Iterative channel estimation for MIMO OFDM systems

Chen, Ju-Ya; Chiang, Cheng-Chih; Lo, Li-Chung

doi:10.1109/ispacs.2007.4446002

Cited by 5 publications

(2 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Also estimation in each iteration, can be used as side information and feed back to system to achieve better result in next iteration. Some of this methods are used for SISO and MIMO systems (Chen et al, 2007;Qiao et al, 2005). In this study for initial channel estimation, data aided schemes are used and pilots are transmitted along with data.…”

Section: Methodsmentioning

confidence: 99%

Iterative Channel Estimation Algorithm in Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing Systems

Nasseri¹

2010

Journal of Computer Science

View full text Add to dashboard Cite

Problem statement: The objective of this study is improving channel estimation accuracy in MIMO-OFDM system because channel state information is required for signal detection at receiver and its accuracy affects the overall performance of system and it is essential to improve the channel estimation for more reliable communications. MIMO-OFDM system was chosen in this study because it has been widely used today due to its high data rate, channel capacity and its adequate performance in frequency selective fading channels. For this purpose a 2×2 system was designed and pilot aided channel estimation with interpolation, is made iterative to enhance BER performance. Approach: First of all, pilots were inserted among subcarriers in transmitter with distances emerged of sampling theory then Least Square (LS) method was chosen for initial channel estimation in pilots at receiver, using applicable proposed receiver, which has simple and usable structure, then channel state information was estimated by linear interpolator in information subcarriers, which uses two adjacent channel estimation in pilots to compute channel in another subcarriers and an LMS iterative algorithm, including a feedback of output is added to system. This algorithm uses the channel estimation of last iteration in current estimation. Results: Adding a LMS iterative algorithm to system, improves the channel estimation performance. Simulation results proved the acceptable BER performance of iterative channel estimation algorithm, which is closed to the ideal channel. Conclusion: The low-complexity proposed receiver including LMS algorithm, has a higher efficiency than conventional methods and it can work in lower amount of SNRs

show abstract

Section: Methodsmentioning

confidence: 99%

Iterative Channel Estimation Algorithm in Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing Systems

Nasseri¹

2010

Journal of Computer Science

View full text Add to dashboard Cite

show abstract

“…This estimation in each iteration can be used as side information and feed back to system to achieve better result for next iteration. [14][15] International Journal of Computer Applications (0975 -8887) Volume 68-No.17, April 2013…”

Section: Lms Iterative Channel Estimationmentioning

confidence: 99%

Performance comparison of Different Pilot Aided Channel Estimation Techniques for OFDM IEEE 802. 11e (Mobile Wimax) Systems

Singh¹,

Saini²

2013

IJCA

View full text Add to dashboard Cite

Orthogonal frequency-division multiplexing (OFDM) modulation is a promising technique for achieving the high bit rates required for a wireless multimedia service. In this paper we present different channel estimation algorithms for OFDM mobile communication systems based on the use of pilot subcarriers. Specifically we present LS (Least Square), MMSE (Minimum Mean Square Error) and LMS iterative channel estimation techniques to show the performance comparison of channel estimation techniques supported by n IFFT-based time channel estimation. The channel estimation is based on the principle of pilotsymbol aided channel estimation (PACE), and it has been implemented using block-type pilot subcarrier arrangements. The low complexity of LMS algorithm, has a higher efficiency than conventional methods (without channel estimation, LS& LMMSE) and it can work in lower amount of SNRs. We have compared the performances of all schemes by measuring bit error rate with 16QAM as modulation scheme, and multi-path Rayleigh fading channel as channel model. Simulation results validate that the LMS Iterative channel estimation scheme can achieve tremendous performance as the existing channel estimation methods.

show abstract

A Non-Iterative Channel Estimation Algorthm for Mobile MIMO-OFDM Systems with Comb-Type Pilots

Lavafi

Abolhassani

2007

2007 IEEE International Conference on Signal Processing and Communications

View full text Add to dashboard Cite

In this paper, a non-iterative least square (LS) channel estimation algorithm is proposed for mobile multiple input, multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. Recent discrete Fourier transform (DFT) based algorithms reduce additive white Gaussian noise (AWGN) and inter-channel interference (ICI) iteratively through low-pass filtering. The proposed algorithm compensates the phase shift which is formed by allocation of antenna pilot subcarriers except those of the first antenna, then by eliminating the iteration and keeping satisfactory performance, reduces complexity considerably. The simulation results show that the proposed algorithm slightly outperforms the iterative algorithm in addition to complexity reduction by eliminating iterations.

show abstract

Iterative channel estimation for MIMO OFDM systems

Cited by 5 publications

References 8 publications

Iterative Channel Estimation Algorithm in Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing Systems

Iterative Channel Estimation Algorithm in Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing Systems

Performance comparison of Different Pilot Aided Channel Estimation Techniques for OFDM IEEE 802. 11e (Mobile Wimax) Systems

A Non-Iterative Channel Estimation Algorthm for Mobile MIMO-OFDM Systems with Comb-Type Pilots

Contact Info

Product

Resources

About