Antenna Selection Strategy for Energy Efficiency Maximization in Uplink OFDMA Networks: A Multi-Objective Approach

Khalili, Ata; Mili, Mohammad Robat; Rasti, Mehdi; Parsaeefard, Saeedeh; Ng, Derrick Wing Kwan

doi:10.1109/twc.2019.2946832

Cited by 39 publications

(39 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Even though the MOOP (14) contains two competing objective functions, we can still find a solution for it that satisfies the predefined conditions of Pareto optimality. In contrast to the Dinkelbach method, which is only applicable to an optimization problem with fractional function, MOOP can be adopted for any optimization problem even if the number of objective function exceeds two [17], [18]. Moreover, MOOP provides a SE-EE trade-off with lower computational complexity compared to the Dinkelbach method.…”

Section: Proof Please See Appendix Amentioning

confidence: 99%

See 1 more Smart Citation

Multi-Objective Energy Efficient Resource Allocation and User Association for In-Band Full Duplex Small-Cells

Zarandi

Khalili

Rasti

et al. 2020

IEEE Trans. on Green Commun. Netw.

Self Cite

View full text Add to dashboard Cite

In this paper, we develop a framework to maximize the network energy efficiency (EE) by optimizing joint userbase station (BS) association, subchannel assignment, and power control considering an in-band full-duplex (IBFD)-enabled smallcell network. We maximize EE (ratio of network aggregate throughput and power consumption) while guaranteeing a minimum data rate requirement in both the uplink and downlink. The considered problem belongs to the category of mixed-integer non-linear programming problem (MINLP), and thus is NPhard. To cope up with this complexity and to derive a tradeoff between system throughput and energy utilization, we first restate the considered problem as a multi-objective optimization problem (MOOP) aiming at maximizing system's throughput and minimizing system's energy consumption, simultaneously. This MOOP is then tackled by using-constraint method. To do so, we first transform the binary subchannel and BS assignment variables into continuous ones without altering the feasible region of the problem and then approximate the nonconvex rate functions through majorization-minimization (MM) approach. Simulation results are presented to demonstrate the effectiveness of our proposed algorithm in improving network's EE compared to the existing literature. Furthermore, simulation results unveil that by employing the IBFD capability in OFDMA networks, our proposed resource allocation algorithm achieves a 69% improvement in the EE as compared to the half-duplex system for practical values of residual self-interference.

show abstract

Section: Proof Please See Appendix Amentioning

confidence: 99%

“…where t 0 is the initial point, 0 ≤ 1 is the stopping criterion, and µ is used for updating the accuracy of the method [17], [25]. Path loss exponent 3…”

Section: B Computational Complexity Analysismentioning

confidence: 99%

Multi-Objective Energy Efficient Resource Allocation and User Association for In-Band Full Duplex Small-Cells

Zarandi

Khalili

Rasti

et al. 2020

IEEE Trans. on Green Commun. Netw.

Self Cite

View full text Add to dashboard Cite

show abstract

“…Content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2020.3032661, IEEE Access restate this constraint as the intersection of the two following regions [38], [43]:…”

Section: Proposed Solutionmentioning

confidence: 99%

“…But, R 2 is still non-convex and is a reverse convex function which makes the optimization problem nonconvex form. To tackle it, we adopt Abstract Lagrangian model and we restate the objective function [38], [43], [44]. Next, we handle the non-convex constraint C 7 via introducing scalar slack variable ξ n j,k,i .…”

Section: Proposed Solutionmentioning

confidence: 99%

See 1 more Smart Citation

Resource Allocation for MC MISO-NOMA SWIPT-Enabled HetNets With Non-Linear Energy Harvesting

2020

Self Cite

View full text Add to dashboard Cite

This paper proposes a resource allocation for multi carrier (MC) multiple input single output (MISO) non-orthogonal multiple access (NOMA) enabling simultaneous wireless information and power transfer (SWIPT) where a separated architecture (SA)-based heterogeneous network (HetNet) is considered. More precisely, we focus on designing MC MISO-NOMA scheme in HetNets, where each base stations (BSs) serves multiple information decoding (ID) and energy harvesting (EH) users with a non-linear energy harvesting model which are equipped with multi antennas. For this configuration, we propose a joint subcarrier assignment, beamforming design, and energy beamforming to maximize the total rate of the network. Moreover, we take into account the condition of cross-layer interference constraints to coordinate interference, satisfying a minimum data rate requirement, fulfilling a minimum harvested energy, and respecting the maximum allowed power transfer constraints. We also consider successive interference cancellation (SIC) decoding order to detect the signal of each user due to coupling between SIC order, beamforming design, and subcarrier allocation. As a result of interference in the rate function, our optimization problem is non-convex and thus challenging to solve. Subsequently, first we adopt semidefinite relaxation (SDR) for beamforming design and then an efficient algorithm via the majorization minimization (MM) approach based on the difference of convex (DC) programming is proposed to obtain a locally optimal solution for the original problem. Simulation results reveal the superiority of our proposed scheme as compared to other existing works addressed in the literature. INDEX TERMS Multi carrier (MC), multiple input single output (MISO), non-orthogonal multiple access (NOMA), simultaneous wireless information and power transfer (SWIPT), subcarrier assignment, beamforming design, and successive interference cancellation (SIC).

show abstract

Power management in green FFR-based heterogeneous cellular networks

Nasr-Esfahani

Ghahfarokhi

2021

Physical Communication

View full text Add to dashboard Cite

Antenna Selection Strategy for Energy Efficiency Maximization in Uplink OFDMA Networks: A Multi-Objective Approach

Cited by 39 publications

References 41 publications

Multi-Objective Energy Efficient Resource Allocation and User Association for In-Band Full Duplex Small-Cells

Multi-Objective Energy Efficient Resource Allocation and User Association for In-Band Full Duplex Small-Cells

Resource Allocation for MC MISO-NOMA SWIPT-Enabled HetNets With Non-Linear Energy Harvesting

Power management in green FFR-based heterogeneous cellular networks

Contact Info

Product

Resources

About