Smart Soft-RAN for 5G: Dynamic Resource Management in CoMP-NOMA Based Systems
In this paper, we design a new smart software-defined radio access network architecture which is flexible and traffic and density aware for the fifth generation (5G) of cellular wireless networks and beyond. The proposed architecture, based on network parameters such as density of users and system t...
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Zusammenfassung: | In this paper, we design a new smart software-defined radio access network
architecture which is flexible and traffic and density aware for the fifth
generation (5G) of cellular wireless networks and beyond. The proposed
architecture, based on network parameters such as density of users and system
traffic, performs five important tasks namely, dynamic radio resource
management (RRM), dynamic BS type selection, dynamic functionality splitting,
dynamic transmission technology selection, and dynamic framing. In this regard,
we first elaborate the structure of the proposed smart soft-RAN model and
explain the details of the proposed architecture and RRM algorithms. Next, as a
case study, based on the proposed architecture, we design a novel coordinated
multi point beamforming technique to enhance the throughput of a virtualized
software defined-based 5G network utilizing the combination of power domain
non-orthogonal multiple access and multiple-input single-output downlink
communication. In doing so, we formulate an optimization problem with the aim
of maximizing the total throughput subject to minimum required data rate of
each user and maximum transmit power constraint of each mobile virtual network
operator and each BS, and find jointly the non-orthogonal set, beamforming, and
subcarrier allocation. To solve the proposed optimization problem, based on the
network density, we design two centralized and semi-centralized algorithms.
Specifically, for the ultra-dense scenario, we use the centralized algorithm
while the semi-centralized one is used for the high and moderate density
scenarios. Numerical results illustrate the performance and signaling overhead
of the proposed algorithms, e.g., taking computational limitations into account
the number of supported users is increased by more than 60%. |
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DOI: | 10.48550/arxiv.1804.03778 |