Hsu, Chia-An, Lin, Kate Ching-Ju, Ren, Yi ORCID: https://orcid.org/0000-0001-7423-6719 and Tseng, Yu-Chee (2020) On optimizing signaling efficiency of retransmissions for voice LTE. In: 2020 IEEE Wireless Communications and Networking Conference (WCNC), 2020-05-25 - 2020-05-28, Seoul, Korea (South).
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Abstract
The emergence of voice over LTE enables voice traffic transmissions over 4G packet-switched networks. Since voice traffic is characterized by its small payload and frequent transmissions, the corresponding control channel overhead would be high. Semi-persistent scheduling (SPS) is hence proposed in LTE-A to reduce such overhead. However, as wireless channels typically fluctuate, tremendous retransmissions due to poor channel conditions, which are still scheduled dynamically, would lead to a large overhead. To reduce the control message overhead caused by SPS retransmissions, we propose a new SPS retransmission protocol. Different from traditional SPS, which removes the downlink control indicators (DCI) directly, we compress some key fields of all retransmissions' DCIs in the same subframe as a fixed-length hint. Thus, the base station does not need to send this information to different users individually but just announces the hint as a broadcast message. In this way, we reduce the signaling overhead and at the same time, preserve the flexibility of dynamic scheduling. Our simulation results show that, by enabling DCI compression, our design improves signaling efficiency by 2.16\times, and the spectral utilization can be increased by up to 60%.
Item Type: | Conference or Workshop Item (Paper) |
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Faculty \ School: | Faculty of Science > School of Computing Sciences |
UEA Research Groups: | Faculty of Science > Research Groups > Smart Emerging Technologies Faculty of Science > Research Groups > Data Science and AI |
Related URLs: | |
Depositing User: | LivePure Connector |
Date Deposited: | 22 Aug 2020 00:09 |
Last Modified: | 10 Dec 2024 01:16 |
URI: | https://ueaeprints.uea.ac.uk/id/eprint/76555 |
DOI: | 10.1109/WCNC45663.2020.9120735 |
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