5G Wireless Network Slicing for eMBB, URLLC, and mMTC
The grand objective of 5G wireless technology is to support three generic services with vastly heterogeneous requirements: enhanced mobile broadband ( eMBB ), massive machine-type communications ( mMTCs ), and ultra-reliable low-latency communications ( URLLCs ). Service heterogeneity can be accommodated by network slicing , through which each service is allocated resources to provide performance ...
Abstract The grand objective of 5G wireless technology is to support three generic services with vastly geneous requirements: enhanced mobile broadband ( eMBB ), massive machin cations ( mMTC ), and ultra-reliable low-latency communications ( URLLC ). Service heterogeneity can ated by network slicing , through which each service is alloca
(PDF) 5G Wireless Network Slicing for eMBB, URLLC, and mMTC
The grand objective of 5G wireless technology is to support services with vastly heterogeneous requirements. Network slicing , in which each service operates within an exclusive slice of allocated ...
The grand objective of 5G wireless technology is to support three generic services with vastly heterogeneous requirements: enhanced mobile broadband ( eMBB ), massive machine-type communications ( mMTC ), and ultra-reliable low-latency communications ( URLLC ). Service heterogeneity can be accommodated by network slicing , through which each service is allocated resources to provide performance ...
PDF 5G wireless network slicing for eMBB, URLLC, and mMTC
Slicing of the radio access network (RAN) is typically done by means of orthogonal resource allocation among the services. This paper studies the potential advantages of allowing for non-orthogonal sharing of RAN resources in uplink communications from a set of eMBB , mMTC , and URLLC devices to a common base station.
In this article, we introduce a logical architecture for network slicing based 5G systems, and present a scheme for managing mobility between different access networks , as well as a joint power ...
PDF 5G Wireless Network Slicing for eMBB, URLLC, and mMTC
Slicing of the radio access network (RAN) is typically done by means of orthogonal resource allocation among the services. This paper studies the potential advantages of allowing for non-orthogonal sharing of RAN resources in uplink communications from a set of eMBB , mMTC , and URLLC devices to a common base station.
This paper proposes a Deep Reinforcement Learning (DRL) agent that performs dynamic resource allocation in 5G wireless network slicing according to traffic requirements of the 5G use cases within two scenarios: eMBB with URLLC and eMBB with mMTC .
5G wireless network slicing for eMBB, URLLC, and mMTC
Slicing of the radio access network (RAN) is typically done by means of orthogonal resource allocation among the services. This paper studies the potential advantages of allowing for non-orthogonal sharing of RAN resources in uplink communications from a set of eMBB , mMTC , and URLLC devices to a common base station.
There are three generic services in 5G : enhanced mobile broadband ( eMBB ), ultra-reliable low-latency communications ( URLLC ), and massive machine-type communications ( mMTC ). To guarantee the performance of heterogeneous services, network slicing is proposed to allocate resources to different services. Network slicing is typically done in an orthogonal multiple access (OMA) fashion, which means ...