CLC number: TN929.53
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2016-09-18
Cited: 1
Clicked: 6040
Bo Li, Sung-kwon Park. Maximizing power saving with state transition overhead for multiple mobile subscriber stations in WiMAX[J]. Frontiers of Information Technology & Electronic Engineering, 2016, 17(10): 1085-1094.
@article{title="Maximizing power saving with state transition overhead for multiple mobile subscriber stations in WiMAX",
author="Bo Li, Sung-kwon Park",
journal="Frontiers of Information Technology & Electronic Engineering",
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pages="1085-1094",
year="2016",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1500314"
}
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%J Frontiers of Information Technology & Electronic Engineering
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%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1500314
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T1 - Maximizing power saving with state transition overhead for multiple mobile subscriber stations in WiMAX
A1 - Bo Li
A1 - Sung-kwon Park
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SP - 1085
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.1500314
Abstract: In the IEEE 802.16e/m standard, three power saving classes (PSCs) are defined to save the energy of a mobile subscriber station (MSS). However, how to set the parameters of PSCs to maximize the power saving and guarantee the quality of service is not specified in the standard. Thus, many algorithms were proposed to set the PSCs in IEEE 802.16 networks. However, most of the proposed algorithms consider only the power saving for a single MSS. In the algorithms designed for multiple MSSs, the sleep state, which is set for activation of state transition overhead power, is not considered. The PSC setting for real-time connections in multiple MSSs with consideration of the state transition overhead is studied. The problem is non-deterministic polynomial time hard (NP-hard), and a suboptimal algorithm for the problem is proposed. Simulation results demonstrate that the energy saving of the proposed algorithm is higher than that of state-of-the-art algorithms and approaches the optimum limit.
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