Chip Error Pattern Analysis in IEEE 802.15.4

IEEE 802.15.4 standard specifies physical layer (PHY) and medium access control (MAC) sublayer protocols for low-rate and low-power communication applications. In this protocol, every 4-bit symbol is encoded into a sequence of 32 chips that are actually transmitted over the air. The 32 chips as a whole is also called a pseudonoise code (PN-Code). Due to complex channel conditions such as attenuation and interference, the transmitted PN-Code will often be received with some PN-Code chips corrupted. In this paper, we conduct a systematic analysis on these errors occurring at chip level. We find that there are notable error patterns corresponding to different cases. We then show that recognizing these patterns enables us to identify the channel condition in great details. We believe that understanding what happened to the transmission in our way can potentially bring benefit to channel coding, routing, and error correction protocol design. Finally, we propose Simple Rule, a simple yet effective method based on the chip error patterns to infer the link condition with an accuracy of over 96 percent in our evaluations.

[1]  Seungjoon Lee,et al.  All Bits Are Not Equal - A Study of IEEE 802.11 Communication Bit Errors , 2009, IEEE INFOCOM 2009.

[2]  Philip Levis,et al.  Understanding the causes of packet delivery success and failure in dense wireless sensor networks , 2006, SenSys '06.

[3]  Gang Zhou,et al.  RID: radio interference detection in wireless sensor networks , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..

[4]  David E. Culler,et al.  A transmission control scheme for media access in sensor networks , 2001, MobiCom '01.

[5]  Marco Zuniga,et al.  Analyzing the transitional region in low power wireless links , 2004, 2004 First Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks, 2004. IEEE SECON 2004..

[6]  Andreas Willig,et al.  Measurements of a wireless link in an industrial environment using an IEEE 802.11-compliant physical layer , 2002, IEEE Trans. Ind. Electron..

[7]  Kaishun Wu,et al.  Chip Error Pattern Analysis in IEEE 802.15.4 , 2010, IEEE Transactions on Mobile Computing.

[8]  Peter Steenkiste,et al.  Measurement and analysis of the error characteristics of an in-building wireless network , 1996, SIGCOMM 1996.

[9]  Haitao Wu,et al.  A Practical SNR-Guided Rate Adaptation , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.

[10]  Deborah Estrin,et al.  Statistical model of lossy links in wireless sensor networks , 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

[11]  Srinivasan Seshan,et al.  Understanding and mitigating the impact of RF interference on 802.11 networks , 2007, SIGCOMM 2007.

[12]  Ratul Mahajan,et al.  Measurement-based models of delivery and interference in static wireless networks , 2006, SIGCOMM 2006.

[13]  Muriel Médard,et al.  Symbol-level network coding for wireless mesh networks , 2008, SIGCOMM '08.

[14]  Suman Banerjee,et al.  Diagnosing Wireless Packet Losses in 802.11: Separating Collision from Weak Signal , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.

[15]  Hayder Radha,et al.  Reducing Packet Losses in Networks of Commodity IEEE 802.15.4 Sensor Motes Using Cooperative Communication and Diversity Combination , 2009, IEEE INFOCOM 2009.

[16]  Qian Zhang,et al.  Side Channel: Bits over Interference , 2012, IEEE Trans. Mob. Comput..

[17]  Kyle Jamieson,et al.  PPR: partial packet recovery for wireless networks , 2007, SIGCOMM 2007.