User Equipment Speed Research Articles

A Beamforming-Based Enhanced Handover Scheme with Adaptive Threshold for 5G Heterogeneous Networks

In order to tackle the explosive growth of data traffic and the number of terminals, 5G heterogeneous network (HetNet) has become an important evolution direction of 5G networking architecture. Densely deployed micro base stations (gNBs) in 5G HetNets will dramatically increase the handover frequency of user equipment (UE), resulting in more handover failures, and seriously reducing the user experience of mobile UE. Aiming at tackling this problem, this paper proposes a beam enhancement handover scheme with an adaptive threshold. Firstly, different beamforming gains are configured for the mobile UE in the overlapping area of two gNBs to improve the signal strength received by the UE at the edge of gNB coverage. Secondly, for mobile UE with different speeds, adaptive handover decision parameters are configured, and reference signal receiving strength (RSRP) as well as reference signal receiving quality (RSRQ) are used for joint handover decisions to achieve reliable handover. The simulation results verify that the proposed scheme can effectively improve the signal strength of the edge area, and the adaptive joint handover decision algorithm based on UE speed can also effectively improve the handover success probability.

Evaluation of HMIPv6 Algorithm in 5G Mmwave Single and Dual Connectivity Handover Network

In this article, we analyzed a Handover Mobile IPv6 (HMIPv6) algorithm under conditions of 5G millimeter wave (mmWave) single and dual connectivity. A single connectivity enables handover between 5G base stations. Meanwhile, a dual connectivity is a handover occurred from a 4G base station to a 5G base station. In sending data, TCP has a congestion control algorithm that allows TCP to handle any congestion problems on the network. In this article, we analyzed the HMIPv6 performance using TCP YeAH and TCP CUBIC with various user equipment (UE) speeds. It showed that each TCP had a fairly stable delay and throughput under the condition of the single connectivity handover with an average delay of 192.8196 ms and average throughput of 52.8812 Mb/s. Whereas, in the dual connectivity handover condition, each TCP had a fluctuating delay and throughput directly proportional to the increasing UE speed. Therefore, TCP YeAH dominated the stability in dual connectivity with an average delay of 221.4226 ms and average throughput of 44.4004 Mb/s. Overall, this article found that TCP YeAH performed better than TCP CUBIC in both the single connectivity and dual connectivity handovers.

Real-time high-speed mobility management

High-speed mobility system has now become a serious concern for mobile operators due to the large frameworks of a heterogeneous network made up of multiple cell types and different frequency bands. Handover (HO) is conducted in a real-life scenario when the user equipment (UE) moves from one network coverage to another by performing proper measurement with high speed. HO breakdown and call loss are observed due to a high speed; thus, high-speed mobility system needs improvement by using the UE speed as one of the key measurement monitoring criteria for the long-term evolution (LTE) network. Vendor consultation has been considered in this paper in addition to real drive test measurement in highways. Results have shown that velocity has a direct impact on the handover quality and overall timing. Results also demonstrate that 120 km/h measurement is better than 140 km/h as UE speed.

Using LTE-Sim in New Hanover Decision Algorithm for 2-Tier Macrocell-Femtocell LTE Network

Deployment of mini macrocell base stations can also be referred to as femtocells improve quality of service of indoor and outdoor users. Nevertheless, mobility management remains a key issue with regards to their deployment. This paper is leaned towards this issue, with in-depth focus on the most important aspect of mobility management - handover. In handover management, making a handover decision in the LTE two-tier macrocell femtocell network is a crucial research area. Decision algorithms in this research, are classified and comparatively analyzed according to received signal strength, user equipment speed, cost function and interference. However, it was observed that most of the discussed decision algorithms fail to consider cell selection with hybrid access policy in a single macrocell multiple femtocell scenario, another observation was a majority of these algorithms lack the incorporation of user equipment residence parameter. Not including this parameter boosts the number of unnecessary handover occurrence. To deal with these issues, a sophisticated handover decision algorithm is proposed. The proposed algorithm considers the user’s velocity, received signal strength, residence time as well as the femtocell base station’s access policy. Simulation results have shown that the proposed algorithm reduces the number of unnecessary handovers when compared to conventional received signal strength based handover decision algorithm.

High Speed Mobility Management Performance in a Real LTE Scenario

This paper discusses the mobility management for high-speed users, which is a crucial challenge for all mobile operators, especially when users are moving vertically across different network technologies. Mobility, also known as seamless connectivity, is directly influencing the quality of service (QoS). Mobility management-Handover (HO) performance was evaluated by field measurements of a Long Term Evolution (LTE) network of a mobile operator in the Middle East. Drive test measurements were used to analyze the results of different high-speed scenarios. User Equipment (UE) with high speed of 80-140km/h causes a high risk of failure of seamless connectivity as the HO procedure timing is longer than for UE with smaller speed. HO failure and call drop may occur when UE is moving with high speed across two adjacent cells in highways. During measurements, HO failure occurred when UE speed was 140km/h, and HO preparation timing increased when UE speed increased.

Individualistic Dynamic Handover Parameter Self-Optimization Algorithm for 5G Networks Based on Automatic Weight Function

Ensuring a reliable and stable communication throughout the mobility of User Equipment (UE) is one of the key challenges facing the practical implementation of the Fifth Generation (5G) networks and beyond. One of the main issues is the use of suboptimal Handover Control Parameters (HCPs) settings, which are configured manually or generated automatically by certain self-optimization functions. This issue becomes more critical with the massive deployment of small base stations and connected mobile users. This will essentially require an individual handover self-optimization technique for each user individually instead of a unified and centrally configured setting for all users in the cell. In this paper, an Individualistic Dynamic Handover Parameter Optimization algorithm based on an Automatic Weight Function (IDHPO-AWF) is proposed for 5G networks. This algorithm dynamically estimates the HCPs settings for each individual UE based on UE's experiences. The algorithm mainly depends on three bounded functions and their Automatic Weights levels. First, the bounded functions are evaluated, independently, as a function of the UE's Signal-to-Interference-plus-Noise-Ratio (SINR), cells' load and UE's speed. Next, the outputs of the three bounded functions are used as inputs in a new proposed Automatic Weight Function (AWF) to estimate the weight of each output bounded function. After that, the final output is used as an indicator for optimizing HCPs settings automatically for a specific user. The algorithm is validated throughout various mobility conditions in the 5G network. The performance of the analytical HCPs estimation method is investigated and compared with other handover algorithms from the literature. The evaluation comparisons are performed in terms of Reference Signal Received Power (RSRP), Handover Probability (HOP), Handover Ping-Pong Probability (HPPP), and Radio Link Failure (RLF). The simulation results show that the proposed algorithm provides noticeable enhancements for various mobile speed scenarios as compared to the existing Handover Parameter Self-Optimization (HPSO) algorithms.

Evaluating the effect of mobility speed on the performance of three handover algorithms in long term evolution networks

This work uses NS3 simulation to study the effect of mobility speed on the performance of three handover algorithms in Long Term Evolution (LTE) Networks. A realistic multi-cell LTE network was set up using NS3 simulation software. Mobility models were used to vary the location of the User Equipment (UE), hence triggering handover events across the network. The performance was measured using Signal Interference Noise Ratio (SINR) and number of completed handovers. Result revealed that at a speed between the ranges of 0 – 3 km/h, the Integrative algorithm performed best while at 4 – 60km/h, the performance of the A3RSRP algorithm was the best with an average value of 95dB. Also, at an increased speed within the range of 60 – 120 km/h, the Integrative algorithm had a slightly better performance than the A3RSRP. However, at a speed above 120 km/h, the integrative algorithm performed best with an SINR of 120dB. In terms of completed handovers, the Integrative algorithm had the least number of completed handovers throughout the entire range of considered speeds. Thus, we establish that mobility speed has a significant effect on the performance of handover algorithms.Keywords: LTE handover, LTE UE Speed, Integrative Algorithm, Power Budget Algorithm

Genetic Based Approach to Optimize the Vertical Handover Performance Among Heterogeneous Network

Mobile terminals typically can be connected to multiple wireless networks that offer different degrees of suitability for different classes of service. A genetic algorithm (GA) - based on a supervised approach - is used to assess the likelihood of a successful handover in heterogeneous networks to increase capacity and network performance. Traditional handoff schemes are prone to ping-pong and corner effects, and the development of an optimized handover scheme for a seamless, faster and less energy-consuming handover decision is a challenge. In order to ensure service continuity and to maintain the promising QoS, the handover decision should be made appropriately. The most general criteria for handover is the received signal strength, which is not sufficient in advanced networks. The GA scheme can effectively optimize the soft handoff decision by using the best-fit network for the mobile terminal (MT), taking into account the quality of service requirements (QoS), the network parameters, and the user preference for the cost of the various connection points for the MT is selected. The mathematical model-based approach to vertical handoff prediction involves a well-defined objective function taking into account signal strength, user equipment speed, load and cost per user bandwidth. The system performance can be improved according to the user settings by adjusting the weights in the defined objective function. Due to the high bandwidth and easy networking, the system consider the wireless access standards: UMTS, Wi-Fi, LTE and Wimax. The decision problem is formulated as several objective optimization problems and simulated using a monitored genetic algorithm. The simulation result shows that the number of handovers can be minimized when using optimized network parameter values.

Performance Evaluation for Local Anchor-Based Dual Connectivity in 5G User-Centric Network

Ultra-dense network (UDN) is considered as one of the most promising techniques in achieving the increasingly explosive growth of data rates for future 5G system. However, a large number of small cells lead to the increased cell edges and the rugged inter-cell interference, which cause frequent handover events and more radio link failure. In this paper, a local anchor-based dual connectivity (DC) architecture is proposed for a user-centric network based on the analysis of mobility management challenges of UDN. Under the proposed architecture, the local anchor acts as the master eNodeB (MeNB) with neighboring small cells acting as slave eNodeBs (SeNBs) to provide DC transmission for user-centric service following each user’s movement. Key procedures for mobility management are correspondingly provided and both the MeNBs and SeNBs are selected from the small cells to investigate the potential of them, which are different from the mobility management methods under the traditional cellular architecture. Performance evaluations are conducted under different parameter configurations to evaluate the maximum potential of the proposed scheme. Simulation results show that in our proposed scheme, the handover failure rate shows a maximum decrease of more than 53% and the average user spectrum efficiency achieves an increase of 5% gains over the current LTE system when the user equipment speed is 3 km/h.

Handover in LTE Networks with Proactive Multiple Preparation Approach and Adaptive Parameters Using Fuzzy Logic Control

High data rates in long-term evolution (LTE) networks can affect the mobility of networks and their performance. The speed and motion of user equipment (UE) can compromise seamless connectivity. However, a proper handover (HO) decision can maintain quality of service (QoS) and increase system throughput. While this may lead to an increase in complexity and operational costs, self-optimization can enhance network performance by improving resource utilization and user experience and by reducing operational and capital expenditure. In this study, we propose the self-optimization of HO parameters based on fuzzy logic control (FLC) and multiple preparation (MP), which we name FuzAMP. Fuzzy logic control can be used to control self-optimized HO parameters, such as the HO margin and time-to-trigger (TTT) based on multiple criteria, viz HO ping pong (HOPP), HO failure (HOF) and UE speeds. A MP approach is adopted to overcome the hard HO (HHO) drawbacks, such as the large delay and unreliable procedures caused by the break-before-make process. The results of this study show that the proposed method significantly reduces HOF, HOPP, and packet loss ratio (PLR) at various UE speeds compared to the HHO and the enhanced weighted performance HO parameter optimization (EWPHPO) algorithms.

System-level performance evaluation of UMTS with multi-service

In this paper, we perform a simulative evaluation of Universal Mobile Telecommunications System (UMTS) with multi-service via Network Simulator 2 for a newly built scenario. We change the scenario environment parameters, such as link delay, speed of User Equipment (UE) and interference traffic rate, to show how diverse services are affected. The results with respect to bandwidth, end-to-end delay, handoff latency, packet loss and delay jitter are presented to provide thorough investigation of UMTS under various services. Additionally, we discuss the impact of co-channel interference and compare the performance in the situation with and without interference. Based on the results from simulations, we have drawn conclusions that (i) end-to-end delay and handoff latency are proportional to link delay so that they are not severely influenced by different services for a high value of link delay, (ii) the number of packet loss is not directly related to link delays or UE's speed, (iii) UE's speed does not affect the performance obviously, (iv) co-channel interference exists in UMTS, and so on.