Embracing Corruption Burstiness: Fast Error Recovery for ZigBee under Wi-Fi Interference

Abstract

Abstract-The ZigBee communication can be easily and severely interfered by Wi-Fi traffic. Error recovery, as an important means for ZigBee to survive Wi-Fi interference, has been extensively studied in recent years. The existing works add upfront redundancy to in-packet blocks for recovering a certain number of random corruptions. Therefore the bursty nature of ZigBee in-packet corruptions under Wi-Fi interference is often considered harmful, since some blocks are full of errors which cannot be recovered and some blocks have no errors but still requiring redundancy. As a result, they often use interleaving to reshape the bursty errors, before applying complex FEC codes to recover the re-shaped random distributed errors. In this paper, we take a different view that burstiness may be helpful. With burstiness, the in-packet corruptions are often consecutive and the requirement for error recovery is reduced as "recovering any k consecutive errors" instead of "recovering any random k errors". This lowered requirement allows us to design far more efficient code than the existing FEC codes. Motivated by this implication, we exploit the corruption burstiness to design a simple yet effective error recovery code using XOR operations (called ZiXOR). ZiXOR uses XOR code and the delay is significantly reduced. More, ZiXOR uses RSSI-hinted approach to detect in packet corruptions without CRC, incurring almost no extra transmission overhead. The testbed evaluation results show that ZiXOR outperforms the state-of-the-art works in terms of the throughput (by 47%) and latency (by 22%).

Portal

“…COF [19] avoids the in-network homogenous interference. The authors in [31] recovers the bit errors caused by CTI. Weeble [22] and ECC [30] actively intervene high-power transmissions to aggregate long white spaces for low-power transmissions.…”

Deploying Edge Computing Nodes for Large-Scale IoT: A Diversity Aware Approach

“…As studied in [18], the difference between a given RSSI value and the lowest RSSI value is a good indicator to the error rate for the corresponding byte. Based on the RSSIbased error estimation method [19], we can obtain a series of BER and the variations from the RSSI samplings. Then PDR can be inferred using BER as follows:…”

Link quality aware channel allocation for multichannel body sensor networks

“…When all paths are assigned and there are still some slots that are not assigned to any links, we arrange to assign these spare slots for possible future retransmissions. During the channel allocation process, link quality is estimated using the in-packet corruptions [29,30,31] for each pair of channel and slot. The link estimation is described in Section 3.3.…”

“…However, one challenge is to obtain the real time link quality profile for each channel/slot pair as only one channel's quality can be measured at a time. Similar with [31,30], we use the 32KHz timer to measure the in-packet byte-level RSSI values. The smallest in-packet RSSI value is used as the RSSI base value.…”