Convexity of Fairness-Aware Resource Allocation in Wireless Powered Communication Networks

Guo, Chongtao; Liao, Bin; Huang, Lei; Li, Qiang; Lin, Xiaohui

doi:10.1109/lcomm.2016.2519344

Cited by 61 publications

(42 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In [7], the well-known "harvest-then-transmit" protocol was proposed, where the time allocated to the hybrid access point (H-AP) for downlink WET and the time and transmit power allocated to the sensors for uplink WIT were jointly optimized for system throughput maximization. Since then, related works have been extensively done in the context of WPSNs with relays [8], [9], full-duplex radio [10], [11], cognitive radio [12]- [15], MIMO [16]- [18] and nonorthogonal multiple access (NOMA) schemes [19]- [21]. However, the above works only focus on the spectrum efficiency of WPSNs, which may lead a great dissipation of energy during the downlink WET.…”

Section: Introductionmentioning

confidence: 99%

Energy Efficiency Optimization For Wireless Powered Sensor Networks With Nonorthogonal Multiple Access

Song

Zheng

2018

IEEE Sens. Lett.

View full text Add to dashboard Cite

Abstract-This article studies a wireless powered sensor network (WPSN), where sensors harvest energy from a hybrid access point (H-AP) and then transmit information to the H-AP via nonorthogonal multiple access (NOMA) scheme. The energy efficiency (EE) maximization problem for the NOMA-based WPSN is, for the first time, formulated as a nonlinear fractional programming, which is difficult to solve for global optimality due to the lack of convexity. To this end, we propose two important properties for the optimal solution to the EE maximization problem, based on which a particle-swarmoptimization-based solution algorithm is proposed. Simulations demonstrate the fast convergence and stability of the proposed algorithm.Index Terms-Sensor networks, wireless powered sensor networks, non-orthogonal multiple access, energy efficiency, particle swarm optimization.

show abstract

Section: Introductionmentioning

confidence: 99%

Energy Efficiency Optimization For Wireless Powered Sensor Networks With Nonorthogonal Multiple Access

Song

Zheng

2018

IEEE Sens. Lett.

View full text Add to dashboard Cite

show abstract

“…1. We assume perfect synchronization among devices, which is in line with recent works [6], [9][10][11], [25].…”

Section: System Modelmentioning

confidence: 85%

“…To the best of our knowledge, the recent works [6], [10], [11], [13] are the most relevant to our proposed scheme. Although the system models in these works are based on wireless power 1 To cross-check we compared AMPL-Couenne with CVX-sedumi/SDPT3 in geometric programming (GP) mode.…”

Section: Sub-optimal Multi-user Scheduling Schemementioning

confidence: 99%

See 1 more Smart Citation

Sequencing and Scheduling for Multi-User Machine-Type Communication

Alvi

Zhou

Durrani

et al. 2020

IEEE Trans. Commun.

View full text Add to dashboard Cite

In this paper, we propose joint sequencing and scheduling optimization for uplink machine-type communication (MTC). We consider multiple energy-constrained MTC devices that transmit data to a base station following the time division multiple access (TDMA) protocol. Conventionally, the energy efficiency performance in TDMA is optimized through multi-user scheduling, i.e., changing the transmission block length allocated to different devices. In such a system, the sequence of devices for transmission, i.e., who transmits first and who transmits second, etc., has not been considered as it does not have any impact on the energy efficiency. In this work, we consider that data compression is performed before transmission and show that the multi-user sequencing is indeed important. We apply three popular energy-minimization system objectives, which differ in terms of the overall system performance and fairness among the devices. We jointly optimize both multi-user sequencing and scheduling along with the compression and transmission rate control. Our results show that multi-user sequence optimization significantly improves the energy efficiency performance of the system. Notably, it makes the TDMA-based multi-user transmissions more likely to be feasible in the lower latency regime, and the performance gain is larger when the delay bound is stringent.

show abstract

“…is emerging. Because of its intrinsic capability of self-sustainability, a lot of researches have been done on it; many of them focus on the high-efficient energy utilization [1][2][3]. As for this energy harvesting-wireless sensor networks (EH-WSN), the main challenge is to maximize its working performance under energy harvesting constraints, so studies on the MAC protocol, routing protocol, and cross layer optimization also obtain lots of achievements [4][5][6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Power allocation and relay selection for energy efficient cooperation in wireless sensor networks with energy harvesting

Yin

Liu

2017

J Wireless Com Network

View full text Add to dashboard Cite

In this paper, we investigate a joint power allocation and relay selection scheme for energy efficient cooperation in energy harvesting-wireless sensor networks (EH-WSN). We mainly propose a simple heuristic algorithm to improve the energy efficiency of each node in a clustering based EH-WSN. First, the effect of cooperative communication is evaluated, and then, the energy sustainability of every node is taken into account, finally, we formulate an online optimization problem which can be solved near optimally with low computational complexity. Extensive simulation results are presented to show the outstanding performance of our proposed scheme in nodes' transmitting power allocation and average working utility. Therefore, this joint optimization algorithm has a promising future in real applications.

show abstract

Convexity of Fairness-Aware Resource Allocation in Wireless Powered Communication Networks

Cited by 61 publications

References 16 publications

Energy Efficiency Optimization For Wireless Powered Sensor Networks With Nonorthogonal Multiple Access

Energy Efficiency Optimization For Wireless Powered Sensor Networks With Nonorthogonal Multiple Access

Sequencing and Scheduling for Multi-User Machine-Type Communication

Power allocation and relay selection for energy efficient cooperation in wireless sensor networks with energy harvesting

Contact Info

Product

Resources

About