Compressive sensing based spectrum sharing and coexistence for machine-to-machine communications

In this paper we develop a new spectrum sharing scheme that uses compressive sensing to support the coexistence of the sporadic machine-to-machine (M2M) communications and the persistent conventional communications such as the 5G cellular transmissions within the same channel. The redundancy in the transmitted signals, such as training symbols, pilots, MAC overheads and correlated data, is exploited to create a sparse signal model. Compressive sensing techniques are then used to detect jointly all the transmitted signals from the mixture. The performance of the new scheme is analyzed. An M2M communication scenario in smart grid is simulated to verify the sparse signal model and the spectrum sharing scheme.