Agarwal, Bharat ORCID: 0000-0002-4040-8145, Ruffini, Marco ORCID: 0000-0001-6220-0065 and Muntean, Gabriel-Miro ORCID: 0000-0002-9332-4770 (2021) Reduced complexity optimal resource allocation for enhanced video quality in a heterogeneous network environment. IEEE Transactions on Wireless Communications, 21 (5). pp. 2892-2908. ISSN 1536-1276
Abstract
The latest Heterogeneous Network (HetNet) environments, supported by 5th generation (5G) network solutions,
include small cells deployed to increase the traditional macrocell network performance. In HetNet environments, before data
transmission starts, there is a user association (UA) process with a
specific base station (BS). Additionally, during data transmission,
diverse resource allocation (RA) schemes are employed. UA-RA
solutions play a critical role in improving network load balancing,
spectral performance, and energy efficiency. Although several
studies have examined the joint UA-RA problem, there is no
optimal strategy to address it with low complexity while also
reducing the time overhead. We propose two different versions of
simulated annealing (SA): Reduced Search Space SA (RS3A) and
Performance-Improved Reduced Search Space SA (P IRS3A),
algorithms for solving UA-RA problem in HetNets. First, the
UA-RA problem is formulated as a multiple knapsack problem
(MKP) with constraints on the maximum BS capacity and
transport block size (TBS) index. Second, the proposed RS3A
and P IRS3A are used to solve the formulated MKP. Simulation
results show that the proposed scheme P IRS3A outperforms
RS3A and other existing schemes such as Default Simulated
Annealing (DSA), and Default Genetic Algorithm (DGA) in terms
of variability and DSA and RS3A in terms of Quality of Service
(QoS) metrics, including throughput, packet loss ratio (PLR),
delay and jitter. Simulation results show that P IRS3A generates
solutions that are very close to the optimal solution.
Metadata
Item Type: | Article (Published) |
---|---|
Refereed: | Yes |
Uncontrolled Keywords: | User Association; Resource Allocation; 5G; HetNet; Simulated Annealing; Multiple Knapsack problem; Combinatorial Optimization |
Subjects: | Engineering > Electronic engineering |
DCU Faculties and Centres: | DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering Research Institutes and Centres > INSIGHT Centre for Data Analytics |
Publisher: | IEEE |
Official URL: | https://doi.org/10.1109/TWC.2021.3116881 |
Copyright Information: | © 2021 The Authors. Open Access (CC-BY 4.0) |
Funders: | Science Foundation Ireland Centre for Research Training in Digitally-Enhanced Reality (D-REAL) under Grant No. 18/CRT/6224., Science Foundation Ireland (SFI) support via the research grants 16/SP/3804 (Enable) and 12/RC/2289 P2 (Insight) |
ID Code: | 28020 |
Deposited On: | 17 Jan 2023 15:33 by Bharat Agarwal . Last Modified 17 Jan 2023 15:33 |
Documents
Full text available as:
Preview |
PDF
- Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
5MB |
Downloads
Downloads
Downloads per month over past year
Archive Staff Only: edit this record