Joint estimation and compensation of transmitter and receiver radio impairments in MIMO-OFDM receivers

Author(s):  
Chen-Jiu Hsu ◽  
Wern-Ho Sheen
Keyword(s):  
2013 ◽  
Vol 2013 ◽  
pp. 1-20 ◽  
Author(s):  
Jian Luo ◽  
Wilhelm Keusgen ◽  
Andreas Kortke

MIMO OFDM is a very promising technique for future wireless communication systems. By applying direct conversion architecture, low-cost, low-power, small size, and flexible implementation of MIMO OFDM systems can be realized. However, the performance of direct conversion architecture-based MIMO OFDM systems can be seriously affected by RF impairments incling carrier frequency offset (CFO) and I/Q-imbalance. While OFDM is sensitive to CFO, direct conversion architecture is sensitive to I/Q imbalance. Such RF impairments aggravate as the carrier frequency becomes higher for example, beyond 60 GHz. To achieve the desired high performance of MIMO OFDM, such RF impairments have to be compensated for. In this paper, the joint compensation of CFO, transmitter and receiver frequency-selective I/Q imbalance, and the MIMO radio channel is investigated. Two preamble-based schemes are proposed for impairment parameter estimation. The proposed preambles are constructed both in time and frequency domains and require much less overhead than the state-of-the-art designs. Furthermore, much lower computational complexity is allowed, enabling efficient implementation. The advantages and effectiveness of both proposed schemes are compared and verified by numerical simulations and complexity analysis.


2011 ◽  
Vol 23 (5) ◽  
pp. 17-21
Author(s):  
T. Shankar ◽  
A. Karthikeyan ◽  
Christopher Clement J

Author(s):  
Nan-Hung Cheng ◽  
Kai-Chieh Huang ◽  
Yung-Fang Chen ◽  
Shu-Ming Tseng

AbstractIn this paper, we present a joint time-variant carrier frequency offset (CFO) and frequency-selective channel response estimation scheme for multiple input-multiple output-orthogonal frequency-division multiplexing (MIMO-OFDM) systems for mobile users. The signal model of the MIMO-OFDM system is introduced, and the joint estimator is derived according to the maximum likelihood criterion. The proposed algorithm can be separated into three major parts. In the first part of the proposed algorithm, an initial CFO is estimated using derotation, and the result is used to apply a frequency-domain equalizer. In the second part, an iterative method is employed to locate the fine frequency peak for better CFO estimation. An adaptive process is used in the third part of the proposed algorithm to obtain the updated CFO estimation and track parameter time variations, including the time-varying CFOs and time-varying channels. The computational complexity of the proposed algorithm is considerably lower than that of the maximum likelihood-based grid search method. In a simulation, the mean squared error performance of the proposed algorithm was close to the Cramer-Rao lower bound. The simulation results indicate that the proposed novel joint estimation algorithm provides a bit error rate performance close to that in the perfect channel estimation condition. The results also suggest that the proposed method has reliable tracking performance in Jakes’ channel models.


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