O. Tervo, L. Tran, H. Pennanen, S. Chatzinotas, B. Ottersten and M. Juntti, "Energy-Efficient Multicell Multigroup Multicasting With Joint Beamforming and Antenna Selection," in IEEE Transactions on Signal Processing, vol. 66, no. 18, pp. 4904-4919, 15 Sept.15, 2018. doi: 10.1109/TSP.2018.2864636
Energy-efficient multicell multigroup multicasting with joint beamforming and antenna selection
|Author:||Tervo, Oskari1,2; Tran, Le-Nam3; Pennanen, Harri1;|
1Centre for Wireless Communications, University of Oulu, Oulu 90014, Finland
2Nokia Bell Labs, Oulu 90620, Finland
3School of Electrical and Electronic Engineering, University College Dublin, Dublin 4, U.K.
4Interdisciplinary Centre for Security, Reliability and Trust, University of Luxembourg, Luxembourg City 2721, Luxembourg
|Online Access:||PDF Full Text (PDF, 0.5 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2019060618786
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2019-06-06
This paper studies the energy efficiency and sum rate tradeoff for coordinated beamforming in multicell multiuser multigroup multicast multiple-input single-output systems. We first consider a conventional network energy efficiency maximization (EEmax) problem by jointly optimizing the transmit beamformers and antennas selected to be used in transmission. We also account for per-antenna maximum power constraints to avoid nonlinear distortion in power amplifiers and user-specific minimum rate constraints to guarantee certain service levels and fairness. To be energy efficient, transmit antenna selection is employed. It eventually leads to a mixed-Boolean fractional program. We then propose two different approaches to solve this difficult problem. The first solution is based on a novel modeling technique that produces a tight continuous relaxation. The second approach is based on sparsity-inducing method, which does not require the introduction of any Boolean variable. We also investigate the tradeoff between the energy efficiency and sum rate by proposing two different formulations. In the first formulation, we propose a new metric, that is, the ratio of the sum rate and the so-called weighted power. Specifically, this metric reduces to EEmax when the weight is 1, and to sum rate maximization when the weight is 0. In the other method, we treat the tradeoff problem as a multiobjective optimization for which a scalarization approach is adopted. Numerical results illustrate significant achievable energy efficiency gains over the method where the antenna selection is not employed. The effect of antenna selection on the energy efficiency and sum rate tradeoff is also demonstrated.
IEEE transactions on signal processing
|Pages:||4904 - 4919|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
This work was supported in part by the Academy of Finland 6Genesis Flagship under Grant 318927, in part by the Infotech Oulu Doctoral Program, in part by the Academy of Finland under projects MESIC belonging to the WiFIUS program with NSF and WiConIE, in part by a Grant from Science Foundation Ireland under Grant 17/CDA/4786, and in part by projects PROSAT, SATSENT, INWIPNET, and H2020 SANSA. The work of O. Tervo was supported in part by Oulu University Scholarship Foundation, in part by Nokia Foundation, in part by Tauno Tönning Foundation, and in part by Walter Ahlström Foundation.
|Academy of Finland Grant Number:||
318927 (Academy of Finland Funding decision)
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