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Energy-spectral-efficiency analysis and optimization of heterogeneous cellular networks: a large-scale user-behavior perspective

Energy-spectral-efficiency analysis and optimization of heterogeneous cellular networks: a large-scale user-behavior perspective
Energy-spectral-efficiency analysis and optimization of heterogeneous cellular networks: a large-scale user-behavior perspective

Heterogeneous cellular networks (HCNs) are capable of meeting the explosive mobile-traffic demands. However, the conventional base station (BS) deployment strategy is unsuitable for supporting the often unpredictable non-uniform mobile-traffic demands, as governed by the large-scale user behavior (LUB). This results in the inefficient exploitation of the system's resources. In this paper, we develop an analytical framework for characterizing the achievable energy-spectral-efficiency (ESE) of HCNs, which explicitly quantifies the relationship between the network's ESE and the randomly time-varying LUBs as well as other network deployment parameters. Specifically, we model the quantitative impact of the geographical mobile-traffic intensity, the load migration factor, the users' required service rate and the per-tier BS densities on the achievable ESE of network, while considering the area-spectral-efficiency requirements. Importantly, a closed-form ESE expression is derived, which enables us to explicitly analyze the properties of the network's ESE. Furthermore, the optimal LUB-aware BS deployment strategy is proposed for maximizing the ESE under specific outage constraints. Using numerical simulations, we verify the accuracy of the analytical ESE expression and quantify the impact of several relevant system parameters on the achievable ESE. Furthermore, we evaluate the achievable ESE performance of the network under diverse time-varying LUB scenarios. Our work therefore provides valuable insights for designing future ultra-dense HCNs.

Aggregates, base station deployment, Cellular networks, energyspectral-efficiency, green communications and networks, Heterogeneous cellular networks, large-scale-user-behaviors, load migration factor, Mobile computing, mobile-traffic intensity, Numerical models, Optimization, Quality of service
0018-9545
4098-4112
Zhao, Guogang
66a33bee-9c30-411b-bee7-3504ec772163
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Zhao, Liqiang
6f028499-c197-4765-9666-c0105afa5b9c
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Zhao, Guogang
66a33bee-9c30-411b-bee7-3504ec772163
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Zhao, Liqiang
6f028499-c197-4765-9666-c0105afa5b9c
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1

Zhao, Guogang, Chen, Sheng, Zhao, Liqiang and Hanzo, Lajos (2018) Energy-spectral-efficiency analysis and optimization of heterogeneous cellular networks: a large-scale user-behavior perspective. IEEE Transactions on Vehicular Technology, 67 (5), 4098-4112. (doi:10.1109/TVT.2018.2789498).

Record type: Article

Abstract

Heterogeneous cellular networks (HCNs) are capable of meeting the explosive mobile-traffic demands. However, the conventional base station (BS) deployment strategy is unsuitable for supporting the often unpredictable non-uniform mobile-traffic demands, as governed by the large-scale user behavior (LUB). This results in the inefficient exploitation of the system's resources. In this paper, we develop an analytical framework for characterizing the achievable energy-spectral-efficiency (ESE) of HCNs, which explicitly quantifies the relationship between the network's ESE and the randomly time-varying LUBs as well as other network deployment parameters. Specifically, we model the quantitative impact of the geographical mobile-traffic intensity, the load migration factor, the users' required service rate and the per-tier BS densities on the achievable ESE of network, while considering the area-spectral-efficiency requirements. Importantly, a closed-form ESE expression is derived, which enables us to explicitly analyze the properties of the network's ESE. Furthermore, the optimal LUB-aware BS deployment strategy is proposed for maximizing the ESE under specific outage constraints. Using numerical simulations, we verify the accuracy of the analytical ESE expression and quantify the impact of several relevant system parameters on the achievable ESE. Furthermore, we evaluate the achievable ESE performance of the network under diverse time-varying LUB scenarios. Our work therefore provides valuable insights for designing future ultra-dense HCNs.

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Energy-Spectral-Efficiency Analysis and Optimization of Heterogeneous Cellular Networks: A Large-Scale User-Behavior Perspective - Accepted Manuscript
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Accepted/In Press date: 5 January 2018
e-pub ahead of print date: 8 January 2018
Published date: 14 May 2018
Keywords: Aggregates, base station deployment, Cellular networks, energyspectral-efficiency, green communications and networks, Heterogeneous cellular networks, large-scale-user-behaviors, load migration factor, Mobile computing, mobile-traffic intensity, Numerical models, Optimization, Quality of service

Identifiers

Local EPrints ID: 417868
URI: http://eprints.soton.ac.uk/id/eprint/417868
ISSN: 0018-9545
PURE UUID: 4ea4716c-f3f8-4fa1-a4c2-950011469a32
ORCID for Lajos Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

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Date deposited: 15 Feb 2018 17:31
Last modified: 07 Oct 2020 01:33

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