Energy-Efficient User Scheduling and Power Control for Multi-Cell OFDMA Networks Based on Channel Distribution Information

Zhang, Yihao; An, Jianping; Yang, Kai; Gao, Xiaozheng; Wu, Jinsong

doi:10.1109/tsp.2018.2871998

Cited by 26 publications

(24 citation statements)

References 36 publications

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“…A pseudoconvex approach based parallel solution is developed for EE maximization in MIMO interference channels in [20]. EE user scheduling and power control is considered for multicell OFDMA networks for a unicast scenario in [21]. Moreover, precoding is not considered in [21].…”

Section: Related Workmentioning

confidence: 99%

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Joint User Grouping, Scheduling, and Precoding for Multicast Energy Efficiency in Multigroup Multicast Systems

Bandi

Shankar

Chatzinotas

et al. 2020

IEEE Trans. Wireless Commun.

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This paper studies the joint design of user grouping, scheduling (or admission control) and precoding to optimize energy efficiency (EE) for multigroup multicast scenarios in single-cell multiuser MISO downlink channels. Noticing that the existing definition of EE fails to account for group sizes, a new metric called multicast energy efficiency (MEE) is proposed. In this context, the joint design is considered for the maximization of MEE, EE, and scheduled users. Firstly, with the help of binary variables (associated with grouping and scheduling) the joint design problem is formulated as a mixed-Boolean fractional programming problem such that it facilitates the joint update of grouping, scheduling and precoding variables. Further, several novel optimization formulations are proposed to reveal the hidden difference of convex/ concave structure in the objective and associated constraints. Thereafter, we propose a convexconcave procedure framework based iterative algorithm for each optimization criteria where grouping, scheduling, and precoding variables are updated jointly in each iteration. Finally, we compare the performance of the three design criteria concerning three performance metrics namely MEE, EE, and scheduled users through Monte-Carlo simulations. These simulations establish the need for MEE and the improvement from the system optimization.

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Section: Related Workmentioning

confidence: 99%

“…EE user scheduling and power control is considered for multicell OFDMA networks for a unicast scenario in [21]. Moreover, precoding is not considered in [21]. The methodologies used in all these works are either SCA based CCT [15], [17], [19] or SCA based Dinkelbach's method [18], [20], [22].…”

Section: Related Workmentioning

confidence: 99%

Joint User Grouping, Scheduling, and Precoding for Multicast Energy Efficiency in Multigroup Multicast Systems

Bandi

Shankar

Chatzinotas

et al. 2020

IEEE Trans. Wireless Commun.

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“…The energy efficiency (EE) consideration for the 5G and beyond networks has turned out to be important concern since the information and communication technology accounts for nearly 5% of the entire world energy consumption [25]. Looking at the immense popularity gained by NOMA as an enabling technology for 5G and beyond, it is of interest to study the EE of the system while proposing any new methods in NOMA as analyzed in [26], [27]. In this work, the EE of the proposed TS techniques is investigated using the optimized time slot duration and the power allocation coefficients.…”

Section: Introductionmentioning

confidence: 99%

User Fairness in NOMA-HetNet Using Optimized Power Allocation and Time Slotting

Swami

Bhatia

Vuppala

et al. 2021

IEEE Systems Journal

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“…It reduces the computational complexity of the network and increased the EE of the network. Zhang et al investigate the energy‐efficient user scheduling and power control problem in downlink multicell multiuser OFDMA networks, where the channel distribution information is available. A centralized joint user scheduling and power control is proposed, which satisfies the generalized Karush‐Kuhn‐Tucker conditions by resorting to the successive convex approximation.…”

Section: Introductionmentioning

confidence: 99%

Energy‐efficient resource allocation for device‐to‐device communication through noncooperative game theory

Mohammed

Sreenivasan

Ravishankar

et al. 2020

Int J Communication

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Summary Wireless network with high data rate applications has seen a rapid growth in recent years. This improved quality of service (QoS) leads to huge energy consumption in wireless network. Therefore, in order to have an energy‐efficient resource allocation in cellular system, a device‐to‐device (D2D) communication is the key component to improve the QoS. In this paper, we propose a noncooperative game (NCG) theory approach for resource allocation to improve energy efficiency (EE) of D2D pair. A three‐tier network with macrocell base station (MBS), femtocell base station (FBS), and D2D pair is considered, which shares the uplink resource block. A resource allocation strategy with constraints is arrived, which maintains minimum throughput for each user in the network. The proposed resource allocation strategy optimizes the EE of D2D pair in the three‐tier network, which achieves Nash equilibrium (NE) and Pareto optimality (PO). Simulation results validate that EE is uniform and optimum for all D2D pair, which converges to NE when channel is static and it converges to PO when the channel is dynamic.

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Energy-Efficient User Scheduling and Power Control for Multi-Cell OFDMA Networks Based on Channel Distribution Information

Cited by 26 publications

References 36 publications

Joint User Grouping, Scheduling, and Precoding for Multicast Energy Efficiency in Multigroup Multicast Systems

Joint User Grouping, Scheduling, and Precoding for Multicast Energy Efficiency in Multigroup Multicast Systems

User Fairness in NOMA-HetNet Using Optimized Power Allocation and Time Slotting

Energy‐efficient resource allocation for device‐to‐device communication through noncooperative game theory

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