CogTRA: a deployable mechanism for cognitive transmission rate adaptation in IEEE 802.11 networks

Abstract

Abstract Wireless local area networks have become vastly popular, and IEEE 802.11 is the chosen standard for almost all wireless devices. This standard specifies several modulation and channel coding techniques that must be implemented by all wireless interfaces to adapt to changes in wireless channels. As a result, these interfaces support multiple transmission data rates. However, this standard does not define how to dynamically select the appropriate data rate; instead, manufacturers can design and implement their own algorithms. Although several solutions have been proposed in the literature, only a few are used in practice. Moreover, their performance is still limited to specific conditions, such as highly dynamic environments. To tackle these challenges, this paper introduces CogTRA, which is a deployable mechanism built upon an existing cognitive framework called CogProt. Due to its self-adjustment functionality, CogTRA can work not only in stable but also in dynamic environments. It was implemented in the OpenWrt Linux distribution for embedded devices and evaluated through experiments using real network equipment. The results underline performance benefits with respect to existing data rate adaptation algorithms, with CogTRA exhibiting better performance especially in such dynamic networks.