5G Multi-Connectivity with Non-Ideal Backhaul: Distributed vs Cloud-Based Architecture

Michalopoulos, Diomidis S.; Maeder, Andreas; Kolehmainen, Niko

doi:10.1109/glocomw.2018.8644234

Cited by 10 publications

(6 citation statements)

References 11 publications

(15 reference statements)

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“…The amount of data is computed based on pending data requests, historical data of the throughputs provided, and the buffer status of the SN. The same traffic split algorithm is also used in [24] in which MC is studied in cloud and distributed Heterogeneous Networks (HetNet) architectures.…”

Section: Related Workmentioning

confidence: 99%

Multi-Connectivity in 5G and Beyond Non-Terrestrial Networks

Mikko

Martikainen

Sormunen

et al. 2022

JCOMSS

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The Fifth Generation (5G) communications systems aim to serve such service classes as Ultra-Reliable Low Latency Communications (URLLC), enhanced Mobile Broadband (eMBB), and massive Machine-Type Communications (mMTC). To meet the growing requirements posed to mobile networks, satellites can be used to complement the Terrestrial Networks (TNs). To increase the efficiency of the satellite communications involved, bandwidth-efficient techniques should be used. Multi-Connectivity (MC) is one such technique. In MC, a User Equipment (UE), for example, a smartphone, can be connected to multiple Next Generation Node Bs (gNBs) simultaneously. In this paper, an adaptive MC activation scheme for throughput enhancement in 5G and beyond Non-Terrestrial Networks (NTNs) is presented. The algorithm is evaluated by system simulations using different traffic split algorithms, namely, even split, data request per connection and per gNB algorithms. In the considered simulation scenario, the maximum throughput enhancement of 9.1%, compared to when MC is turned off, is experienced when using the adaptive Secondary Node (SN) addition algorithm with the combination of the data request algorithms.

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Section: Related Workmentioning

confidence: 99%

Multi-Connectivity in 5G and Beyond Non-Terrestrial Networks

Mikko

Martikainen

Sormunen

et al. 2022

JCOMSS

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“…Various architectures have been proposed for implementing multi-connectivity in 5G [18]. Throughput performance of multi-connectivity in distributed and cloud-based heterogeneous network architectures has been compared in [19]. Cloudbased heterogeneous networks have been shown to provide better throughput performance.…”

Section: A Related Literaturementioning

confidence: 99%

Leveraging Multi-Connectivity for Multicast Video Streaming

Zuhra¹,

Chaporkar²,

Karandikar³

et al. 2022

Preprint

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Multi-connectivity has emerged as a key enabler for providing seamless connectivity in cellular mobile networks. However, its potential for improving the quality of multicast transmissions has remained unexplored. In this paper, we investigate the use of multi-connectivity in wireless multicast streaming. Multi-connectivity can significantly improve the performance of multicast services. It especially benefits the cell edge users who often suffer from poor channel conditions. In this work, we assess the impact of multi-connectivity on the performance of multicast streaming. We propose procedures for establishing multi-connectivity in a multicast system and address the associated resource allocation problem. We prove that the optimal resource allocation problem is NP-hard. We propose a greedy approximation algorithm for this problem and prove that no other polynomial-time algorithm can provide a better approximation. Since video streaming is the primary use case under consideration here, we use traces from actual videos to generate realistic video traffic patterns in our simulations. Our simulation results clearly establish that multi-connectivity results in considerable performance improvement in multicast streaming.

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“…Network cloudification and programmability allow telecom operators making their networks more scalable, flexible, and agile and to offer innovative and marketoriented services. By centralizing certain functionalities, cloud computing enables on-demand resource sharing and it empowers applications with elasticity and scalability at low cost [16], [17]. In [18], it is shown that the cloud-based heterogeneous access network architecture exceeds the distributed architecture in terms of throughput performance.…”

Section: Related Workmentioning

confidence: 99%

Programmability of Connectivity Control

Atanasov¹,

Pencheva²

2021

ELEKTRON ELEKTROTECH

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Network programmability and edge computing as key features of next generation communications enable innovative services. While the programmability is focused on the core network of the fifth-generation system, the edge computing moves the network intelligence to the radio access network. This paper presents a study on the programmability of connectivity control as a function of radio access network using Multi-access Edge Computing. The capability of using more than one radio access technology simultaneously enhances reliability and increases the throughput, especially in dense networks. Opening the radio access network interfaces for programmability of multi-connectivity enables analytics applications to control the device connections to multiple radio links simultaneously based on information of radio conditions, user location or specific policies. The research novelty is in opening the radio access network interfaces for edge applications to access connectivity control.

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5G Multi-Connectivity with Non-Ideal Backhaul: Distributed vs Cloud-Based Architecture

Cited by 10 publications

References 11 publications

Multi-Connectivity in 5G and Beyond Non-Terrestrial Networks

Multi-Connectivity in 5G and Beyond Non-Terrestrial Networks

Leveraging Multi-Connectivity for Multicast Video Streaming

Programmability of Connectivity Control

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