Basireddy, Ashish (2012-07). Timing Synchronization at the Relay Node in Physical Layer Network Coding. Master's Thesis. Thesis uri icon


  • In recent times, there has been an increased focus on the problem of information exchange between two nodes using a relay node. The introduction of physical layer network coding has improved the throughput efficiency of such an exchange. In practice, the reliability of information exchange using this scheme is reduced due to synchronization issues at the relay node. In this thesis, we deal with timing synchronization of the signals received at the relay node. The timing offsets of the signals received at the relay node are computed based on the propagation delays in the transmitted signals. However, due to the random attenuation of signals in a fading channel, the near far problem is inherent in this situation. Hence, we aim to design near far resistant delay estimators for this system. We put forth four algorithms in this regard. In all the algorithms, propagation delay of each signal is estimated using a known preamble sent by the respective node at the beginning of the data packet. In the first algorithm, we carefully construct the preamble of each data packet and apply the MUSIC algorithm to overcome the near far problem. The eigenstructure of the correlation matrix is exploited to estimate propagation delay. Secondly, the idea of interference cancellation is implemented to remove the near far problem and delay is estimated using a correlator. Thirdly, a modified decorrelating technique is presented to negate the near far problem. Using this technique we aim to obtain an estimate of the weak user's delay that is more robust to errors in the strong user's delay estimate. In the last algorithm, pilot signals with desired autocorrelation and cross correlation functions are designed and a sliding correlator is used to estimate delay. Even though this approach is not near far resistant, performance results demonstrate that for the length's of preamble considered, this algorithm performs similar to the other algorithms.

publication date

  • July 2012