TY - JOUR
T1 - Optimal fronthaul quantization for cloud radio positioning
AU - Jeong, Seongah
AU - Simeone, Osvaldo
AU - Haimovich, Alexander
AU - Kang, Joonhyuk
N1 - Funding Information:
This work was supported by the ICT R and D Program of the Ministry of Science, ICT and Future Planning/Institute for Information and Communications Technology Promotion (B0101-15-1372: Development of Mobile Multi-mode Transmission Technology Based on Spatial Spreading).
Publisher Copyright:
© 1967-2012 IEEE.
PY - 2016/4
Y1 - 2016/4
N2 - Wireless positioning systems that are implemented by means of a cloud radio access network (C-RAN) may provide cost-effective solutions, particularly for indoor localization. In a C-RAN, baseband processing, including localization, is carried out at a centralized control unit (CU) based on quantized baseband signals received from the radio units (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 Cramér-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.
AB - Wireless positioning systems that are implemented by means of a cloud radio access network (C-RAN) may provide cost-effective solutions, particularly for indoor localization. In a C-RAN, baseband processing, including localization, is carried out at a centralized control unit (CU) based on quantized baseband signals received from the radio units (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 Cramér-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.
KW - Cloud Radio Access Networks (C-RANs)
KW - Cramer-Rao bound (CRB)
KW - localization
KW - quantization
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U2 - 10.1109/TVT.2015.2431491
DO - 10.1109/TVT.2015.2431491
M3 - Article
AN - SCOPUS:84964614193
SN - 0018-9545
VL - 65
SP - 2763
EP - 2768
JO - IEEE Transactions on Vehicular Communications
JF - IEEE Transactions on Vehicular Communications
IS - 4
M1 - 7104164
ER -