A Joint Tensor Completion and Prediction Scheme for Multi-Dimensional Spectrum Map Construction

Spectrum data, which are usually characterized by many dimensions, such as location, frequency, time, and signal strength, present formidable challenges in terms of acquisition, processing, and visualization. In practice, a portion of spectrum data entries may be unavailable due to the interference during the acquisition process or compression during the sensing process. Nevertheless, the completion work in multi-dimensional spectrum data has drawn few attention to the researchers working in the eld. In this paper, we rst put forward the concept of spectrum tensor to depict the multi-dimensional spectrum data. Then, we develop a joint tensor completion and prediction scheme, which combines an improved tensor completion algorithm with prediction models to retrieve the incomplete measurements. Moreover, we build an experimental platform using Universal Software Radio Peripheral to collect real-world spectrum tensor data. Experimental results demonstrate that the effectiveness of the proposed joint tensor processing scheme is superior than relying on the completion or prediction scheme only

A Cloud-Based Architecture for the Internet of Spectrum Devices over Future Wireless Networks

The dramatic increase in data rates in wireless networks has caused radio spectrum usage to be an essential and critical issue. Spectrum sharing is widely recognized as an affordable, near-term method to address this issue. This paper first characterizes the new features of spectrum sharing in future wireless networks, including heterogeneity in sharing bands, diversity in sharing patterns, crowd intelligence in sharing devices, and hyperdensification in sharing networks. Then, to harness the benefits of these unique features and promote a vision of spectrum without bounds and networks without borders, this paper introduces a new concept of the Internet of spectrum devices (IoSDs) and develops a cloud-based architecture for IoSD over future wireless networks, with the prime aim of building a bridging network among various spectrum monitoring devices and massive spectrum utilization devices, and enabling a highly efficient spectrum sharing and management paradigm for future wireless networks. Furthermore, this paper presents a systematic tutorial on the key enabling techniques of the IoSD, including big spectrum data analytics, hierarchal spectrum resource optimization, and quality of experience-oriented spectrum service evaluation. In addition, the unresolved research issues are also presented