Earticle

초록

영어

Massive MIMO can boost the capacity and increase the coverage, however the pilot overhead of its channel estimation will linearly increase with the antenna increasing. In order to reduce pilot overhead and improve the quality of channel estimation, a multi-dimension Wiener filtering channel estimation algorithm was put forward. First we analyzed Massive MIMO system model and channel model in which Base station configured a two-dimension antenna array; then accomplished channel estimation applying the correlation function of time, frequency, the row and column of the antenna array, and presented a simple closed-form solution of the space-time-frequency correlation function to reduce the complexity of the algorithm. The proposed algorithm extends one-dimension space filtering to two-dimension, so doesn’t need to transmit pilots in every raw of the two-dimension antenna array contrast with 3D-Wiener and can reduce beyond 50% pilot overhead. Based on the simulation results, this algorithm can achieve 8dB performance gain over 2D-Winner and 3dB over 3D-Wiener with same pilot overhead and can acquires the optimal throughput with considering both the channel estimation quality and pilot overhead.

목차

Abstract
 1. Introduction
 2. System Model and Massive MIMO Channel Model
 3. Multi-stage Wiener Filtering Channel Estimation Algorithm
 4. IV Performance Analysis and Simulation Results
 5. Conclusions
 Acknowledgements
 References

키워드

저자

• Jiang Jinga [ Xi'an University of Posts and Telecommunications, Xi’an and 710061, China ]
• Wang Ni [ Xi'an University of Posts and Telecommunications, Xi’an and 710061, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Grid and Distributed Computing

• 간기

  격월간

• pISSN

  2005-4262

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605