Surviving wi-fi interference in low power ZigBee networks

Abstract

Frequency overlap across wireless networks with different radio technologies can cause severe interference and reduce communication reliability. The circumstances are particularly unfavorable for ZigBee networks that share the 2.4 GHz ISM band with WiFi senders capable of 10 to 100 times higher transmission power. Our work first examines the interference patterns between ZigBee and WiFi networks at the bit-level granularity. Under certain conditions, ZigBee activities can trigger a nearby WiFi transmitter to back off, in which case the header is often the only part of the ZigBee packet being corrupted. We call this the symmetric interference regions, in comparison to the asymmetric regions where the ZigBee signal is too weak to be detected by WiFi senders, but WiFi activity can uniformly corrupt any bit in a ZigBee packet. With these observations, we design BuzzBuzz to mitigate WiFi interference through header and payload redundancy. Multi-Headers provides header redundancy giving ZigBee nodes multiple opportunities to detect incoming packets. Then, TinyRS, a full-featured Reed Solomon library for resource-constrained devices, helps decoding polluted packet payload. On a medium-sized testbed, BuzzBuzz improves the ZigBee network delivery rate by 70%. Furthermore, BuzzBuzz reduces ZigBee retransmissions by a factor of three, which increases the WiFi throughput by 10%.

Detecting and Avoiding Multiple Sources of Interference in the 2.4 GHz Spectrum

“…Concurrent traffic over WiFi constitutes a major part of cross-technology interference in the 2.4 GHz ISM band [1]. Therefore it is necessary that a sensor node avoids operating on channels that overlap with WiFi activity.…”

“…Typically, IEEE 802.15.4-compliant sensor nodes compete for channel access with an increasing number of WiFi and Bluetooth devices such as laptops, smartphones, and tablet PCs. This results in long contention delays and collisions that degrade sensor network performance [1,2].…”

“…Several mitigation approaches [1][2][3][4] have been proposed to tackle the problem of external interference in sensor networks. Knowing the type of interference enables a sensor node to choose a suitable mitigation strategy [1,5,6].…”

“…Knowing the type of interference enables a sensor node to choose a suitable mitigation strategy [1,5,6]. In this regard, interference classification is prerequisite towards mitigation.…”

“…Lastly, multiple interference detection enables wireless devices to disambiguate external interference from in-network channel traffic. This provides a clearer context for motivating interference mitigation mechanisms as in [1,2].…”