Energy Efficient Uplink Transmissions in LoRa Networks

Su, B. and Qin, Z. and Ni, Q. (2020) Energy Efficient Uplink Transmissions in LoRa Networks. IEEE Transactions on Communications, 68 (8). pp. 4960-4972. ISSN 0090-6778

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Abstract

LoRa has been recognized as one of the most promising low-power wide-area (LPWA) techniques. Since LoRa devices are usually powered by batteries, energy efficiency (EE) is an essential consideration. In this paper, we investigate the energy efficient resource allocation in LoRa networks to maximize the system EE (SEE) and the minimal EE (MEE) of LoRa users, respectively. Specifically, our objective is to maximize the corresponding EE by jointly exploiting user scheduling, spreading factor (SF) assignment, and transmit power allocations. To solve them efficiently, we first propose a suboptimal algorithm, including the low-complexity user scheduling scheme based on matching theory and the heuristic SF assignment approach for LoRa users scheduled on the same channel. Then, to deal with the power allocation, an optimal algorithm is proposed to maximize the SEE. To maximize the MEE of LoRa users assigned to the same channel, an iterative power allocation algorithm based on the generalized fractional programming and sequential convex programming is proposed. Numerical results show that the proposed user scheduling algorithm achieves near-optimal EE performance, and the proposed power allocation algorithms outperform the benchmarks. © 2020 IEEE.

Item Type:
Journal Article
Journal or Publication Title:
IEEE Transactions on Communications
Additional Information:
©2020 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2200/2208
Subjects:
?? energy efficiencyloralow-power wide-areamatching theorybenchmarkingconvex optimizationiterative methodsschedulingenergy-efficient resource allocationessential considerationsgeneralized fractional programmingpower allocation algorithmssequential convex pro ??
ID Code:
147575
Deposited By:
Deposited On:
25 Sep 2020 11:50
Refereed?:
Yes
Published?:
Published
Last Modified:
12 Oct 2024 00:18