A Novel training based QR-RLS channel estimator for MIMO OFDM systems (original) (raw)
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2008 5th IFIP International Conference on Wireless and Optical Communications Networks (WOCN '08), 2008
channel compensation has been considered as a major problem from the advent of wireless communications, but recent progresses in this realm has made the old problem more challenging. Especially by introducing Space-Time codes and using Array Antennas exploiting an equalization method which can track the changing channel condition with higher accuracy and lower computations is a challenging demand. This paper analyses a suggested new method for channel estimation in a MIMO-OFDM Receiver. In the proposed method, optimum training sequences are derived base on calculated MSE for LS channel estimation, utilizing these training sequences adaptive methods based on LMS and RLS are applied to estimate the channel for a system which emits independent data streams from transmitter antennas. Proposed method is capable of computing all sub-channel coefficients between a receiver antenna and all transmitters. Finally, performances of RLS and LMS algorithms are simulated and compared with LS algorithm.
Recursive Least Square Technique For Channel Estimation For Transmit Diversity Case In MIMO-OFDM
The traffic in wireless networks has been showing an exponential growth over the last decade. In order to meet the demand, and support a continuation of this growth, the scarce radio resources need to be efficiently used. The use of MIMO combined with OFDM systems has significantly improved the reliable system performance. Combination of multiple-input multiple-output (MIMO) system with orthogonal frequency division multiplexing (OFDM) technique can be exploited to attain high data rate and better spectral efficiency. Channel estimation plays a major role in communication system. In mobile communication systems bits of information is transmitted by making changes in amplitude or phase of radio waves. Channel estimation is the estimation of transmitted signal bits. The paper proposes an implementation of Recursive Least Square (RLS) technique for the Channel estimation in Transmit Diversity.
Channel Estimation for MIMO-OFDM Systems
2012
Multiple-input multiple (MIMO) communication system combined with the orthogonal frequency division multiplexing (OFDM) modulation technique can achieve reliable high data rate transmission over broadband wireless channels. In this paper performance analysis of channel estimation through different algorithms for estimating channel using different modulation scheme are investigated. The estimation of channel at pilot frequencies is based on Least Square, Minimum mean square, Least Mean Square and Recursive Least Square channel estimation algorithm. We have compared the performances of channel estimation algorithm by measuring bit error rate vs. SNR with BPSK, QPSK 16-PSK and 256-PSK modulation schemes. Recursive Least Square estimation has been shown to perform much better than LS, MMSE and LMS but is more complex than other channel estimation algorithm.
Enhanced Adaptive Channel Estimation Technique for MIMO-OFDM Wireless Systems
International Journal of Computer Applications, 2014
Multiple Input Multiple Output (MIMO) in combination with Orthogonal Frequency Division Multiplexing (OFDM) can provide spectrally efficient and ISI free communication. Channel estimation is of great importance in order to recover the signal at the receiver side. Therefore accurate channel state information is essential for proper detection and decoding in MIMO-OFDM wireless systems. To estimate channel state information various types of techniques are being deployed in these systems. Accuracy and precision of channel estimation depends on the techniques used for the purpose of estimating channel state information. The more the accuracy of the technique, more will be the accurate performance of the system. In this paper an enhanced adaptive channel estimation using RLMS technique has been purposed. It is the combination of LMS and RLS algorithm. This technique provides better performance which can be judged by the BER performance. Comparison of the technique is done with the simple LMS and LLMS which is the combination of two LMS algorithms. Simulation results show that the purposed algorithm outperforms the latter algorithms. BPSK and QPSK modulations are used for analysis purposes.
Implementation of the least squares channel estimation algorithm for MIMO-OFDM systems
2009
The least squares (LS) channel estimation algorithm for a multiple-input multiple-output (MIMO) system with orthogonal frequency division multiplexing (OFDM) is considered in this paper. Two architectures for the algorithm are presented and the architectures are implemented using fixed point arithmetic. The minimum word lengths for the implementations are determined through computer simulations for 2 × 2 and 4 × 4 MIMO systems with quadrature phaseshift keying (QPSK) modulation. Field-programmable gate array (FPGA) synthesis simulation is done for the architectures using the obtained word lengths which provides complexity and latency results. The algorithm implementations are shown to consume reasonably small amount of hardware resources.
ITERATIVE QR DECOMPOSTION CHANNEL ESTIMATION FOR MIMO-OFDM SYSTEMS
Channel estimation algorithms have a key role in signal detection in MIMO-OFDM systems. In this system, the number of channel components which need to be estimated is much more than conventional SISO wireless systems. Consequently, the computational process of channel estimation is highly intensive. In addition, the high performance channel estimation algorithms mostly suffer from high computational complexity. In the other words, the system undergoes intensive computations if high performance efficiency is desired. However, there is an alternative solution to achieve both high performance efficiency and relatively low level of computational complexity. In this solution, high efficient channel estimation is firstly designed, and then it is simplified using alternative mathematical expressions. In this paper, Iterative channel estimation based on QR decomposition for MIMO-OFDM systems is proposed. From simulation results, the iterative QRD channel estimation algorithm can provide better mean-square-error and bit error rate performance than conventional methods.
AN EXTENSIVE REVIEW OF SIGNIFICANT RESEARCHES ON CHANNEL ESTIMATION IN MIMO-OFDM 1
In communication systems, Multiple-Input Multiple-Output (MIMO) plays a major role because of its high performance. In MIMO systems, multiple antennas are used in both transmitter and receiver to improve the communication performance, whereas the orthogonal frequency division multiplexing (OFDM) is a multicarrier modulation method. MIMO-OFDM is commonly used for communication systems due to its high transmission rates and robustness against multipath fading. In MIMO-OFDM, channel estimation plays a major role and channel estimation is the estimation of the transmitted signal bits using the corresponding received signal bits. While designing the channel estimator for wireless OFDM systems, two main problems will occur. The first problem is the arrangement of pilot information, in which pilot is the reference signal employed by both transmitters and receivers, whereas the second problem is the design of an estimator with both less intricacy and excellent channel tracking ability. In this paper an extensive review on different channel estimation methods used in MIMO-OFDM like pilot based, least square (LS) & minimum mean square error method (MMSE), least mean square (LMS) & recursive least squares (RLS) methods and also other channel estimation methods used in MIMO-OFDM was discussed with their achieved results.
Adaptive Channel Estimation Techniques for MIMO OFDM Systems
International Journal of Advanced Computer Science and Applications, 2010
In this paper, normalized least mean (NLMS) square and recursive least squares (RLS) adaptive channel estimator are described for multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. These CE methods uses adaptive estimator which are able to update parameters of the estimator continuously, so that the knowledge of channel and noise statistics are not necessary. This NLMS/RLS CE algorithm requires knowledge of the received signal only. Simulation results demonstrated that the RLS CE method has better performances compared NLMS CE method for MIMO OFDM systems. In addition, the utilizing of more multiple antennas at the transmitter and/or receiver provides a much higher performance compared with fewer antennas. Furthermore, the RLS CE algorithm provides faster convergence rate compared to NLMS CE method. Therefore, in order to combat the more channel dynamics, the RLS CE algorithm is better to use for MIMO OFDM systems.
Analysis of adaptive channel estimation techniques in MIMO- OFDM system
2013
Multiple input multiple output (MIMO) can be used to improve information carrying capacity in orthogonal frequency division multiplexing (OFDM).In MIMO‐OFDM system channel estimation task becomes more difficult due to the change in channel parameter. Hence, to find appropriate channel estimation method which is able to follow changes at moment is matter of high significance. In this paper types of adaptive algorithm for channel estimation in MIMO‐OFDM system is discussed. The adap‐ tive filter can be least mean square (LMS), recursive least square (RLS) or KALMAN which does not require prior knowledge of second order statistic (SOS) of channel and noise. The adaptive RLS channel estimation with adaptive forgetting factor outper‐ forms in frequency selective fading. The LMS adaptive estimation can be used to improve the channel performance.But the low convergence speed and serious estimation error led to the combination of LMS with KALMAN filter for more accurate estima‐ tion. Howeve...
A Comparative Analysis of LS and MMSE Channel Estimation Techniques for MIMO-OFDM System
The objective of this study is up channel estimation accuracy in OFDM system as a result of channel state info is needed for detection at receiver and its accuracy affects the performance of system and it's essential to improve the channel estimation for a lot of reliable communications. OFDM system was chosen during this study because it's been wide used nowadays owing to its high knowledge rate, data rate and its adequate performance in frequency selective attenuation channels. The pilots were inserted among subcarriers in transmitter with distances emerged of sampling theory then Least sq. (LS) technique & minimum mean-square error (MMSE) was chosen for initial channel estimation in pilots at receiver, mistreatment applicable projected receiver, that has straight forward and usable structure, then channel state info was calculable by linear interpolator in information subcarriers, that uses 2 adjacent channel estimation in pilots to calculate channel in another subcarriers and associate degree LMS repetitive algorithmic rule, as well as a feedback of output is another to system. This algorithmic rule uses the channel estimation of last iteration in current estimation. Adding a LMS repetitive algorithmic rule to system, improves the channel estimation performance. Simulation results established the acceptable BER performance of repetitive channel estimation algorithm, that is closed to the best channel. The low complexity projected receiver as well as LMS algorithmic rule, has a higher potency than typical methods (without channel estimation & LMMSE ) and it will add lower quantity of SNRs.