SCIENCE CHINA Information Sciences, Volume 60, Issue 2: 022309(2017) https://doi.org/10.1007/s11432-016-5601-1

Energy-efficiency-aware relay selection in distributed full duplex relay network with massive MIMO

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  • ReceivedDec 11, 2015
  • AcceptedMar 2, 2016
  • PublishedSep 13, 2016


This paper considers a distributed full duplex relay network where multiple sources simultaneously transmit their signals to multiple destinations via the cooperation of a set of relay stations (RSs). Each RS is assumed to be equipped with large antenna arrays while all sources and destinations only have a single antenna. We assume the channels are Rician fading and the RSs use linear processing to process the signals with imperfect channel state information (CSI). We derive the closed-form expressions of the end-to-end achievable rates for the maximum-ratio combining/matched-filter (MRC/\text{MF}) and the zero-forcing (\text{ZF}) processing. These results are then used to pursue a detailed analysis of the power saving of the relay network. Then we study the energy-efficiency-aware relay selection strategy since the energy efficiency affects network lifetime in future wireless network. We propose a sub-optimal strategy with low complexity that only requires the statistical CSI. Simulations show that the energy efficiency of the system can be improved with optimal power allocation and our proposed strategy performs very close to the exhaustive search algorithm which is optimal.



This work was supported in part by National High-tech R&D Program of China (863) (Grant No. 2014AA01A706), Fundamental Research Funds for the Central Universities (Grant No. 2014JBZ001), National Natural Science Foundation of China (Grant No. 61471027), Beijing Nova Programme (Grant No. xx2016023), Research Fund of National Mobile Communications Research Laboratory, Southeast University (Grant No. 2014D05), and Beijing Natural Science Foundation Project (Grant No. 4152043). We would like to thank the anonymous referees for their help in improving this paper.


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