PERFORM Publications

Keyword search (4,163 papers available)

Title		Authors	PubMed ID
1	Age estimation via electrocardiogram from smartwatches	Adib A; Zhu WP; Ahmad MO;	41142465 ENCS
2	Robust landmark-based brain shift correction with a Siamese neural network in ultrasound-guided brain tumor resection	Pirhadi A; Salari S; Ahmad MO; Rivaz H; Xiao Y;	36306056 PERFORM
3	DiffeoRaptor: diffeomorphic inter-modal image registration using RaPTOR	Masoumi N; Rivaz H; Ahmad MO; Xiao Y;	36173541 ENCS
4	Multimodal 3D ultrasound and CT in image-guided spinal surgery: public database and new registration algorithms	Masoumi N; Belasso CJ; Ahmad MO; Benali H; Xiao Y; Rivaz H;	33683544 PERFORM
5	Cluster based statistical feature extraction method for automatic bleeding detection in wireless capsule endoscopy video.	Ghosh T, Fattah SA, Wahid KA, Zhu WP, Ahmad MO	29407997 IMAGING
6	A Crowdsensing Based Analytical Framework for Perceptional Degradation of OTT Web Browsing.	Li K, Wang H, Xu X, Du Y, Liu Y, Ahmad MO	29762493 ENCS
7	Image denoising via overlapping group sparsity using orthogonal moments as similarity measure.	Kumar A, Ahmad MO, Swamy MNS	30392726 ENCS
8	Big Data-Driven Cellular Information Detection and Coverage Identification.	Wang H, Xie S, Li K, Ahmad MO	30813353 ENCS

Title:	Big Data-Driven Cellular Information Detection and Coverage Identification.
Authors:	Wang H, Xie S, Li K, Ahmad MO
Link:	https://www.ncbi.nlm.nih.gov/pubmed/30813353?dopt=Abstract
Publication:
Keywords:
PMID:	30813353	Category:	Sensors (Basel)	Date Added:	2019-06-04
Dept Affiliation:	ENCS 1 College of Smart City, Beijing Union University, Beijing 100101, China. 161081210208@buu.edu.cn. 2 College of Smart City, Beijing Union University, Beijing 100101, China. 171081210207@buu.edu.cn. 3 College of Smart City, Beijing Union University, Beijing 100101, China. like@buu.edu.cn. 4 Department of Electrical and Computer Engineering, Concordia University, Montreal, QC H3G IM8, Canada. omair@ece.concordia.ca.

Description:

Big Data-Driven Cellular Information Detection and Coverage Identification.

Sensors (Basel). 2019 Feb 22;19(4):

Authors: Wang H, Xie S, Li K, Ahmad MO

Abstract

As one of the core data assets of telecom operators, base station almanac (BSA) plays an important role in the operation and maintenance of mobile networks. It is also an important source of data for the location-based service (LBS) providers. However, it is always less timely updated, nor it is accurate enough. Besides, it is not open to third parties. Conventional methods detect only the location of the base station (BS) which cannot satisfy the needs of network optimization and maintenance. Because of these drawbacks, in this paper, a big-data driven method of BSA information detection and cellular coverage identification is proposed. With the help of network-related data crowd sensed from the massive number of smartphone users in the live network, the algorithm can estimate more parameters of BSA with higher accuracy than conventional methods. The coverage capability of each cell was also identified in a granularity of small geographical grids. Computational results validate the proposed algorithm with higher performance and detection ability over the existing ones. The new method can be expected to improve the scope, accuracy, and timeliness of BSA, serving for wireless network optimization and maintenance as well as LBS service.

PMID: 30813353 [PubMed - indexed for MEDLINE]

BookR: School of Health Core Facilities Booking

"Ahmad MO" Authored Publications:

Search Publications

No results