Fast and fine-grained counting and identification via constructive interference in WSNs

Abstract

Counting and identifying neighboring active nodes are two fundamental operations in wireless sensor networks (WSNs). In this paper, we propose two mechanisms, Power based Counting (Poc) and Power based Identification (Poid), which achieve fast and accurate counting and identification by allowing neighbors to respond simultaneously to a poller. A key observation that motivates our design is that the power of a superposed signal increases with the number of component signals under the condition of constructive interference (CI). However, due to the phase offsets and various hardware limitations (e.g., ADC saturation), the increased superposed power exhibits dynamic and diminishing returns as the number of component signals increases. This uncertainty of phase offsets and diminishing returns property of the superposed power pose serious challenges to the design of both Poc and Poid. To overcome these challenges, we design delay compensation methods to reduce the phase offset of each component signal, and propose a novel probabilistic estimation technique in cooperation with CI. We implement Poc and Poid on a testbed of 1 USRP and 50 TelosB nodes, the experimental results show that the accuracy of Poc is above 97.9%, and the accuracy of Poid is above 96.5% for most cases. In addition to their high accuracy, our methods demonstrate significant advantages over the state-of-the-art solutions in terms of substantially lower energy consumption and estimation delay.

On the Reception of Concurrent Transmissions in Wireless Sensor Networks

“…(t) φ I (t) dt = A u 4 cos ϕ c cos ϕ p τ β I k−1 + (2T − τ ) β I k − 2T π sin ϕ p β I k−1 − β I k − sin ϕ c sin ϕ p τ Q β Q k Q −1 + 2T − τ Q β Q k Q + 2T π cos ϕ p β Q k Q −1 − β Q k Q A. Integrating the Term X 1 (2k+1)T (2k−1)T b I (t − τ ) (cos ϕ p + cos 2ω p t cos ϕ p + sin 2ϕ p t sin ϕ p ) dt = cos ϕ pˆ( 2k+1)T (2k−1)T b I (t − τ ) dt + cos ϕ pˆ( 2k+1)T (2k−1)T b I (t − τ ) cos 2ω p t dt + sin ϕ pˆ( 2k+1)T (2k−1)T b I (t − τ ) sin 2ω p t dt = cos ϕ p S I k (1) + cos ϕ p S I k (cos 2ω p t) + sin ϕ p S I k (sin 2ω p t)By using the results in Appendix A (Eqs (13),(15). and(17)), we can reformulate this equation to = cos ϕ p τ β I k−1 + (2T − τ ) β I k ϕ p sin 2ϕ p + sin ϕ p (1 − cos 2ϕ p )) + β I k 2ω p (cos ϕ p sin 2ϕ p + sin ϕ p (1 − cos 2ϕ p )) Simplifying this equation yields the desired result.…”

Synchronous Transmissions in Low-Power Wireless: A Survey of Communication Protocols and Network Services

“…Strawman [88] Collision resolution Stairs [56] Collision resolution POC/POID [129] Collision resolution and leave the network. Applications use A 2 to reliably agree on, for example, cryptographic keys, channel-hopping sequences, or actuator commands, even in the presence of node or link failures.…”

“…The literature includes works that use synchronous transmissions to realize efficient collision resolution mechanisms [28,56,88,129]. In this case, synchronous transmissions are not employed to transmit actual application data, but to implement a signaling protocol invisible to upper layers.…”

Constructive Interference in 802.15.4: A Tutorial

“…These studies are concerned with understanding how constructive interference takes place, and focus on specific "atomic" issues, such as time drift, capture effect or packet length. 2) protocol proposals (Section V) which utilize CI to target a particular problem, such as data prediction [20], bulk transfer [21], neighbor counting and identifying [22], etc. through the proposal of new networking protocols.…”

“…It can be seen that P 3 doubles the throughput compared to Splash protocol. Different from the previous CI-based protocol designs focusing on conveying data to the destination, Dingming et al [22] utilize CI for neighbor discovery and identification. Counting and identify neighbors are two fundamental operations for most of low-power wireless networks.…”