%0 Journal Article
%T Optimal Fronthaul Quantization for Cloud Radio Positioning
%A Seongah Jeong
%A Osvaldo Simeone
%A Alexander Haimovich
%A Joonhyuk Kang
%J Mathematics
%D 2014
%I arXiv
%X Wireless positioning systems that are implemented by means of a Cloud Radio Access Networks (C-RANs) may provide cost-effective solutions, particularly for indoor localization. In a C-RAN, the baseband processing, including localization, is carried out at a centralized control unit (CU) based on quantized baseband signals received from the RUs over finite-capacity fronthaul links. In this paper, the problem of maximizing the localization accuracy over fronthaul quantization/compression is formulated by adopting the Cram\'{e}r-Rao bound (CRB) on the localization accuracy as the performance metric of interest and information-theoretic bounds on the compression rate. The analysis explicitly accounts for the uncertainty of parameters at the CU via a robust, or worst-case, optimization formulation. The proposed algorithm leverages the Charnes-Cooper transformation and Difference-of-Convex (DC) programming, and is validated via numerical results.
%U http://arxiv.org/abs/1409.2095v3