scholarly journals Wireless channel estimation in OFDM systems based on collaborative filtering techniques

2019 ◽  
Vol 70 (3) ◽  
pp. 244-252
Author(s):  
Velimir Švedek ◽  
Adrian Satja Kurdija ◽  
Željko Ilić

Abstract In this paper, a new channel estimation algorithm in Orthogonal Frequency Division Multiplexing (OFDM) systems is proposed. The proposed algorithm is suitable for cases with low density of pilot sub-carriers, where standard interpolation methods (linear, second order and cubic spline interpolation) are inaccurate. The algorithm improves the interpolation methods by employing memory based collaborative filtering (CF) techniques which are less sensitive to the number and location of the pilot subcarriers. CF algorithms are usually used in the context of recommender systems (e-commerce) for predictions of the unknown user-item ratings based on known values of similar users. The advantage of CF is the ability to e ciently produce quality predictions with highly sparse data. Computer simulations are used to verify the proposed channel estimation algorithm and demonstrate that the proposed algorithm improves predictive accuracy metrics, such as Root Mean Squared Error (RMSE), compared to usual estimation methods.

Author(s):  
Lidong Wang ◽  
Yimei Ma ◽  
Xudong Chang ◽  
Chuang Gao ◽  
Qiang Qu ◽  
...  

Abstract In this paper, an efficient projection wavelet weighted twin support vector regression (PWWTSVR) based orthogonal frequency division multiplexing system (OFDM) system channel estimation algorithm is proposed. Most Channel estimation algorithms for OFDM systems are based on the linear assumption of channel model. In the proposed algorithm, the OFDM system channel is consumed to be nonlinear and fading in both time and frequency domains. The PWWTSVR utilizes pilot signals to estimate response of nonlinear wireless channel, which is the main work area of SVR. Projection axis in optimal objective function of PWWRSVR is sought to minimize the variance of the projected points due to the utilization of a priori information of training data. Different from traditional support vector regression algorithm, training samples in different positions in the proposed PWWTSVR model are given different penalty weights determined by the wavelet transform. The weights are applied to both the quadratic empirical risk term and the first-degree empirical risk term to reduce the influence of outliers. The final regressor can avoid the overfitting problem to a certain extent and yield great generalization ability for channel estimation. The results of numerical experiments show that the propose algorithm has better performance compared to the conventional pilot-aided channel estimation methods.


Symmetry ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 997 ◽  
Author(s):  
Zhang ◽  
Zhou ◽  
Wang

Orthogonal frequency division multiplexing (OFDM) systems have inherent symmetric properties, such as coding and decoding, constellation mapping and demapping, inverse fast Fourier transform (IFFT) and fast Fourier transform (FFT) operations corresponding to multi-carrier modulation and demodulation, and channel estimation is a necessary module to resist channel fading in the OFDM system. However, the noise in the channel will significantly affect the accuracy of channel estimation, which further affects the recovery quality of the final received signals. Therefore, this paper proposes an efficient noise suppression channel estimation method for OFDM systems based on adaptive weighted averaging. The basic idea of the proposed method is averaging the last few channel coefficients obtained from coarse estimation to suppress the noise effect, while the average frame number is adaptively adjusted by combining Doppler spread and signal-to-noise ratio (SNR) information. Meanwhile, to better combat the negative effect brought by Doppler spread and inter-carrier interference (ICI), the proposed method introduces a weighting factor to correct the weighted value of each frame in the averaging process. Simulation results show that the proposed channel estimation method is effective and provides better performance compared with other conventional channel estimation methods.


Author(s):  
А.В. Башкиров ◽  
О.Ю. Макаров ◽  
А.С. Демихова ◽  
М.В. Долженко ◽  
О.В. Ильина

Предложен метод сочетания мультиплексирования с ортогональным частотным разделением каналов (OFDM) с пространственно-временным блочным кодированием (STBC). Предлагаются коды с пониженной сложностью декодирования и высокой эффективностью использования полосы пропускания. Большинство работ по данной тематике предлагают комбинацию кодов STBC-OFDM для ситуаций, где параметры канала известны заранее и прошиты в приемнике. С внедрением новых методов оценки каналов моделируются и анализируются реальные условия, чтобы предложить методы, подходящие для эффективной работы будущих беспроводных технологий, таких как 5G. Исследована методика оценки каналов для систем STBC-OFDM с использованием различного количества передающих и приемных антенн, различного порядка модуляции для пилотных и информационных поднесущих, различного количества пилотных поднесущих и различных условий состояния канала. Представлены результаты моделирования для 2-х и 4-х передающих антенн и 1-х и 2-х приемных антенн, а также проведено сравнение алгоритма оценки канала с идеальным случаем, когда предполагается, что параметры канала известны в приемнике. Кроме того, исследовано влияние группового декодирования путем анализа времени декодирования одного блока STBC-OFDM и времени, сэкономленного на декодировании всей группы блоков данных. Из результатов моделирования видно, что предложенная методика обладает преимуществами повышения вычислительной эффективности системы за счет сокращения времени вычислений при одновременном увеличении числа пилотных поднесущих. Использование метода группового декодирования позволяет системе быть более устойчивой к распространению ошибок. Действительно, в традиционных схемах, использующих итерационный метод, где оценка канала выполняется в начале передачи, распространение ошибки имеет решающее значение, так как ошибка в оценке параметра канала приведет к неточному декодированию данных. В рамках проведенного исследования были предложены новая совместная оценка канала и восстановление поврежденных данных. Метод отличается энергоэффективностью и простотой вычислений за счет того, что он не требует инверсии матрицы на приемнике в отличие от других методов, рассматриваемых в литературе In this paper, a method for combining OFDM with STBC is proposed. Codes with reduced decoding complexity and high bandwidth efficiency are proposed. Most of the works on this topic suggest a combination of STBC-OFDM codes for situations where the channel parameters are known in advance and are embedded in the receiver. With the introduction of new channel estimation methods, real-world conditions are modeled and analyzed to propose methods suitable for efficient operation of future wireless technologies such as 5G. The article explores a channel estimation technique for STBC-OFDM systems using different numbers of transmit and receive antennas, different modulation orders for pilot and data subcarriers, different numbers of pilot subcarriers, and different channel conditions. Simulation results for 2 and 4 transmitting antennas and 1 and 2 receiving antennas are presented, as well as a comparison of the channel estimation algorithm with the ideal case, when it is assumed that the channel parameters are known in the receiver. In addition, the effect of group decoding was investigated by analyzing the decoding time of one STBC-OFDM block and the time saved on decoding the entire group of data blocks. It can be seen from the simulation results that the proposed method has the advantages of increasing the computational efficiency of the system by reducing the computation time while increasing the number of pilot subcarriers. As part of the research carried out in the article, a new joint channel assessment and recovery of damaged data were proposed. The method is distinguished by its energy efficiency and simplicity of calculations due to the fact that the method does not require inversion of the matrix at the receiver, unlike other methods proposed in the literature


2014 ◽  
Vol 989-994 ◽  
pp. 3759-3762 ◽  
Author(s):  
Gulomjon Sangirov ◽  
Yong Qing Fu ◽  
Ye Fang

An orthogonal frequency division multiplexing (OFDM) is one of the effective techniques used in wireless communications. In OFDM systems, channel impairments due to multipath dispersive wireless channels can cause deep fades in wireless channels. The OFDM receiver also requires an accurate and computationally efficient channel state information when coherent detection is involved. Therefore, it needs a good robust estimation method of the channel in wireless communication for OFDM systems. And one of these channel estimation methods is minimum mean square error (MMSE) channel estimation. MMSE channel estimation one most used method in OFDM systems. In this work we enhanced robustness of MMSE channel estimation by using it in base of quasi-cyclic low density parity check (QC-LDPC) coded OFDM system.


2007 ◽  
Vol 16 (03) ◽  
pp. 319-335 ◽  
Author(s):  
QINGHAI YANG ◽  
KYUNG SUP KWAK

This paper addresses the pilot-aided multiuser least square (LS) channel estimation for the uplink of multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. The systems under consideration allow all users use all available subcarriers independently and thus involve multiuser interference in the frequency domain. Direct application of the known pilot-aided single-user channel estimation methods to these systems is prohibited, requiring much more new investigations. The decentralized and centralized channel estimation algorithms are developed according to different multiuser scenarios. Optimal multiuser pilots are proposed, especially for centralized estimation methods with respect to the mean square error (MSE) of LS channel estimate. In addition, channel tracking algorithms are represented in terms of individual user's channels.


2021 ◽  
Author(s):  
Ekin Basak Bektas ◽  
Erdal Panayirci

Abstract In this paper, a new iterative channel estimation algorithm is proposed that exploits channel sparsity in the time domain for DC-biased optical orthogonal frequency division multiplexing OFDM (DCO-OFDM) systems in indoor visible light communications (VLC) in the presence of a clipping noise. A path-based channel model is used, in which the channel is described by a limited number of paths, each characterized by a delay and channel gain. Making use of the pilot symbols, overall sparse channel tap delays and path gains were initially estimated by the compressed sensing approach, in the form of the Orthogonal Matching Pursuit (OMP) and the least-squares (LS) algorithms, respectively. Then a computationally efficient and novel iterative channel estimation algorithm is developed that estimates the clipping noise in the time-domain and compensated for its effect in the frequency-domain. Computer simulation results show that the algorithm converges in maximum two iterations and that yields excellent mean square error (MSE) and bit error rate (BER) performance, outperforming those channel estimation algorithms, which do not have the clipping noise mitigation capability.


2014 ◽  
Vol 35 (3) ◽  
pp. 665-670 ◽  
Author(s):  
Zhi-bin Xie ◽  
Tong-si Xue ◽  
Yu-bo Tian ◽  
Wei-chen Zou ◽  
Qing-hua Liu ◽  
...  

2019 ◽  
Vol 5 (3) ◽  
pp. 6 ◽  
Author(s):  
Neha Dubey ◽  
Ankit Pandit

In wireless communication, orthogonal frequency division multiplexing (OFDM) plays a major role because of its high transmission rate. Channel estimation and tracking have many different techniques available in OFDM systems. Among them, the most important techniques are least square (LS) and minimum mean square error (MMSE). In least square channel estimation method, the process is simple but the major drawback is it has very high mean square error. Whereas, the performance of MMSE is superior to LS in low SNR, its main problem is it has high computational complexity. If the error is reduced to a very low value, then an exact signal will be received. In this paper an extensive review on different channel estimation methods used in MIMO-OFDM like pilot based, least square (LS) and minimum mean square error method (MMSE) and least minimum mean square error (LMMSE) methods and also other channel estimation methods used in MIMO-OFDM are discussed.


2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Ruo-Nan Yang ◽  
Wei-Tao Zhang ◽  
Shun-Tian Lou

In order to track the changing channel in multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems, it is prior to estimate channel impulse response adaptively. In this paper, we proposed an adaptive blind channel estimation method based on parallel factor analysis (PARAFAC). We used an exponential window to weight the past observations; thus, the cost function can be constructed via a weighted least squares criterion. The minimization of the cost function is equivalent to the decomposition of third-order tensor which consists of the weighted OFDM data symbols. To reduce the computational load, we adopt a recursive singular value decomposition method for tensor decomposition; then, the channel parameters can be estimated adaptively. Simulation results validate the effectiveness of the proposed algorithm under diverse signalling conditions.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 83070-83080
Author(s):  
Fran Casino ◽  
Peio Lopez-Iturri ◽  
Erik Aguirre ◽  
Leyre Azpilicueta ◽  
Francisco Falcone ◽  
...  

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