Wireless communications often suffers from error bursts — a long sequence of bits is corrupted when being transmitted over the air. A relatively new technique that tries to mitigate this unreliability is cooperative relaying. Its basic idea is simple: When a device transmits data packets to a destination, adjacent devices can overhear these packets. If the direct transmission to the destination fails, one of those devices can retransmit (“relay”) its packet copy to the destination.
Information theorists have proved that such relaying can outperform standard communication techniques. In practice, however, relaying requires some coordination among the involved devices. In particular, a protocol for relay selection is used which in turn causes extra signaling packets. Such overhead can reduce the throughput benefits gained by relaying, and a relay update policy must define how and when relay selection is performed anew.
Nikolaj Marchenko and Christian Bettstetter investigate the performance of cooperative relaying with relay selection. Their forthcoming article to be published in the IEEE Transactions on Vehicular Technology proposes a framework for modelling and analysis of cooperative relaying protocols with the help of semi-Markov processes. Using this tool, they find under which conditions which protocol leads to improved throughput and energy efficiency.
“Reactive selection is commonly considered to be the best,” Marchenko explains. “Though, if you take signaling and energy for receiving into account, it turns out that reactive selection can be very inefficient. Under certain conditions it is outperformed even by a single permanent relay.” The PhD candidate and his professor propose a novel technique that adjusts to the current situation in an adaptive manner.
After having laid the theoretical foundation, the team is now working on an experimental evaluation of cooperative relaying in industrial sensor networks.
Nikolaj Marchenko and Christian Bettstetter. Cooperative ARQ with Relay Selection: An Analytical Framework Using Semi-Markov Processes. IEEE Transactions on Vehicular Technology, vol. 63, no. 1, pp. 178-190, January 2014.