Multi-Node RSS-based Localization with the Aid of Compressed Sensing: An 1-localization Approach


E. Zandi, R. Mathar,


        In this work try we try to estimate the positions of multiple co-channel wireless nodes along with the unknown transmit power of them. The propagation channel is assumed to be log-normal shadowing model. We propose an unbiased estimator. The underlying complicated optimization problem has a combinatorial nature that selects the best grid points as the location of the targets. We then convert the combinatorial problem to a convex form by means of `1-minimization, or precisely a technique which is inspired by the theory of compressed sensing (CS). The performance of the estimator is justified to be good using simulations.

BibTEX Reference Entry 

	author = {Ehsan Zandi and Rudolf Mathar},
	title = "Multi-Node {RSS}-based Localization with the Aid of Compressed Sensing: An {$\ell_1$}-localization Approach",
	pages = "1-8",
	booktitle = "23rd International ITG Workshop on Smart Antennas (WSA 2019)",
	address = {Vienna, Austria},
	month = Apr,
	year = 2019,
	hsb = RWTH-2019-04279,


 Download paper  Download bibtex-file

This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights there in are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.