Results 51 to 60 of about 533 (135)
5G Network Slicing as a Service Enabler for the Automotive Sector
This paper explores how network slicing can benefit the automotive sector throughout the vehicle lifecycle, from manufacturing to vehicular communications. We analyze the cost equilibrium for network slicing to be effective for car manufacturers, and tests in real 5G networks that demonstrate the performance improvement in OTA updates coexisting with ...
David Candal‐Ventureira +7 more
wiley +1 more source
Breaking Orthogonality in Uplink With Randomly Deployed Sources
The requirement of the upcoming sixth-generation (6G) wireless communication systems to significantly elevate the services of enhanced mobile broadband (eMBB) and massive machine-type communications (mMTC) necessitates the design and investigation of ...
Apostolos A. Tegos +5 more
doaj +1 more source
This article proposes an optimal next cell selection technique for users in the software‐defined heterogeneous network to tackle the challenges of handover and mobility management. The technique uses linear programming (LP) to facilitate optimal cell selection and reduce the number of user handovers based on multiple parameters, including user ...
Adil Khan +5 more
wiley +1 more source
This paper presents SAMA, a simulator for 5G Radio Access Networks (RAN), designed to evaluate the performance of different network configurations. The diagram illustrates the simulator's workflow: from inputs such as base station (BS) and user equipment (UE) arrangements, SAMA simulates resource allocation and scheduling, considering interference.
Christian Fragoas F. Rodrigues +2 more
wiley +1 more source
Exploring the Potential of AI in Network Slicing for 5G Networks: An Optimisation Framework
Our approach is to incorporate precise programming of segment routing over IPv6 (SRv6) identifiers, allowing dynamic assignment of SIDs based on predicted slice types, accurately distinguishing up to 40,000 eMBB slices and separating uRLLC and mMTC slices with high proficiency.
Zeina Boufakhreddine +4 more
wiley +1 more source
Machine learning approach of multi‐RAT selection for travelling users in 5G NSA networks
The authors present RAT selection algorithm for efficient resource allocation for public bus travelling user(s), utilising live data from multiple 5G NSA base stations. Models of the supervised machine learning algorithms: SVM, DNN and XGBoost were deployed for implementation to predict or select the appropriate RAT between 4G and 5G RATs.
Nurudeen O. Salau +2 more
wiley +1 more source
The services of enhanced mobile broadband (eMBB) and the ultra-reliable low-latency communication (URLLC) enabled by 5G new radio (NR) are considered as the essential prerequisites of the future intelligent transportation systems.
Xiaoshi Song, Mengying Yuan
doaj +1 more source
IoT‐5G and B5G/6G resource allocation and network slicing orchestration using learning algorithms
In this article, the challenges related to the evolution of 5G and B5G/6G networks are examined more closely. The authors then primarily focus on machine learning solutions for resource allocation in 5G and B5G/6G networks. The requirements for dynamic network slicing orchestration are also analysed.
Ado Adamou Abba Ari +5 more
wiley +1 more source
The enhanced Mobile Broadband (eMBB) and ultra-Reliable Low Latency Communications (uRLLC) are the two main scenarios of $5^{th}$ generation (5G) mobile communication system networks.
Jingxuan Zhang +5 more
doaj +1 more source
As the number of services and applications with diverse requirements keeps increasing, it is therefore of paramount importance to develop more efficient resource allocation techniques.
Ege Engin +3 more
doaj +1 more source

