scholarly journals A Statistical Approach to Determine Handover Success Using the Principle of Inclusion and Load Variation on Links in Wireless Networks

2015 ◽  
Vol 1 (1) ◽  
pp. 143-151
Author(s):  
Horace L KING ◽  
Urvashi Pal
Keyword(s):  
Statistical Approach ◽  
Success Probability ◽  
Signal Strength ◽  
Active Set ◽  
Network Resource ◽  
Site Specific ◽  
Load Variation ◽  
Soft Handover ◽  
Pilot Pollution ◽  
Pilot Power

In this paper we present a statistical approach to establish a more efficient mechanism to predict handover success probability on a link in a wireless Network. We develop formulations that are used in the analysis to determine a more effective approach that reduces soft handover occurrences hence reducing unnecessary Network resource consumption. This approach can exploit the soft handover overhead metric and by optimum dimensioning can estimate the active set responsiveness using conditional thresholds set in a given service area. Furthermore, we analyse load variation and the value of pilot power in a given cell and the effects of pilot pollution in a dynamic traffic environment. Results of the analysis are presented for the probability of handover success and plots of signal strength variation on selected links using defined site specific formulations.

scholarly journals Impact of soft handover and pilot pollution on video telephony in a commercial network

2010 ◽  
Author(s):  
Lu Chen ◽  
Kumbesan Sandrasegaran ◽  
Riyaj Basukala ◽  
Faisal Mohd. Madani ◽  
Cheng-Chung. Lin
Keyword(s):  
Video Telephony ◽  
Soft Handover ◽  
Pilot Pollution ◽  
Commercial Network

Measurement-based Statistical Method for Estimating and Verifying Signal Coverage and Coverage Probability in Urban Microcells

2018 ◽  
Vol 8 (6) ◽  
pp. 74
Author(s):  
Joseph Isabona ◽  
Kingsley Obahiagbon
Keyword(s):  
Outage Probability ◽  
Communication Networks ◽  
Coverage Probability ◽  
Statistical Approach ◽  
Radio Signal ◽  
Signal Strength ◽  
Signal Coverage ◽  
Radio Signals ◽  
Coverage Quality

Customer’s complaints and concerns about radio signal coverage at their home are important trigger to performance relevant drive test in the relevant area to observe the coverage quality. In this paper, statistical approach has been employed to assess the quality of the radio coverage and outage probability based on measured radio signals in an established UMTS network, operational in Ikoyi, a typical urban microcell in Nigerian environment. The results shows that the quality of radio signals at the cell edge is very poor in locations 2 and 4, as they recorded poor coverage probability performance of 89.25% and 81.72% and high outage probability performance of 10.74% and 18.28% respectively. It is also observed that the smaller the fade margin, the higher the outage probability and the lower the coverage reliability. This implies that the smaller the fade margin, the smaller the received signal strength at the MS and the more likely outage events. Hence, sufficient signal strength is needed at the mobile terminals at locations 2 and 4 in order to achieve the outage probability and coverage reliability required to effectively operate cellular communication networks.

scholarly journals Side-Information-Aided Preprocessing Scheme for Deep-Learning Classifier in Fingerprint-Based Indoor Positioning

Electronics ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 982 ◽  
Author(s):  
Yue Liu ◽  
Rashmi Sharan Sinha ◽  
Shu-Zhi Liu ◽  
Seung-Hoon Hwang
Keyword(s):  
Deep Learning ◽  
Side Information ◽  
Success Probability ◽  
Dynamic Environment ◽  
Signal Strength ◽  
Access Point ◽  
Indoor Positioning ◽  
Received Signal Strength ◽  
Learning Classifier ◽  
Learning Classifiers

Deep-learning classifiers can effectively improve the accuracy of fingerprint-based indoor positioning. During fingerprint database construction, all received signal strength indicators from each access point are combined without any distinction. Therefore, the database is created and utilised for deep-learning models. Meanwhile, side information regarding specific conditions may help characterise the data features for the deep-learning classifier and improve the accuracy of indoor positioning. Herein, a side-information-aided preprocessing scheme for deep-learning classifiers is proposed in a dynamic environment, where several groups of different databases are constructed for training multiple classifiers. Therefore, appropriate databases can be employed to effectively improve positioning accuracies. Specifically, two kinds of side information, namely time (morning/afternoon) and direction (forward/backward), are considered when collecting the received signal strength indicator. Simulations and experiments are performed with the deep-learning classifier trained on four different databases. Moreover, these are compared with conventional results from the combined database. The results show that the side-information-aided preprocessing scheme allows better success probability than the conventional method. With two margins, the proposed scheme has 6.55% and 5.8% improved performances for simulations and experiments compared to the conventional scheme. Additionally, the proposed scheme, with time as the side information, obtains a higher success probability when the positioning accuracy requirement is loose with larger margin. With direction as the side information, the proposed scheme shows better performance for high positioning precision requirements. Thus, side information such as time or direction is advantageous for preprocessing data in deep-learning classifiers for fingerprint-based indoor positioning.

Large-cluster and combined fluorescent and gold immunoprobes

1996 ◽  
Vol 54 ◽  
pp. 892-893
Author(s):  
Richard D. Powell ◽  
James F. Hainfeld ◽  
Carol M. R. Halsey ◽  
David L. Spector ◽  
Shelley Kaurin ◽  
...  
Keyword(s):  
Metal Cluster ◽  
Sulfonyl Chloride ◽  
Gel Filtration ◽  
Cross Linking ◽  
Site Specific ◽  
Fab Fragments ◽  
Cluster Label ◽  
Covalently Linked ◽  
Texas Red ◽  
Fold Excess

Two new types of covalently linked, site-specific immunoprobes have been prepared using metal cluster labels, and used to stain components of cells. Combined fluorescein and 1.4 nm “Nanogold” labels were prepared by using the fluorescein-conjugated tris (aryl) phosphine ligand and the amino-substituted ligand in the synthesis of the Nanogold cluster. This cluster label was activated by reaction with a 60-fold excess of (sulfo-Succinimidyl-4-N-maleiniido-cyclohexane-l-carboxylate (sulfo-SMCC) at pH 7.5, separated from excess cross-linking reagent by gel filtration, and mixed in ten-fold excess with Goat Fab’ fragments against mouse IgG (obtained by reduction of F(ab’)2 fragments with 50 mM mercaptoethylamine hydrochloride). Labeled Fab’ fragments were isolated by gel filtration HPLC (Superose-12, Pharmacia). A combined Nanogold and Texas Red label was also prepared, using a Nanogold cluster derivatized with both and its protected analog: the cluster was reacted with an eight-fold excess of Texas Red sulfonyl chloride at pH 9.0, separated from excess Texas Red by gel filtration, then deprotected with HC1 in methanol to yield the amino-substituted label.

The challenge of detecting modifications on proteins

2020 ◽  
Vol 64 (1) ◽  
pp. 135-153 ◽  
Author(s):  
Lauren Elizabeth Smith ◽  
Adelina Rogowska-Wrzesinska
Keyword(s):  
Mass Spectrometry ◽  
Protein Function ◽  
Chemical Properties ◽  
Lysine Acetylation ◽  
Mass Determination ◽  
Post Translational Modifications ◽  
Site Specific ◽  
The Common

Abstract Post-translational modifications (PTMs) are integral to the regulation of protein function, characterising their role in this process is vital to understanding how cells work in both healthy and diseased states. Mass spectrometry (MS) facilitates the mass determination and sequencing of peptides, and thereby also the detection of site-specific PTMs. However, numerous challenges in this field continue to persist. The diverse chemical properties, low abundance, labile nature and instability of many PTMs, in combination with the more practical issues of compatibility with MS and bioinformatics challenges, contribute to the arduous nature of their analysis. In this review, we present an overview of the established MS-based approaches for analysing PTMs and the common complications associated with their investigation, including examples of specific challenges focusing on phosphorylation, lysine acetylation and redox modifications.

Sign in / Sign up

Export Citation Format

Share Document