Reference Waveforms Forward Concurrent Transmissions in ZigBee Communications

Abstract

The number of Internet of Things is growing exponentially, among which the ZigBee devices are being widely deployed, incurring severe collision problem in ZigBee networks. Instead of collision avoidance or packet retransmissions which introduce extra time/energy overhead, existing methods try to decompose multi-packet collision directly. For example, state-of-the-art mZig exploits collision-free chips to decompose the collided chips iteratively, however, suffers from the high bit error rate and low frame reception rate which limit the practical applications. Toward this end, we observe three major issues of existing solutions: 1) all existing solutions adopt the priori-chip-dependent decomposition pattern, leading to the error propagation; 2) the available samples for chip decoding can be scarce, resulting in severe scarce-sample errors; 3) existing solutions assume the consistent frequency offset for consecutive packets, leading to inaccurate frequency offset estimation. To solve these issues in collision decomposition, we propose FORWARD, a novel physical layer design to enable accurate collision decoding in ZigBee. The key idea is to generate all possible overlapping combinations as reference waveforms. The decomposition is determined by comparing the collided signal with the reference waveforms. Such a priori-chip-independent design has the advantages to eliminate the error propagation. To ensure sufficient samples for decoding, FORWARD always choose the longest segment as reference. Furthermore, the real-time channel estimation and frequency offset calibration ensure the accurate collision decoding. We implement FORWARD on USRP platform and evaluate its performance. Experimental results demonstrate that FORWARD reduces bit error rate by order of magnitude and increases frame reception rate by 10% ~ 50% compared with the state-of-the-art.