조금 늘려도 인식 성능이 유의할 만큼 향상됨을 보여준다.

Keywords

References

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