Abstract
Auto rate adaptation mechanisms have been proposed to improve the throughput in wireless local area networks with IEEE 802.11a/b/g standards that can support multiple data rate at the physical layer. However, even with the capability of transmitting multi-packets with multi-rate IEEE 802.11 PHY, a mobile host (MH) near the fringe of the Access-Point’s (AP’s) transmission range still needs to adopt a low-level modulation to cope with the lower signal-to-noise ratio (SNR), Thus, it can not obtain a data rate as high as that of a host near AP in most cases. According to the characteristics of modulation schemes, the highest data rate between a pair of mobile hosts will be inversely proportional with the transmission distance. Considering these factors, we here demonstrate a Relay-Based Adaptive Auto Rate (RAAR) protocol that can find a suitable relay node for data transmission between transmitter and receiver, and can dynamically adjust its modulation scheme to achieve the maximal throughput of a node according to the transmission distance and the channel condition. The basic concept is that the best modulation schemes are adaptively used by a wireless station to transmit an uplink data frame, according to the path loss condition between the station itself and a relay node, and that between the relay node and AP, thus delivering data at a higher overall data rate. Evaluation results show that this scheme provides significant throughput improvement for nodes located at the fringe of the AP’s transmission range, thus remarkably improving overall system performance.
This work was supported by the National Science Council, Republic of China, under grant NSC92-2213-E-126-004.
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© 2005 International Federation for Information Processing
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Liu, J., Lin, CH.R. (2005). RAAR: A Relay-Based Adaptive Auto Rate Protocol for Multi-Rate and Multi-Range Infrastructure Wireless LANs. In: Belding-Royer, E.M., Al Agha, K., Pujolle, G. (eds) Mobile and Wireless Communication Networks. MWCN 2004. IFIP International Federation for Information Processing, vol 162. Springer, Boston, MA. https://doi.org/10.1007/0-387-23150-1_24
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DOI: https://doi.org/10.1007/0-387-23150-1_24
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