Spectrum cartography aims at estimating the pattern of wideband signal power propagation over a region of interest (i.e. the radio map)-from limited samples taken sparsely over the region. Classical cartography methods are mostly concerned with recovering the aggregate radio frequency (RF) information while ignoring the constituents of the radio map-but fine-grained emitter-level RF information is of great interest. In addition, most existing cartography methods are based on random geographical sampling that is considered difficult to implement in some cases, due to legal/privacy/security issues. The theoretical aspects (e.g., identifiability of the radio map) of many existing methods are also unclear. In this work, we propose a radio map disaggregation method that is based on coupled block-term tensor decomposition. Our method guarantees identifiability of the individual wideband radio map of each emitter in the geographical region of interest (thereby that of the aggregate radio map as well), under some realistic conditions. The identifiability result holds under a large variety of geographical sampling patterns, including many pragmatic systematic sampling strategies. We also propose an effective optimization algorithm to carry out the formulated coupled tensor decomposition problem.
|Original language||English (US)|
|Title of host publication||Conference Record - 53rd Asilomar Conference on Circuits, Systems and Computers, ACSSC 2019|
|Editors||Michael B. Matthews|
|Publisher||IEEE Computer Society|
|Number of pages||5|
|State||Published - Nov 2019|
|Event||53rd Asilomar Conference on Circuits, Systems and Computers, ACSSC 2019 - Pacific Grove, United States|
Duration: Nov 3 2019 → Nov 6 2019
|Name||Conference Record - Asilomar Conference on Signals, Systems and Computers|
|Conference||53rd Asilomar Conference on Circuits, Systems and Computers, ACSSC 2019|
|Period||11/3/19 → 11/6/19|
Bibliographical noteFunding Information:
ACKNOWLEDGMENT The work of X. Fu and M. Hong is supported in part by the National Science Foundation under Project ECCS 1808159 and the Army Research Office under Project ARO W911NF-19-1-0247. The work of G. Zhang and J. Wang is supported in part by the National Key R&D Program of China under Grant 2018YFC0807101, the National Research Program of China under Grant 9020302, the Foundation of National Key Laboratory of Science and Technology on Communications, the Innovation Fund of NCL (IFN), and the National Natural Science Foundation of China (NSFC) under Grant 61471099.
© 2019 IEEE.
- block term decomposition
- coupled tensor decomposition
- radio map
- spectrum cartography