Multi-dimensional spectrum map construction: A tensor perspective

Spectrum data, which is usually characterized by many dimensions, such as location, frequency, time and signal strength, presents 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 the compression during the sensing process. However, the completion work in multi-dimensional spectrum data has drawn few attention. In this paper, we first put forward the concept of spectrum tensor to depict the multi-dimensional data, and then we invoke the recent theocratical advances of tensor completion algorithms to retrieve the incomplete measurements. Moreover, we also build an experimental platform using Universal Software Radio Peripheral (USRP) to collect real-world spectrum tensor data. Experimental results demonstrate that the effectiveness of the proposed spectrum tensor processing scheme is over the state-of-the-art spectrum matrix processing scheme.