FOCS '02 Proceedings of the 43rd Symposium on Foundations of Computer Science
IEEE/ACM Transactions on Networking (TON) - Special issue on networking and information theory
Efficient channel-aware rate adaptation in dynamic environments
Proceedings of the 6th international conference on Mobile systems, applications, and services
Proceedings of the 14th ACM international conference on Mobile computing and networking
Cross-layer wireless bit rate adaptation
Proceedings of the ACM SIGCOMM 2009 conference on Data communication
A universal lattice code decoder for fading channels
IEEE Transactions on Information Theory
Seamless rate adaptation for wireless networking
Proceedings of the 14th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems
Proceedings of the 10th ACM Workshop on Hot Topics in Networks
AutoMAC: rateless wireless concurrent medium access
Proceedings of the 18th annual international conference on Mobile computing and networking
A comparative simulation study of rate adaptation algorithms in wireless LANs
International Journal of Sensor Networks
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Rate adaptation is a fundamental primitive in wireless networks. Since wireless channel strength varies quickly and unpredictably, senders have to constantly measure the channel and correspondingly adapt the bitrate so that the transmitted packet gets correctly decoded. Prior approaches to this problem can be divided into two classes: those that require constant and expensive feedback from the receiver about channel strength, or those that use coarse and often inaccurate inference based on packet losses to measure channel strength and decide what bitrate to use. In this paper we take the opposite approach. Instead of actively adapting the bitrate based on receiver or packet loss feedback, we present a technique where the sender does no measurement or adaptation, yet the receiver manages to receive packets at a bitrate corresponding to whatever channel conditions exist at that point. The technique works with existing coding and modulation techniques (e.g. convolutional codes in WiFi), and requires no changes to them. Our preliminary evaluation shows that our proposed feedback-free technique achieves a performance that is nearly as good as if the sender knew exactly what the channel strength was in advance.