N. Le, L. Tran, Q. Vu and D. Jayalath, "Energy-Efficient Resource Allocation for OFDMA Heterogeneous Networks," in IEEE Transactions on Communications, vol. 67, no. 10, pp. 7043-7057, Oct. 2019. doi: 10.1109/TCOMM.2019.2936813
Energy-efficient resource allocation for OFDMA heterogeneous networks
|Author:||Le, Nam-Tran1; Tran, Le-Nam2; Vu, Quang-Doanh3;|
1Science and Engineering Faculty, Queensland University of Technology, Queensland, Australia
2School of Electrical and Electronic Engineering, University College Dublin, Dublin D04 V1W8, Ireland
3Centre for Wireless Communications, University of Oulu, P.O.Box 4500, FI-90014, Oulu, Finland
|Online Access:||PDF Full Text (PDF, 0.5 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2019121046451
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2019-12-10
We proposed several energy-efficient resource allocation algorithms for the downlink of an orthogonal frequency-division-multiple-access (OFDMA) based femtocell heterogeneous networks (HetNets). Heterogeneous QoS and fairness in rate are investigated in the proposed resource allocation problem. A dense deployment of femtocells in the coverage area of a central macrocell is considered and energy usage of both femtocell and macrocell users are optimized simultaneously. We aim to maximize the weighted sum of the individual energy efficiencies (WSEEMax) and the network energy efficiency (NEEMax) while satisfying the following: (1) minimum throughput for delay-sensitive (DS) users, (2) fairness constraint for delay-tolerant (DT) users, (3) required constraints of OFDMA systems. The problem is formulated in three different forms: mixed 0—1 integer programming formulation, time-sharing formulation and sparsity-inducing formulation. The proposed resource block (RB) and power optimization problems are combinatorial and highly non-convex due to the fractional form of the objective function, the integer constraint of OFDMA RBs and non-affine fairness. We adopt the successive convex approximation (SCA) approach and transform the problems into a sequence of convex subproblems. With the proposed algorithms, we show that the overall joint RB and power allocation schemes converge to suboptimal solutions. Numerical examples confirm the merits of the proposed algorithms.
IEEE transactions on communications
|Pages:||7043 - 7057|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
This work was funded by the Australian Government under the Endeavour Postgraduate Scholarship Program and by the Science and Engineering Faculty, Queensland University of Technology, Australia under the Faculty Write-up Scholarship. This publication has emanated from research supported in part by a Grant from Science Foundation Ireland under Grant number 17/CDA/4786. The work of Vu was supported by the projects ”Flexible Uplink-Downlink Resource Management for Energy and Spectral Efficiency Enhancing in Future Wireless Networks (FURMESFuN)” funded by the Academy of Finland under Grant 310898, and ”6Genesis Flagship” funded by the Academy of Finland under Grant 318927.
|Academy of Finland Grant Number:||
310898 (Academy of Finland Funding decision)
318927 (Academy of Finland Funding decision)
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