EVALUATION OF VOICE TRANSMISSION QUALITY IN THE LTE NETWORKS

Background. LTE mobile networks combine packet network technology and radio technology. Parameters of packet and radio subsystems significantly affects the quality of all traffic types transmission, especially telephone traffic, as the most demanding to such parameters of network transmission as delay, jitter and packet loss rate. The recommendations of the International Telecommunication Union and the documents of the partner organization of telecommunications operators (3GPP) contain hypothetical reference models, targets for end-to-end connection quality, and lists the factors that affect the quality (QoS) of VoLTE services. In addition, the network points are shown where you need to measure the quality of telephone traffic and tools for quality assessment. The quality of telephony services is assessed according to the E-model using the method of determining the mean opinion score (MOS). However, this technique is intended primarily to determine the MOS during the network planning. To calculate the MOS in a working network, you have to measure such network performance first such as voice delay and packet loss rate. This article presents the method of calculating MOS in the LTE network based on the E-model and presents the results of practical quality studies. Objective. The purpose of this article is research the impact of delay and packet loss ratio and voice codec characteristics in the real LTE network on quality of telephone services. Methods. Analysis of factors affecting on telephone services quality and analysis MOS assessment methods. Practical studies of the delay and packet loss ratio affect the MOS level in various conditions of radio coverage and network load. Results. Practical results of delay and packet loss ratio influence on the telephone services quality in the LTE network. Calculated MOS based on the practically measured delay and packet loss ratio. Conclusions. The combination of packet technologies, modern AMR-WB codecs and QoS support mechanisms in the LTE networks provides high quality perception of voice messages at the level of not less than 4 on the MOS scale. With a delay not exceeding 180 ms, a sufficiently high quality of voice transmission is ensured (MOS ≈ 4). VoLTE technology using the AMR-WB codec is quite resistant to packet loss and provides high quality perception of voice messages at a packet loss ratio of up to 1%.

Analysis of the Performance of Cellular Mobile Networks for the Remote-Control Systems of Unmanned Aerial Vehicles. Summary of the Doctoral Thesis

The Thesis is concerned with assessing the suitability of LTE (4G) cellular networks for the remote control of low-flying UAVs. To solve this problem, an approach to the analysis of the delay values in cellular networks has been developed, which makes it possible to estimate the delays of individual cells and overall cellular network. Requirements for delays in the UAV control channel were developed, conclusions were drawn about the suitability of the LTE network as a communication solution for the UAV remote control. A method for calculating the effect of parallel redundancy is proposed, and an experimental assessment of the possibility of using two existing solutions for parallel redundancy in LTE networks is carried out. In addition, a compact technical solution for analyzing the level of base station signals was demonstrated.

Artificial Neural Network-Based Uplink Power Prediction From Multi-Floor Indoor Measurement Campaigns in 4G Networks

Paving the path toward the fifth generation (5G) of wireless networks with a huge increase in the number of user equipment has strengthened public concerns on human exposure to radio-frequency electromagnetic fields (RF EMFs). This requires an assessment and monitoring of RF EMF exposure, in an almost continuous way. Particular interest goes to the uplink (UL) exposure, assessed through the transmission power of the mobile phone, due to its close proximity to the human body. However, the UL transmit (TX) power is not provided by the off-the-shelf modem and RF devices. In this context, we first conduct measurement campaigns in a multi-floor indoor environment using a drive test solution to record both downlink (DL) and UL connection parameters for Long Term Evolution (LTE) networks. Several usage services (including WhatsApp voice calls, WhatsApp video calls, and file uploading) are investigated in the measurement campaigns. Then, we propose an artificial neural network (ANN) model to estimate the UL TX power, by exploiting easily available parameters such as the DL connection indicators and the information related to an indoor environment. With those easy-accessed input features, the proposed ANN model is able to obtain an accurate estimation of UL TX power with a mean absolute error (MAE) of 1.487 dB.

The Impact of Healthcare Traffic Over H2H and M2M Networks During the Spread Phase of Pandemic Diseases

Recently, the coronavirus pandemic has caused widespread panic around the world. Modern technologies can be used to monitor and control this highly contagious disease. A plausible solution is to equip each patient who is diagnosed with or suspected of having COVID-19 with sensors that can monitor various healthcare and location parameters and report them to the desired facility to control the spread of the disease. However, the simultaneous communication of numerous sensors installed in the majority of an area’s population results in a huge burden on existing Long-Term Evolution (LTE) networks. The existing network becomes oversaturated because it has to manage two kinds of traffic in addition to normal traffic (text, voice, and video): healthcare traffic generated by a large number of sensors deployed over a huge population, and extra traffic generated by people contacting their family members via video or voice calls. In pandemics, e-healthcare traffic is critical and should not suffer packet loss or latency due to network overload. In this research, we studied the performance of existing networks under various conditions and predicted the severity of network degradation in an emergency. We proposed and evaluated three schemes (doubling bandwidth, combining LTE-A and LTE-M networks, and request queuing) for ensuring quality of service (QoS) of healthcare sensor (HCS) network traffic without perturbation from routine human-to-human or machine-to-machine communications. Finally, we simulated all proposed schemes and compared them with existing network scenarios. The results have showed that when we have doubled the bandwidth the SCR of all traffic was 100% as same as the Queue strategy. However, when we prioritized the HCS traffic the SCR has recorded 100%, while H2H and M2M traffic has recorded 73%. When we used hybrid network LTE-A and LTE-M network, the HCS and H2H traffic has recorded 100% and M2M traffic has recorded 70%. After analyzing the results, we conclude that our proposed queuing schemes performed well in all conditions and provide the best QoS for HCS traffic.