Adaptive N Tree Anti-Collision Algorithm Based on Bitmap Construction

Abstract

Abstract:

Abstract： Aimed at the RFID (radio frequency identification) collision problem caused by multiple access of shared channel, this paper proposed two RFID adaptive N tree anticollision algorithms based on bitmap construction, single frame bitmap track N tree algorithm (SFBTNA) and multiframe bitmap track N tree algorithm(MFBTNA). First of all, the two methods take advantage of the maximum likelihood tag numbers estimation method (MLBE) that can effectively estimate the number of tags. Secondly, based on the MLBE, it put forward the probe method construct bitmap. The SFBTNA adaptively adjusts the optimization value of N and builds N trees on one frame based on bitmap. The MFBTNA adaptively adjusts optimization value of N and builds N trees frame by frame. At the same time, the SFBTNA and MFBTNA identify the subtrees using collision track tree algorithm (CT). The combination of bitmap and CT greatly reduces the impact of collision time slot. Theoretical analysis and simulation experiments show that the performance of the two algorithms is higher than that of the other existing anticollision algorithms.

Key words: radio frequency identification (RFID), anticollision, adaptive, throughput rate

CLC Number:

TP 393

WANG Xin1,JIA Qingxuan1,GAO Xin1,CHEN Gang1,ZHAO Bing2. Adaptive N Tree Anti-Collision Algorithm Based on Bitmap Construction[J]. Journal of Shanghai Jiaotong University, 2015, 49(02): 150-157.

References

［1］Ullah S, Alsalih W, Alshaim A, et al. A review of tags anticollision and localization protocols in RFID networks ［J］. Journal of Medical Systems, 2012, 36(6): 40374050.

［2］Klair K, Chin W, Raad R. A survey and tutorial of RFID anticollision protocols ［J］. IEEE Communications Surveys and Tutorials, 2010, 12(3): 400421.

［3］Namboodiri V, DeSilva M, Deegala K, et al. An extensive study of slotted Alohabased RFID anticollision protocols ［J］. Computer Communications, 2013, 35(16): 19551966.

［4］Rao S S, Rajan E G, Lalkishore K. ASAF ALOHA protocol for dense RFID systems ［J］. Wireless Personal Communications, 2013, 66(4): 667681.

［5］Javier V A, Victoria B D, Esteban E L, et al. Multiframe maximumlikelihood tag estimation for RFID anticollision protocols ［J］. IEEE Trans on Industrial Informatics, 2011, 7(3): 487496.

［6］He Y J, Wang X Y. An Alohabased improved anticollision algorithm for RFID systems ［J］. IEEE Wireless Communications, 2013, 20(5): 152158.

［7］Yang C N, Hu L J, Lai J B. Query tree algorithm for RFID tag with binarycoded decimal EPC ［J］. IEEE Communications Letters, 2012, 16(10): 16161619.

［8］Gou H, Yoo Y. Bit collision detection based query tree protocol for anticollision in RFID system ［J］. International Journal of Innovative Computing Information and Control, 2012, 8(5A): 30813102.

［9］Lai Y C, Hsiao L Y. General binary tree protocol for coping with the capture effect in RFID tag identification ［J］. IEEE Communications Letters, 2010, 14(3): 208210.

［10］Jia X L, Feng Q Y, Yu L S, et al. Stability analysis of an efficient anticollision protocol for RFID tag identification ［J］. IEEE Transactions on Communications, 2012, 60(8): 22852294.

［11］Lai Y C, Chen H J, Lai C N, et al. A novel query tree protocol with bit tracking in RFID tag identification ［J］. IEEE Transactions on Mobile Computing, 2013, 12(10): 20632074.

［12］Chen W T, Lin G H. An efficient scheme for multiple access in a RFID system ［J］. IEICE Trans Commun, 2006, E89B(12): 33863392.

［13］EPCGLOBAL. EPCGLOBC1G2: Radiofrequency identity protocol Class1 Generation2 UHF RFID protocol for communication at 860MHZ960MHZ Version1.2.0. ［EB/OL］. （20081023) ［20140507］,http:∥www.gs1.org/gsmp/kc/epcglobal/uhfc1g2/uhfc1g2_1_2_0standard20080511.pdf.

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