Using learning automata for adaptively adjusting the downlink-to-uplink ratio in IEEE 802.16e wireless networks

Using learning automata for adaptively adjusting the downlink-to-uplink ratio in IEEE 802.16e wireless networks

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A. Sarigiannidis, P. Nicopolitidis, G. Papadimitriou, P. Sarigiannidis, M. Louta: Using learning automata for adaptively adjusting the downlink-to-uplink ratio in IEEE 802.16e wireless networks. 2011.

Περίληψη

IEEE 802.16e allows for flexibly defining the relation of the downlink and uplink sub-frames' width from 3:1 to 1:1, respectively. However, the determination of the most suitable ratio is left open to the network designers and the research community. Existing scheduling and mapping schemes are inflexibly designed. In this paper, a novel adaptive mapping scheme is proposed aiming to dynamically adjust the downlink-to-uplink ratio, following adequately the modification of the load requests with respect to both downlink and uplink directions. A learning automaton is exploited in order to sense the performance of the downlink and uplink mapping processes and to determine the most appropriate length ratio of both sub-frames in order to maximize the network performance. The suggested ratio determination scheme is evaluated through realistic scenarios and it is compared with static schemes that maintain a fixed ratio. The results show that our proposed scheme introduces considerable improvement, increasing the network's service ratio and reducing the bandwidth waste. © 2011 IEEE.

BibTeX (Download)

@conference{Sarigiannidis2011353,
title = {Using learning automata for adaptively adjusting the downlink-to-uplink ratio in IEEE 802.16e wireless networks},
author = { A. Sarigiannidis and P. Nicopolitidis and G. Papadimitriou and P. Sarigiannidis and M. Louta},
url = {https://www.researchgate.net/publication/221504931_Using_learning_automata_for_adaptively_adjusting_the_downlink-to-uplink_ratio_in_IEEE_80216e_wireless_networks},
doi = {10.1109/ISCC.2011.5983863},
year  = {2011},
date = {2011-01-01},
journal = {Proceedings - IEEE Symposium on Computers and Communications},
pages = {353-358},
abstract = {IEEE 802.16e allows for flexibly defining the relation of the downlink and uplink sub-frames' width from 3:1 to 1:1, respectively. However, the determination of the most suitable ratio is left open to the network designers and the research community. Existing scheduling and mapping schemes are inflexibly designed. In this paper, a novel adaptive mapping scheme is proposed aiming to dynamically adjust the downlink-to-uplink ratio, following adequately the modification of the load requests with respect to both downlink and uplink directions. A learning automaton is exploited in order to sense the performance of the downlink and uplink mapping processes and to determine the most appropriate length ratio of both sub-frames in order to maximize the network performance. The suggested ratio determination scheme is evaluated through realistic scenarios and it is compared with static schemes that maintain a fixed ratio. The results show that our proposed scheme introduces considerable improvement, increasing the network's service ratio and reducing the bandwidth waste. © 2011 IEEE.},
keywords = {IEEE 802.16, Learning automata, mapping, OFDMA, WiMAX},
pubstate = {published},
tppubtype = {conference}
}
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