A comparative assessment of GSM and UMTS Networks

It is common knowledge that the transition of mobile networks from one generation to another is basically for the improvement in the network’s Quality of Service (QoS). Bearing this in mind, we will assumme that the Universal Mobile Telecommunication System (UMTS) will outperform the Global System for Mobile Communication (GSM), hence, the motivation to conduct this study in Calabar, Nigeria, for four mobile networks; MTN, Airtel, Globacom and 9mobile. With the aid of a TEMS investigation software installed in a laptop, a measurement campaign was carried out and log files collected, with focus on Call Setup Success Rate (CSSR), Dropped Call Rate (DCR), Handover Success Rate (HOSR), Call Setup Time (CST), network coverage and network quality. The collected data was analyzed with the aid of a TEMS discovery software. The analyzed data for each Key Performance Indicator (KPI) was compared with the minimum benchmark of the telecommunications regulatory body, the Nigerian Communication Commission (NCC). Result reveal that there was no outright improvement in the QoS and there was fluctuation in the QoS provided by the network operators. We therefore conclude that the network operators, either did not make accurate planning before installing their base stations or do not optimize their networks frequently and this led to poor QoS in most cases.

IMPROVEMENT OF CALL SETUP TIME DURING CIRCUIT SWITCHED FALLBACK

In handover procedure, target cell would be prepared and UE will move on target cell based on the configuration sent by source eNodeB to User Equipment. Cell Reselection happens only when the user equipment (or Mobile Phone) is in Idle MODE, and the User Equipment needs to go a more appropriate cell. The main feature of CSFB Ps handover does not interrupt data transfer when switching from Long Term Evolution to UTRAN/GSM. After switching to 3G is already in connected mode it does not waste time to switch to connected mode. This feature let us improve call setup time when we make call in LTE.

Analysis of 4G Network Performance in Malang Region

The implementation of LTE in Indonesia has experienced problems, especially in maintaining the performance of radio networks due to the increasing number of users and less than optimal coverage quality. This research will conduct an analysis of the performance of the 4G LTE network with a case study in the area around Jalan Jend. Basuki Rachmat and Malang City Station. The Key Performance Indicator (KPI) parameters used to measure the performance of the 4G LTE network in this study include RRC setup success rate, ERAB setup success rate, and Call setup success rate Accessibility, call drop rate (VoiP), service drop rate (all). Retainability, handover, Throughput and Radio Frequency (RF), data obtained from drive tests and statistical data.From the standard KPI data for the Drive test area, Jend.basuki Rachmat has a value above -100 dBm, the percentage of power transmitted is 100% with a download value of 98.83% throughput of more than 265 Mbps and an upload value of 100% throughputI of more than 265 Mbps. As well as the Malang City Station area has a value above -100 dBm, the percentage of transmitted power is 92.39% with a download value of 96.12% throughput of more than 265 Mbps and an upload value of 100% throughputI of more than 265 Mbps. The parameters of Accessibility, Retainability, Mobility, integrity and Radio Frequency (RF) must comply with KPI standards in order to get maximum performance according to user needs.

Analysis of International Mobile Roaming Services with Smart Call Assistant System in GSM Originating Call

In this research, it takes a trace log data with real testing using the Polystar and TrafficNews to know the comparison operator Telkomsel network calls with and without the SCA, as well as performance data call in roaming of Roamware SCA tools to know the Key Performance Indicator (KPI) from the parameters of the Call Setup Success Rate (CSSR) and Call Drop Rate (CDR) then be processed and analyzed to find out the quality of service the influence of SCA implementation calls the overall international operators in the three countries with the highest incoming data so that it could become the next parameter in the repair services provided. Results of the study to the difference between the signals operators are implemented with the SCA system of the inbound roaming customers. CSSR percentage in average in 3 countries, Australia, China, Singapore prior to SCA system in May of 81.48%, while after system restored by SCA of 90.98%, where after the repaired system SCA standard KPIS PT. Telkomsel i.e. normal state – good, whereas the percentage KPI failure calls (CDR) in 3 countries, Australia, China, Singapore prior to SCA system in May of 18.52%, while after the repaired system SCA amounted to 9.02%, where after improved system SCA standard KPI applied PT. Telkomsel into normal state.

A Cross-Layer Design for a Multihop, Self-Healing, and Self-Forming Tactical Network

In mission and time critical applications, bandwidth and delay optimizations are the key goals of communication systems. This paper presents a cross-layer framework design that reduces the call setup time, provides collision-free communication, and reuses the empty slots of Time Division Multiple Access (TDMA) protocol which otherwise causes low throughput and large delay. As number of communicating nodes in tactical networks is small as compared to commercial mobile ad hoc networks (MANETs), classical TDMA will yield huge number of empty slots and any Carrier Sense Multiple Access/Collision Detection (CSMA/CD) technique may cause more delay in some critical scenarios. Proposed methodology gives a Cross-Layer Architecture for Network (NET) Layer and Medium Access Control (MAC) Layer. Our design provides bandwidth efficient, collision-free communication to Software-Defined Radios (SDRs) in self-forming and self-healing tactical networks with low call setup time and multihop routing. For this purpose TDMA as MAC layer protocol and Ad Hoc On Demand Distance Vector (AODV) as Network Layer Routing Protocol are used. Our slot allocation (SA) algorithm, Cross-Layer TDMA (CL-TDMA), consists of control phase where AODV control packets are exchanged and data transfer phase where transmission of data and voice occurs. All active radios in vicinity gather information about communicating nodes based on the exchange of control packets by SDRs. Our algorithm then uses this information to help all active SDRs find slot(s) that will be used for collision-free transmission. A number of experiments are performed to establish improved performance of the proposed technique compared to other established techniques and protocols.

A Comparison Between Inter-Asterisk eXchange Protocol and Jingle Protocol: Session Time

Over the last few years, many multimedia conferencing and Voice over Internet Protocol (VoIP) applications have been developed due to the use of signaling protocols in providing video, audio and text chatting services between at least two participants. This paper compares between two widely common signaling protocols: InterAsterisk eXchange Protocol (IAX) and the extension of the eXtensible Messaging and Presence Protocol (Jingle) in terms of delay time during call setup, call teardown, and media sessions.

Measurement of Mobile Switching Centres Throughput in GSM Network Integrating Sliding Window Algorithm with a Single Server Finite Queuing Model

The sliding window algorithm proposed for determining an optimal sliding window does not consider the waiting times of call setup requests of a mobile station in queue at a Mobile Switching Centre (MSC) in the Global System for Mobile (GSM) Communication Network. This study proposes a model integrating the sliding window algorithm with a single server finite queuing model, referred to as integrated model for measurement of realistic throughput of a MSC considering the waiting times of call setup requests. It assumes that a MSC can process one call setup request at a time. It is useful in determining an optimal sliding window size that maximizes the realistic throughput of a MSC. Though the model assumes that a MSC can process one call setup request at a time, its scope can be extended for measuring the realistic throughput of a MSC that can process multiple call setup requests at a time.