Impact of Call Drop Ratio Over 5G Network

Impact of Call Drop Ratio Over 5G Network

Jay Kumar Pandey, Shahanawaj Ahamad, Vivek Veeraiah, Nishchal Adil, Dharmesh Dhabliya, Ashok Koujalagi, Ankur Gupta
Copyright: © 2023 |Pages: 24
DOI: 10.4018/978-1-6684-7000-8.ch011
OnDemand:
(Individual Chapters)
Available
$37.50
Current Special Offers
No Current Special Offers
TOTAL SAVINGS: $37.50

Abstract

The 5G network is the main topic of this investigation. 5G is expected to be far more advanced than 4G since it makes use of three distinct bands of the network spectrum. The acronym “5G” refers to the latest generation of wireless communications. With 5G, communications will improve all across the world. The purpose of this research is to examine the consequences of the increasing call drop ratio in 5G networks. In other words, if a user's current session is interrupted, they will need to make a new connection to continue using the service. One area where 5G excels over its predecessors, 4G (and LTE), is in reducing latency. Also, there would be fewer lost calls for individuals utilizing VoIP because network uptime will have risen significantly. Reduced call failure rates lead to happier customers.
Chapter Preview
Top

1 Introduction

5G improves global connection. This study examines the call drop ratio on 5G networks. A call drop indicates a user's ongoing session is dropped, necessitating a new connection to resume services. 5G offers better latency than 4G (and LTE). Increased network uptime means fewer lost VoIP calls. Fewer dropped calls improve customer satisfaction (Aldmour et al., 2017). In section 1 the call drop ratio and key performance indicator optimization for call drop ratio are considered. Then Radio-Induced Call Drops is elaborated with hardware execution failure. Then evaluation of wireless toward 5G along with most compelling aspects is presented. Section also considers optimum 5G and performance indicators of 5G such as throughput, deployment, mobility, connected devices, energy efficiency, data volume, latency and reliability. Section 2 is considered research related to 5G network. In the field of mobile cellular networks, there have been several studies that have investigated the 5g network. A few of the authors focused their attention on the percentage of dropped calls on 5G networks. Section 3 is focused on the challenges and issues faced by 5G networks (Anand et al., 2018).

Those research faced issues related to call drop, performance, error rate and accuracy. Section 4 is presenting the process flow of overall work where WSN, localization, machine learning and call drop ratio related research work are studied and problems such as call drop, performance, error, accuracy are identified. Then a novel approach for mobile node localization has been proposed that is making use of machine learning and considering call drop ratio. Finally the performance and accuracy evaluation has been made in order to find the reliability of work. Section 5 is presenting the simulation results for optimized and non optimized dataset. Section 6 is considering conclusion while section 7 is focused on future scope (Al-Maitah et al., 2018).

1.1 Call Drop Ratio

The percentage of phone conversations that are disconnected mid-conversation due to technical difficulties is known as the dropped-call rate (DCR) in the field of telecommunications. Typically, this proportion is expressed as a share (or percentage) of total calls.

978-1-6684-7000-8.ch011.m01

The number of call setup success times+1: After the Alerting message is received.

1.2 KPI (Key Performance Indicator) Optimization for Call Drop Ratio

The percentage of calls lost over LTE is a crucial key performance indicator. Since the advent of VoLTE, this KPI has taken on increased significance in LTE, and as a result, every network is working to enhance it. A call drop in LTE is the interruption of an active session, necessitating the establishment of a new connection before further use is possible. Upon inspection of the Context Release message, the eNB will recognize this as an anomalous release for reasons indicated by the cause code (Anioke et al., 2015).

Complete Chapter List

Search this Book:
Reset