Abstract

Channel bonding is a technique first defined in the IEEE 802.11n standard to increase the throughput in wireless networks by means of using wider channels. In IEEE 802.11n (nowadays also known as Wi-Fi 4), it is possible to use 40 MHz channels instead of the classical 20 MHz channels. Although using channel bonding can increase the throughput, the classic 802.11 setting only allows for two orthogonal channels in the 2.4 GHz frequency band, which is not enough for proper channel assignment in dense settings. For that reason, it is commonly accepted that channel bonding is not suitable for this frequency band. However, to the best of our knowledge, there is not any accurate study that deals with this issue thoroughly. In this work, we study in depth the effect of channel bonding in Wi-Fi 4 dense, decentralized networks operating in the 2.4 GHz frequency band. We confirm the negative effect of using channel bonding in the 2.4 GHz frequency band with 11 channels which are 20 MHz wide (as in North America), but we also show that when there are 13 or more channels at hand (as in many other parts of the world, including Europe and Japan), the use of channel bonding yields consistent throughput improvements. For that reason, we claim that the common assumption of not considering channel bonding in the 2.4 GHz band should be revised.

Highlights

  • Introduction and State of theArt e huge increase of wireless devices competing for the limited wireless bandwidth [1] has attracted the attention of researchers, since it is an increasingly complex problem

  • We confirm the negative effect of using channel bonding in the 2.4 GHz frequency band with 11 channels which are 20 MHz wide, but we show that when there are 13 or more channels at hand, the use of channel bonding yields consistent throughput improvements

  • We study the effect of channel bonding in dense, decentralized Wi-Fi 4 scenarios, such as a residential building. e paper contributions can be summarized as follows: (i) We describe a graph-based scenario model for WiFi 4 dense decentralized networks, using realistic indoor signal propagation and interference models, as well as the precise location and interference between all wireless devices (both access points (APs) and stations (STAs)), in order to compute the throughput

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Summary

Wi-Fi 4 Network Model

We will have two types of edges, one type representing the association between STAs and APs and the other type representing the interfering signals between wireless devices of different networks. As we focus on indoor Wi-Fi environments (dense Wi-Fi networks are usually indoor networks), we have used the propagation model defined by the ITU-R in the Recommendation P.1238-10 [28], as it assumes that STAs and APs are in the same building, which will be our testing scenario. Is procedure operates asynchronously among the APs changing the order in which the different APs scan the environment Note that this channel selection procedure represents the usual situation when a user sets up his/her AP leaving the channel selection to a decision of the AP, typically using the option called “Auto” instead of forcing the use of a specific channel.

Performance Evaluation
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