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Interference alignment with delayed channel state information and dynamic AR-model channel prediction in wireless networks

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Abstract

Interference alignment (IA) is a promising technique that can effectively eliminate the interferences in multiuser wireless networks. However, it requires highly accurate channel state information (CSI) of the whole network at all the transmitters and receivers. In practical wireless systems, it is difficult to obtain the perfect knowledge of a dynamic channel. Particularly, the CSI at transmitters used in IA is usually delayed through feedback, which will dramatically affect the performance of IA. In this paper, the performance of IA with delayed CSI is studied. The expressions of the average signal to interference plus noise ratio and sum rate of IA networks with delayed CSI are established. To alleviate the influence of delayed CSI, an IA scheme based on dynamic autoregressive (AR)-model channel prediction is proposed, in which the parameters of AR mode are updated frequently. The CSI of the next time instant is predicted using the present and past CSI in the proposed scheme to improve the performance of IA networks. Two key factors of the scheme, window length and refresh rate are analyzed in detail. Simulation results are presented to show that the proposed IA scheme based on channel prediction can significantly improve its performance with delayed CSI.

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Acknowledgments

This research was supported in part by the National Natural Science Foundation of China (NSFC) under Grant 61201224 and 61372089, China Postdoctoral Science Foundation Special Funded Project under 2013T60282, and the Fundamental Research Funds for the Central Universities under DUT14QY44.

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Authors and Affiliations

  1. School of Information and Communication Engineering, Dalian University of Technology, Dalian, China

    Nan Zhao, Hongxi Yin & Guan Wang

  2. Department of Systems and Computer Engineering, Carleton University, Ottawa, ON, Canada

    F. Richard Yu

  3. School of Engineering and Computer Science, Durham University, Durham, DH1 3LE, UK

    Hongjian Sun

  4. Institute of Telecommunications, King’s College London, London, WC2R 2LS, UK

    A. Nallanathan

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  1. Nan Zhao
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Correspondence to F. Richard Yu.

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Zhao, N., Yu, F.R., Sun, H. et al. Interference alignment with delayed channel state information and dynamic AR-model channel prediction in wireless networks. Wireless Netw 21, 1227–1242 (2015). https://doi.org/10.1007/s11276-014-0850-7

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  • DOI: https://doi.org/10.1007/s11276-014-0850-7

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