Abstract:

The large-scale Internet of things with multi observation phenomenon uses orthogonal multiple access (OMA) mechanism to transmit the observation data of distributed nodes, which will cause great transmission delay and lead to the loss of timeliness of data.To cope with the heavy latency of observations due to OMA, an efficient scheme integrating compressed sensing (CS) technique with communication was proposed for large-scale Internet of things to monitor multiple phenomena.In this proposed scheme, the nodes monitoring different phenomena were assigned to different time durations for transmission.During the assigned time duration, all nodes concurrently transmitted observations to the fusion center (FC)for CS measurement, and the FC recovered observation by CS algorithms.To evaluate the performance of the proposed scheme, the achievable rate of the observed phenomena was derived, which was closely related to the time allocation of clusters.To further improve the performance, the optimization problems of time allocation were studied under the two objectives of maximizing the total rate and ensuring the fairness of observation.Finally, the performance was verified and analyzed by numerical simulation.The simulation results show that the achievable rate of observations for different phenomena is improved the proposed scheme significantly compared with OMA schemes.

Key words: large-scale Internet of things, multiple phenomena monitoring, CS-communication integration