SigMix: Decoding Superimposed Signals for IoT

The growth of Internet of Things (IoT) is anticipated to accelerate in the coming years. However, the wireless spectrum is insufficient to support the ever-growing IoT applications. A promising solution is to allow concurrent wireless transmissions and decode the superimposed signal. To make this solution practical for IoT systems, dynamic channel conditions and hardware imperfections are the key practical challenges, but not yet be addressed in the past work, leading to a low decoding performance. In this article, we introduce SigMix, aiming to deal with the practical challenges by proposing a solution to decode the superimposed signal, and eventually boost the spectrum efficiency. To this end, we first derive a theoretical expression that reveals the close relationship between phase shifts among concurrently transmitted signals and the error probability in decoding the superimposed signal. Then, based on the theoretical expression, we propose a rotation code and an adaptive decoding scheme to largely reduce the decoding error probability. Extensive experiments have shown that the median bit-error-rate of our scheme is one-order lower than the state-of-the-art.