10th EAI International Conference on Communications and Networking in China

Research Article

Channel Estimation For Wireless Cellular Systems with Massive Linear Receiving Antennas

  • @INPROCEEDINGS{10.4108/eai.15-8-2015.2260570,
        author={Dian Fan and Zhangdui Zhong and Gongpu Wang and Feifei Gao},
        title={Channel Estimation For Wireless Cellular Systems with Massive Linear Receiving Antennas},
        proceedings={10th EAI International Conference on Communications and Networking in China},
        publisher={IEEE},
        proceedings_a={CHINACOM},
        year={2015},
        month={9},
        keywords={massive mimo pilot contamination cellular network doa channel estimation},
        doi={10.4108/eai.15-8-2015.2260570}
    }
    
  • Dian Fan
    Zhangdui Zhong
    Gongpu Wang
    Feifei Gao
    Year: 2015
    Channel Estimation For Wireless Cellular Systems with Massive Linear Receiving Antennas
    CHINACOM
    IEEE
    DOI: 10.4108/eai.15-8-2015.2260570
Dian Fan,*, Zhangdui Zhong1, Gongpu Wang1, Feifei Gao2
  • 1: Beijing Jiaotong University, Beijing, China.
  • 2: Tsinghua National Laboratory for Information Science and Technology, Beijing, China.
*Contact email: fandian14@163.com

Abstract

Massive Multiple Input Multiple Output (Massive MIMO) system can be a promising technology for future fifth generation (5G) wireless communication systems due to its large gains in spectral-efficiency and energy-efficiency. One well-known challenge for cellular systems with massive MIMO is the estimation problem of large-scale channel parameters. This paper investigates the channel estimation problem for cellular systems with massive linear receiving antennas. Firstly, a system model is built up based on a time-shifted pilots and time-division duplexing (TDD) cellular network with both intracell and inter-cell interference taken into account. Secondly, an estimation algorithm is proposed to obtain all channel parameters through multiple signal classification (MUSIC) method and reconstructing. Moreover, Cramer Rao Lower Bound (CRLB) is found to evaluate the estimation performance. It is found that the suggested estimation algorithm works well and can obtain all channel parameters without requiring a large number of pilots, which can effectively reduce the pilot contamination. Finally, simulation results are provided to corroborate our proposed studies.