Mobile-traffic-aware offloading for energy- and spectrum-efficient large-scale D2D-enabled cellular networks
Mobile-traffic-aware offloading for energy- and spectrum-efficient large-scale D2D-enabled cellular networks
This paper investigates how to enhance the energy and spectral efficiency (ESE) performance of large-scale cellular networks by offloading mobile traffic with the aid of device-to-device (D2D) communication. By appropriately exploiting the D2D-based mobile-traffic offloading mechanism, the users’ behaviors and the specific network operating conditions, we develop an ESE evaluation framework for large-scale D2D-enabled cellular networks. This framework enables us to characterize the explicit relationship between the network’s ESE and the offloading parameters as well as to quantify the influence of the users’ behavior. Explicitly, we quantify the effects of the mobile-traffic intensity, the users’ quality of service requirements as well as the base station density and other cellular system parameters on the achievable ESE. Tractable closed-form ESE-expressions are derived for a pair of spectrum sharing schemes, namely, D2D overlay and underlay in-band modes. Furthermore, we apply the analytical results to derive an optimal D2D-enabled mobile-traffic offloading scheme for the D2D overlay cellular networks to maximize the network’s ESE under a specific maximal cellular user outage and D2D transmitter power constraint. The numerical and simulation results are provided to verify our modeling accuracy and to demonstrate the impact of the system parameters on the achievable ESE.
3251-3264
Zhao, Guogang
66a33bee-9c30-411b-bee7-3504ec772163
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Qi, Lin
c5ce17a3-e842-4b0f-820f-44c91e86fcbd
Zhao, Liqiang
6f028499-c197-4765-9666-c0105afa5b9c
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
10 June 2019
Zhao, Guogang
66a33bee-9c30-411b-bee7-3504ec772163
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Qi, Lin
c5ce17a3-e842-4b0f-820f-44c91e86fcbd
Zhao, Liqiang
6f028499-c197-4765-9666-c0105afa5b9c
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Zhao, Guogang, Chen, Sheng, Qi, Lin, Zhao, Liqiang and Hanzo, Lajos
(2019)
Mobile-traffic-aware offloading for energy- and spectrum-efficient large-scale D2D-enabled cellular networks.
IEEE Transactions on Wireless Communications, 18 (6), .
(doi:10.1109/TWC.2019.2912596).
Abstract
This paper investigates how to enhance the energy and spectral efficiency (ESE) performance of large-scale cellular networks by offloading mobile traffic with the aid of device-to-device (D2D) communication. By appropriately exploiting the D2D-based mobile-traffic offloading mechanism, the users’ behaviors and the specific network operating conditions, we develop an ESE evaluation framework for large-scale D2D-enabled cellular networks. This framework enables us to characterize the explicit relationship between the network’s ESE and the offloading parameters as well as to quantify the influence of the users’ behavior. Explicitly, we quantify the effects of the mobile-traffic intensity, the users’ quality of service requirements as well as the base station density and other cellular system parameters on the achievable ESE. Tractable closed-form ESE-expressions are derived for a pair of spectrum sharing schemes, namely, D2D overlay and underlay in-band modes. Furthermore, we apply the analytical results to derive an optimal D2D-enabled mobile-traffic offloading scheme for the D2D overlay cellular networks to maximize the network’s ESE under a specific maximal cellular user outage and D2D transmitter power constraint. The numerical and simulation results are provided to verify our modeling accuracy and to demonstrate the impact of the system parameters on the achievable ESE.
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Accepted/In Press date: 11 April 2019
e-pub ahead of print date: 29 April 2019
Published date: 10 June 2019
Identifiers
Local EPrints ID: 431810
URI: http://eprints.soton.ac.uk/id/eprint/431810
ISSN: 1536-1276
PURE UUID: a0d0ac63-cbed-4abc-8723-61b30a73c2c9
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Date deposited: 18 Jun 2019 16:30
Last modified: 18 Mar 2024 02:36
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Author:
Guogang Zhao
Author:
Sheng Chen
Author:
Lin Qi
Author:
Liqiang Zhao
Author:
Lajos Hanzo
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