Online Mobile User Speed Estimation: Performance and Tradeoff Considerations

International audienceThis paper presents an online algorithm for mobile user speed estimation in 3GPP Long Term Evolution (LTE)/LTE-Advanced (LTE-A) networks. The proposed method leverages on uplink (UL) sounding reference signal (SRS) power measurements performed at the base station, also known as eNodeB (eNB), and remains effective even under large sampling period. Extensive performance evaluation of the proposed algorithm is carried out using field traces from realistic environment. The on-line solution is proven highly efficient in terms of computational requirement, estimation delay, and accuracy. In particular, we show that the proposed algorithm can allow for the first speed estimation to be obtained after 10 seconds and with an average speed underestimation error of 14 kmph. After the first speed acquisition, subsequent speed estimations can be obtained much faster (e.g., each second) with limited implementation cost and still provide high accuracy

Handover management strategies in LTE-advanced heterogeneous networks.

Doctoral Degree. University of KwaZulu-Natal, Durban.Meeting the increasing demand for data due to the proliferation of high-specification mobile devices in the cellular systems has led to the improvement of the Long Term Evolution (LTE) framework to the LTE-Advanced systems. Different aspects such as Massive Multiple-Input Multiple Output (MIMO), Orthogonal Frequency Division Multiple Access (OFDMA), heterogeneous networks and Carrier Aggregation have been considered in the LTE-Advanced to improve the performance of the system. The small cells like the femtocells and the relays play a significant role in increasing the coverage and the capacity of the mobile cellular networks in LTE-Advanced (LTE-A) heterogeneous network. However, the user equipment (UE) are faced with the frequent handover problems in the heterogeneous systems than the homogeneous systems due to the users‟ mobility and densely populated cells. The objective of this research work is to analyse the handover performance in the current LTE/LTE-A network and to propose various handover management strategies to handle the frequent handover problems in the LTE-Advance heterogeneous networks. To achieve this, an event driven simulator using C# was developed based on the 3GPP LTE/LTE-A standard to evaluate the proposed strategies. To start with, admission control which is a major requirement during the handover initiation stage is discussed and this research work has therefore proposed a channel borrowing admission control scheme for the LTE-A networks. With this scheme in place, resources are better utilized and more calls are accepted than in the conventional schemes where the channel borrowing is not applied. Also proposed is an enhanced strategy for the handover management in two-tier femtocell-macrocell networks. The proposed strategy takes into consideration the speed of user and other parameters in other to effectively reduce the frequent and unnecessary handovers, and as well as the ratio of target femtocells in the system. We also consider scenarios such as the one that dominate the future networks where femtocells will be densely populated to handle very heavy traffic. To achieve this, a Call Admission Control (CAC)-based handover management strategy is proposed to manage the handover in dense femtocell-macrocell integration in the LTE-A network. The handover probability, the handover call dropping probability and the call blocking probability are reduced considerably with the proposed strategy. Finally, the handover management for the mobile relays in a moving vehicle is considered (using train as a case study). We propose a group handover strategy where the Mobile Relay Node (MRN) is integrated with a special mobile device called “mdev” to prepare the group information prior to the handover time. This is done to prepare the UE‟s group information and services for timely handover due to the speed of the train. This strategy reduces the number of handovers and the call dropping probability in the moving vehicle.Publications and conferences listed on page iv-v

An overview of emergency communication networks

In recent years, major natural disasters and public safety accidents have frequently occurred worldwide. In order to deal with various disasters and accidents using rapidly deployable, reliable, efficient, and stable emergency communication networks, all countries in the world are strengthening and improving emergency communication network construction and related technology research. Motivated by these situations, in this paper, we provide a state-of-the-art survey of the current situation and development of emergency communication networks. In this detailed investigation, our primary focus is the extensive discussion of emergency communication network technology, including satellite networks, ad hoc networks, cellular networks, and wireless private networks. Then, we explore and analyze the networks currently applied in emergency rescue, such as the 370M narrowband private network, broadband cluster network, and 5G constellation plan. We propose a broadband-narrowband integrated emergency communication network to provide an effective solution for visual dispatch of emergency rescue services. The main findings derived from the comprehensive survey on the emergency communication network are then summarized, and possible research challenges are noted. Lastly, we complete this survey by shedding new light on future directions for the emergency communication network. In the future, the emergency network will develop in the direction of intelligence, integration, popularization, and lower cost, and space-air-ground-sea integrated networks. This survey provides a reference basis for the construction of networks to mitigate major natural disasters and public safety accidents

Applications

Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications

Stochastic Geometry Based Analysis of Capacity, Mobility and Energy Efficiency for Dense Heterogeneous Networks

In recent years, the increase in the population of mobile users and the advances in computational capabilities of mobile devices have led to an exponentially increasing traffic load on the wireless networks. This trend is foreseen to continue in the future due to the emerging applications such as cellular Internet of things (IoT) and machine type communications (MTC). Since the spectrum resources are limited, the only promising way to keep pace with the future demand is through aggressive spatial reuse of the available spectrum which can be realized in the networks through dense deployment of small cells. There are many challenges associated with such densely deployed heterogeneous networks (HetNets). The main challenges which are considered in this research work are capacity enhancement, velocity estimation of mobile users, and energy efficiency enhancement. We consider different approaches for capacity enhancement of the network. In the first approach, using stochastic geometry we theoretically analyze time domain inter-cell interference coordination techniques in a two-tier HetNet and optimize the parameters to maximize the capacity of the network. In the second approach, we consider optimization of the locations of aerial bases stations carried by the unmanned aerial vehicles (UAVs) to enhance the capacity of the network for public safety and emergency communications, in case of damaged network infrastructure. In the third approach, we introduce a subsidization scheme for the service providers through which the network capacity can be improved by using regulatory power of the government. Finally, we consider the approach of device-to-device communications and multi-hop transmissions for enhancing the capacity of a network. Velocity estimation of high speed mobile users is important for effective mobility management in densely deployed small cell networks. In this research, we introduce two novel methods for the velocity estimation of mobile users: handover-count based velocity estimation, and sojourn time based velocity estimation. Using the tools from stochastic geometry and estimation theory, we theoretically analyze the accuracy of the two velocity estimation methods through Cramer-Rao lower bounds (CRLBs). With the dense deployment of small cells, energy efficiency becomes crucial for the sustained operation of wireless networks. In this research, we jointly study the energy efficiency and the spectral efficiency in a two-tier HetNet. We optimize the parameters of inter-cell interference coordination technique and study the trade-offs between the energy efficiency and spectral efficiency of the HetNet

Applications

Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications