کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6879993 1443299 2018 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Joint localization of multiple sources from incomplete noisy Euclidean distance matrix in wireless networks
ترجمه فارسی عنوان
محلی سازی چندگانه منابع چندگانه از ماتریس فاصله اقلیدسی پر سر و صدا نهایی در شبکه های بی سیم
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر شبکه های کامپیوتری و ارتباطات
چکیده انگلیسی
One major challenge of massive wireless networks is to identify the locations of source nodes from partially observed and noisy distance information. This is especially important for wireless sensor networks (WSN) and wireless local area networks (WLAN). In this paper, we propose a unified localization framework of multiple sources from an Euclidean distance matrix (EDM) with noise and outliers both in WSN and WLAN scenarios. We first develop a semidefinite programming (SDP) based low rank matrix completion (LRMC) estimator by using the semidefinite embedding lemma to recover EDM. Based on our recovered EDM, two robust localization estimators, namely, semidefinite relaxation localization (SDRL) and weighted semidefinite relaxation localization (WSDRL), are derived to efficiently relax our non-convex localization problem into a convex one, and yield more accuarate location estimates. As compared with existing techniques, our proposed techniques are more robust to noise and outliers with higher accuracies both in EDM recovery and source localization. Simulations and real data experiments are included to evaluate the performance of the proposed algorithms by comparing them with some existing methods.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computer Communications - Volume 122, June 2018, Pages 20-29
نویسندگان
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