scholarly journals Network coding for reliable video distribution in multi-hop device-to-device communications

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Lei Wang ◽  
Yu Liu ◽  
Jia Xu ◽  
Jun Yin ◽  
Lijie Xu ◽  
...  
Keyword(s):  
Network Coding ◽  
Video Transmission ◽  
Base Stations ◽  
D2d Communication ◽  
Original Video ◽  
Fifth Generation ◽  
Video Distribution ◽  
Device To Device ◽  
Generation Network ◽  
Crucial Information

AbstractIt is becoming more and more popular to share videos among multiple users. However, sharing video in traditional cellular networks will incur high expenses. Device-to-device (D2D) communication is one of the crucial technologies in the fifth-generation network, and it enables the devices to transmit data directly without the relay of base stations. This paper proposes a network-coding-based video distribution scheme for the D2D communication environment. The proposed scheme applies the network coding technology in the H.264 video transmission, which can protect crucial information of the video. This scheme enables the receivers to decode the original video with a high probability, especially in the networks with interferences. Both the simulation results and the actual experimental results show that using network coding technology in video transmission can improve the quality of the received video. Compared with the traditional scheme, the successful decoding rate of the proposed scheme is increased by $$46\%$$ 46 % in our experimental settings.

scholarly journals Handover Management for D2D Communication in 5G Networks

2020 ◽  
Vol 10 (12) ◽  
pp. 4409
Author(s):  
Wei Kuang Lai ◽  
Chin-Shiuh Shieh ◽  
Fu-Sheng Chou ◽  
Chia-Yu Hsu ◽  
Meng-Han Shen
Keyword(s):  
Mobile Networks ◽  
Base Station ◽  
Base Stations ◽  
D2d Communication ◽  
Expected Improvement ◽  
5G Networks ◽  
Handover Management ◽  
Current Standard ◽  
Handover Procedure ◽  
Device To Device

This study addresses the handover management issue for Device-to-Device communication in fifth-generation (5G) networks. The Third Generation Partnership Project (3GPP) drafted a standard for proximity services (ProSe), also named device-to-device (D2D) communication, which is a promising technology in offering higher throughput and lower latency services to end users. Handover is an essential issue in wireless mobile networks due to the mobility of user equipment (UE). Specifically, we need to transfer an ongoing connection from an old E-UTRAN Node B (eNB) to a new one, so that the UE can retain its connectivity. In the data plane, both parties of a D2D pair can communicate directly with each other without the involvement of the base station. However, in the control plane, devices must be connected to the eNB for tasks such as power control and resource allocation. In the current standard of handover scheme, the number of unnecessary handovers would be increased by the effect of shadowing fading on two devices. More important, the handover mechanism for D2D pairs is not standardized yet. LTE-A only considers the handover procedure of a single user. Therefore, when a D2D pair moves across cell boundaries, the control channels of the two UEs may connect to different base stations and result in increased latency due to the exchange of D2D related control messages. Hence, we propose a handover management scheme for D2D communication to let both parties of a D2D pair handover to the same destination eNB at the same time. By doing so, the number of unnecessary handovers, as well as the handover latency, can be reduced. In the proposed method, we predict the destination eNB of D2D users based on their movements and the received signal characteristics. Subsequently, we make a handover decision for each D2D pair by jointly factoring in the signal quality and connection stability. Expected improvement can be attained, as revealed in the simulation. Unnecessary handover can be avoided. Consequently, both UEs of a D2D pair reside in the same cell and, therefore, result in increased throughput and decreased delay.

scholarly journals Energy Consumption Analysis of D2D Communication in 5G Systems: Latest Advances in 3GPP Standardization

2017 ◽  
Author(s):  
Marko Höyhtyä ◽  
Olli Apilo ◽  
Mika Lasanen
Keyword(s):  
Energy Consumption ◽  
Autonomous Driving ◽  
Base Stations ◽  
D2d Communication ◽  
High Data ◽  
Fifth Generation ◽  
Radio Access ◽  
The Status ◽  
3Gpp Long Term Evolution ◽  
Air Interfaces

Device-to-device (D2D) communication is an essential part of the future fifth generation (5G) system that can be seen as “network of networks”, consisting of multiple seamlessly integrated radio access technologies (RATs). Public safety communications, autonomous driving, social-aware networking, and infotainment services are example use cases of D2D technology. High data rate communications and use of several active air interfaces in the described network create energy consumption challenges for both base stations and the end user devices. In this paper, we review the status of 3GPP standardization and define a set of application scenarios. We use the recent models of 3GPP Long Term Evolution (LTE) and WiFi interfaces in analyzing the power consumption both from the infrastructure and user device perspectives. The results indicate that the number of active interfaces should be minimized.

scholarly journals Resource Allocation in Millimeter-Wave Device-to-Device Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Filbert Onkundi Ombongi ◽  
Heywood Ouma Absaloms ◽  
Philip Langat Kibet
Keyword(s):  
Resource Allocation ◽  
Millimeter Wave ◽  
Base Stations ◽  
D2d Communication ◽  
System Capacity ◽  
Fourth Generation ◽  
Live Streaming ◽  
Data Traffic ◽  
Research Issues ◽  
Device To Device

Recently, the mobile wireless communication has seen explosive growth in data traffic which might not be supported by the current Fourth Generation (4G) networks. The Fifth Generation (5G) networks will overcome this challenge by exploiting a higher spectrum available in millimeter-wave (mmwave) band to improve network throughput. The integration of the millimeter-wave communication with device-to-device communication can be an enabling 5G scheme in providing bandwidth-intensive proximity-based services such as video sharing, live streaming of data, and socially aware networking. Furthermore, the current cellular network traffic can also be offloaded by the D2D user devices thereby reducing loading at Base Stations (BSs), which would then increase the system capacity. However, the mmwave D2D communication is associated with numerous challenges, which include signal blockages, user mobility, high-computational complexity resource allocation algorithms, and increase in interuser interference for dense D2D user scenario. The paper presents review of existing channel and power allocation approaches and mathematical resource optimization solution techniques. In addition, the paper discusses the challenges hindering the realization of an effective allocation scheme in mmwave D2D communication and gives open research issues for further study.

scholarly journals Effect of increasing the network capacity using device-to-device technology for next generation networks

2020 ◽  
Vol 17 (1) ◽  
pp. 303
Author(s):  
Aws Zuheer Yonis
Keyword(s):  
Communication Systems ◽  
Network Capacity ◽  
Base Station ◽  
D2d Communication ◽  
Next Generation Networks ◽  
Wireless Communication Systems ◽  
Next Generation ◽  
Direct Communication ◽  
Fifth Generation ◽  
Device To Device

Device-to-device (D2D) communication is one of the key technologies in the fifth generation of wireless communication systems, which is defined as direct communication between two mobile users without traversing the base station D2D communication plays an increasingly important role and which improves communication capability and reduces communication delay and power consumption. D2D communication that enables direct communication between nearby mobiles is an exciting and innovative feature of next-generation cellular networks. In order to meet the rising subscriber demands and provide them satisfactory services, D2D communication is being looked upon as an emerging technology of the next generation networks.

scholarly journals Leveraging Machine-Learning for D2D Communications in 5G/Beyond 5G Networks

Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 169
Author(s):  
Sherief Hashima ◽  
Basem M. ElHalawany ◽  
Kohei Hatano ◽  
Kaishun Wu ◽  
Ehab Mahmoud Mohamed
Keyword(s):  
Machine Learning ◽  
Network Architecture ◽  
D2d Communication ◽  
Neighbor Discovery ◽  
Research Directions ◽  
Fifth Generation ◽  
Research Activities ◽  
Comprehensive Survey ◽  
Network Overhead

Device-to-device (D2D) communication is a promising paradigm for the fifth generation (5G) and beyond 5G (B5G) networks. Although D2D communication provides several benefits, including limited interference, energy efficiency, reduced delay, and network overhead, it faces a lot of technical challenges such as network architecture, and neighbor discovery, etc. The complexity of configuring D2D links and managing their interference, especially when using millimeter-wave (mmWave), inspire researchers to leverage different machine-learning (ML) techniques to address these problems towards boosting the performance of D2D networks. In this paper, a comprehensive survey about recent research activities on D2D networks will be explored with putting more emphasis on utilizing mmWave and ML methods. After exploring existing D2D research directions accompanied with their existing conventional solutions, we will show how different ML techniques can be applied to enhance the D2D networks performance over using conventional ways. Then, still open research directions in ML applications on D2D networks will be investigated including their essential needs. A case study of applying multi-armed bandit (MAB) as an efficient online ML tool to enhance the performance of neighbor discovery and selection (NDS) in mmWave D2D networks will be presented. This case study will put emphasis on the high potency of using ML solutions over using the conventional non-ML based methods for highly improving the average throughput performance of mmWave NDS.

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