Coverage and Handover Analysis of Ultra-Dense Millimeter-Wave Networks With Control and User Plane Separation Architecture

Yang, Bin; Yang, Xuan; Ge, Xiaohu; Li, Qiang

doi:10.1109/access.2018.2871363

Cited by 29 publications

(16 citation statements)

References 22 publications

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“…DC enables UEs to have connectivity to two different cells at the same time [79][80][81][82][83][84][85][86]. One connection is established to a macro cell and another to a small cell [87].…”

Section: B Dual Connectivity (Dc)mentioning

confidence: 99%

Key Challenges, Drivers and Solutions for Mobility Management in 5G Networks: A Survey

et al. 2020

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Ensuring a seamless connection during the mobility of various User Equipment (UE) will be one of the major challenges facing the practical implementation of the Fifth Generation (5G) networks and beyond. Several key determinants will significantly contribute to numerous mobility challenges. One of the most important determinants is the use of millimeter waves (mm-waves) as it is characterized by high path loss. The inclusion of various types of small coverage Base Stations (BSs), such as Picocell, Femtocell and drone-based BSs is another challenge. Other issues include the use of Dual Connectivity (DC), Carrier Aggregation (CA), the massive growth of mobiles connections, network diversity, the emergence of connected drones (as BS or UE), ultra-dense network, inefficient optimization processes, central optimization operation, partial optimization, complex relation in optimization operations, and the use of inefficient handover decision algorithms. The relationship between these processes and diverse wireless technologies can cause growing concerns in relation to handover associated with mobility. The risk becomes critical with high mobility speed scenarios. Therefore, mobility issues and their determinants must be efficiently addressed. This paper aims to provide an overview of mobility management in 5G networks. The work examines key factors that will significantly contribute to the increase of mobility issues. Furthermore, the innovative, advanced, efficient, and smart handover techniques that have been introduced in 5G networks are discussed. The study also highlights the main challenges facing UEs' mobility as well as future research directions on mobility management in 5G networks and beyond.

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Section: B Dual Connectivity (Dc)mentioning

confidence: 99%

Key Challenges, Drivers and Solutions for Mobility Management in 5G Networks: A Survey

et al. 2020

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“…When addressing the HO in 5G, existing works are usually divided in targeting the reduction of HOFs [3], [31], [62], reduction of HO rate [1], [63], [64], [65], or a combination of both [66]- [70], improving throughput or QoE of the user [1], [31], [71]- [77] and reduction of HO signaling [78], [79]. Other works are devoted to assess the energy saving [62], [80] and load balancing [62], [64].…”

Section: B Literature Surveymentioning

confidence: 99%

“…The works in [78], [79] are focused on the HO signaling reduction. A mobility management scheme based on UE location tracking was proposed in [78] to provide proactive and seamless HOs.…”

Section: B Literature Surveymentioning

confidence: 99%

“…This technique eliminates the HO signaling overheads and provides seamless mobility at the cost of increased computational complexity. Performance of an ultra-dense network millimeter-wave network with control and user plane separation architecture was compared with a conventional architecture in [79]. To minimize the HO cost with a certain coverage probability requirement, an analytical framework was also proposed.…”

Section: B Literature Surveymentioning

confidence: 99%

“…A comparison table of the literature survey is shown in Table 3. Overall, location estimation errors are found in [1], [9], [23], [30], [35], [39], [43], [64], [81], the works proposed in [3], [13], [19], [29], [30], [36], [40], [43], [48], [49], [79], [80] effect other HO performance related parameters, the algorithm proposed in [34], [35], [37], [38], [47], [57], [58], [78] increased the computational complexity, the multiconnectivity in [27], [28], [31] [62], [63], [82] introduces high UE complexity and high utilization of resources, and efficient HO algorithm were not shown in [28], [50], [64].…”

Section: B Literature Surveymentioning

confidence: 99%

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A Survey on Handover Management: From LTE to NR

2019

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To satisfy the high data demands in future cellular networks, an ultra-densification approach is introduced to shrink the coverage of base station (BS) and improve the frequency reuse. The gain in capacity is expected but at the expense of increased interference, frequent handovers (HOs), increased HO failure (HOF) rates, increased HO delays, increase in ping pong rate, high energy consumption, increased overheads due to frequent HO, high packet losses and bad user experience mostly in high-speed user equipment (UE) scenarios. This paper presents the general concepts of radio access mobility in cellular networks with possible challenges and current research focus. In this article, we provide an overview of HO management in longterm evolution (LTE) and 5G new radio (NR) to highlight the main differences in basic HO scenarios. A detailed literature survey on radio access mobility in LTE, heterogeneous networks (HetNets) and NR is provided. In addition, this paper suggests HO management challenges and enhancing techniques with a discussion on the key points that need to be considered in formulating an efficient HO scheme. INDEX TERMS Radio access mobility, cell selection, handover, LTE, 5G, NR, mobility enhancers. Ph.D. degree in electrical engineering with Aalto University, Finland. He has more than two years, from 2013 to 2015, of professional experience as an RF Planning and Optimization Executive at Wi-Tribe Pakistan Ltd. (Ooredoo Group). During his stay at KFUPM, he was associated with the King Abdullah University of Science and Technology (KAUST), Saudi Arabia, as a Visiting Student and a KFUPM-KAUST Joint Research Initiative. He has been a Researcher with the Helsinki Research Center, Huawei Technologies Finland Oy, since February 2018. His current research interest includes energy-efficient mobility for small-cell overlaid cellular networks. He received the Gold Medal Award for obtaining the first position in the B.Sc. degree. XAVIER GELABERT received the M.Sc. degree in electrical engineering from the KTH Royal Institute of Technology, Stockholm, in 2003, and the joint B.Sc. and M.Sc. degrees in telecom engineering and the Ph.D. degree (Hons.

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Overview of evolutionary algorithms and neural networks for modern mobile communication

Kouhalvandi

Shayea

Özoğuz

et al. 2022

Trans Emerging Tel Tech

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The sixth generation (6G) of mobile networks must support the huge growth of mobile connections and provides various intelligent services in future mobile networks. For that, designing high-performance network architecture and communication systems (CSs) as well as finding coherent solutions for the determined problems is critical demand that needs to be achieved in 6G networks.Optimal solutions are mainly sought by using modifiable, smart, and perceptive algorithms aimed at optimizing more specific tasks. Therefore, advanced optimization methods are highly required to accommodate the requirements of CSs efficiently. That will be in various parts of the future networks such as advanced mobility management, multi communication links, efficient power consumption, ultra-lower latency, ultra-security, high speed, and reliable connectivity.Accordingly, highly accurate and smart functions must be modeled to optimize the required communication parameters in the network. This study provides a comprehensive overview of optimization methods that may need further investigations and developments to be applied in 6G networks at various parts of networks. A detailed theoretical description for each method is presented and discussed to elucidate future research directions for optimizing specific characteristics with multi-objective optimizations. Moreover, this article illustrates the conceptual and structural viewpoints of reported optimization methods. Also, the capability of various optimization methods that can offer industrial solutions in 6G is discussed. The potential applications of each method are also analyzed. Finally, this article presented the research issues and future directions of optimization technology and research gaps that need to be addressed before the standardization of 6G networks. INTRODUCTIONRecently, innovative solutions of communication systems (CSs) have been developed impressively, as data traffic is increasing exponentially by more than 50% per year. 1 Several factors will contribute for increasing data demand massively, for example, as predicted by CISCO, the video will make up 82% of the all IP traffic by 2022. 2,3 This massive increase in data traffic will cause several new issues that will facing the implementation of future mobile networks. That will include a dramatic increase for wider spectrum need, 4 the necessity for big system capacity, 5 further mobility issues, 6,7 and higher energy consumption, 8 in which cannot be handled efficiently by the current cellular networks.

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Coverage and Handover Analysis of Ultra-Dense Millimeter-Wave Networks With Control and User Plane Separation Architecture

Cited by 29 publications

References 22 publications

Key Challenges, Drivers and Solutions for Mobility Management in 5G Networks: A Survey

Key Challenges, Drivers and Solutions for Mobility Management in 5G Networks: A Survey

A Survey on Handover Management: From LTE to NR

Overview of evolutionary algorithms and neural networks for modern mobile communication

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