Acta Metallurgica Sinica(English letters) ›› 2015, Vol. 22 ›› Issue (6): 86-93.doi: 10.1016/S1005-8885(15)60699-9

• Wireless • Previous Articles     Next Articles

An optimization on semi-blind channel estimation for MIMO-OFDM systems

Sangirov Gulomjon, Fu Yongqing, Sangirov Jamshid   

  1. 1. College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China 2. Electrical Engineering Department, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
  • Received:2015-05-18 Revised:2015-10-15 Online:2015-12-31 Published:2015-12-30
  • Contact: Gulomjon Sangirov E-mail:gulomjons@hrbeu.edu.cn
  • Supported by:
    This work was supported by the National Natural Science Foundation of China (61401031), the Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry.

Abstract: An orthogonal frequency division multiplexing (OFDM) is one of the effective techniques used in wireless communication. In OFDM systems, channel impairments due to multipath dispersive spreading can cause deep fades in wireless channels. Thus, the OFDM receiver requires channel state information when coherent detection is involved. Therefore, to overcome the impact of channel fades good channel estimation (CE) methods are needed in OFDM systems. And one of these CE methods is a semi-blind CE. However, the semi-blind method requires a large number of processing operations. In order to avoid the high computing complexity of the existing method, scaled least square (SLS) technique is applied to improve the performance of the semi-blind channel estimator which require less knowledge of the channel second-order statistics and have better performance than the least square (LS) which used in semi-blind CE. Simulation results shows, this proposed method of semi-blind CE has the capacity of elevating CE performance in multiple-input multiple-output (MIMO) OFDM systems.

Key words: semi-blind channel estimation, OFDM, least square, scaled least square, MIMO