Smart Channel Sounder for 5G IoT: From Wireless Big Data to Active Communication - Xuhong Chen; Shanyun Liu; Jiaxun Lu; Pingyi Fan; Khaled Ben Letaief (IEEE Access)
Internet-of-Things (IoT) will connect billions of smart devices and generate inundant data through prominent solutions, such as machine type communication. The Third Generation Partnership Project has launched the corresponding standards for multiple heterogeneous wireless smart devices in the long term evolution (LTE)/LTE-advanced. In the forthcoming years, the valuable information hidden in the deluge of data will be extracted and utilized in every field to improve quality and efficiency. However, the bottleneck of realizing this magnificent vista of future intelligent lives lies in how to satisfy the practical demands to transmit huge data volume through efficient wireless communication in diverse scenarios. Herein, multi-scenario wireless communication triggers critical problems in wireless channel modeling and soundings for 5G IoT, which by far, are understudied. In this paper, we introduce a general wireless channel model and its multiple up-to-date corresponding channel sounding methods for future 5G IoT green wireless communication. Through adopting the perspective of wireless big data excavation, the smart channel sounder transforms the traditional passive wireless communication scheme into an active expectation-guaranteed wireless communication scheme, which helps achieve efficient and green communication. To demonstrate the validity and efficiency of this smart sounder scheme, we make a compatible prototype testified in multiple scenarios. The multiple real-scenario experiments demonstrate that the smart sounder can function effectively, especially in those scenarios where traditional channel state information is not available or imperfect.