Channel Frequency Response Estimation Research Articles

2D Joint Estimation of Information Symbols and Channel Frequency Response in OFDM Communication Systems

2D Joint Estimation of Information Symbols and Channel Frequency Response in OFDM Communication Systems

Performance Analysis of SIMO–OFDM Systems With Pilot-Aided Channel Estimation

Pilot symbols are commonly modulated on uniformly spaced subcarriers to aid channel estimation, thereby facilitating data demodulation in practical orthogonal frequency-division multiplexing (OFDM) systems operating over quasi-static multipath channels, where the channel frequency response (CFR) remains static within one block. Aided by uniformly spaced pilot symbols, the direct least-square CFR estimation can enable reliable symbol-by-symbol data demodulation within the same OFDM block, based on the principle of generalized likelihood ratio test (GLRT). Such GLRT-based OFDM can be easily incorporated with single-input multiple-output (SIMO) antenna technique to enhance data demodulation over quasi-static channels exhibiting random multipaths. In this article, an upper bound to the average bit error probability (BEP) is analytically derived for this GLRT-based SIMO–OFDM system over quasi-static random multipath channels. The analysis is generally applicable to arbitrary two-dimensional component modulations when the quasi-static SIMO channel consists of independent but not necessarily identically distributed random channel paths with Rician or Rayleigh distributed path response magnitudes. The BEP upper bound facilitates the error performance characterization of the GLRT-based SIMO–OFDM system with respect to data-to-noise power ratio, data-to-pilot power ratio, antenna diversity, pilot density, and pilot power allocation.

Iterative Joint Estimation Procedure of Channel and PDP for OFDM Systems.

The power-delay profile (PDP) estimation of wireless channels is an important step to generate a channel correlation matrix for channel linear minimum mean square error (LMMSE) estimation. Estimated channel frequency response can be used to obtain time dispersion characteristics that can be exploited by adaptive orthogonal frequency division multiplexing (OFDM) systems. In this paper, a joint estimator for PDP and LMMSE channel estimation is proposed. For LMMSE channel estimation, we apply a candidate set of frequency-domain channel correlation functions (CCF) and select the one that best matches the current channel to construct the channel correlation matrix. The initial candidate set is generated based on the traditional CCF calculation method for different scenarios. Then, the result of channel estimation is used as an input for the PDP estimation whereas the estimated PDP is further used to update the candidate channel correlation matrix. The enhancement of LMMSE channel estimation and PDP estimation can be achieved by the iterative joint estimation procedure. Analysis and simulation results show that in different communication scenarios, the PDP estimation error of the proposed method can approach the Cramér-Rao lower bound (CRLB) after a finite number of iterations. Moreover, the mean square error of channel estimation is close to the performance of accurate PDP-assisted LMMSE.

Optimum DCT type-I based transceiver model and effective channel estimation for uplink NB-IoT system

Single-tone and multi-tone transmissions in the narrowband Internet of Things (NB-IoT) uplink system can be accomplished by employing different orthogonal basis. In this paper, we develop an uplink NB-IoT baseband system model and derive the corresponding analytical signal model based on the discrete cosine transform type-I (DCT-I) domain. Basically, the circular convolution and channel matrix diagonalization issues for designing DCT-based systems are addressed without exploiting any redundancy (a prefix and a suffix sequences, and zero-padding (ZP)) into each transmitted data symbol blocks. In our proposed DCT-I based transceiver, we employ a standard cyclic prefix (CP) and apply discrete Fourier transform (DFT) and inverse DFT (IDFT) operations directly to make the channel matrix circulant and diagonal, resulting in the use of one-tap frequency-domain channel equalizer without incorporating extra front-end prefilter at the receiver. Furthermore, we propose novel least squares (LS) and linear minimum mean square error (LMMSE) channel estimators by considering the energy concentration and spectral compaction properties of DCT-I for the uplink NB-IoT system. The expressions for the DCT-I domain LS and LMMSE estimators are derived for channel frequency response estimation and mean square error computation. Finally, the viability of the proposed CP-DCT-I-NB-IoT uplink system, as well as the channel estimators, are tested compared with the standardized CP-DFT-NB-IoT and ZP-DCT type-2 even based single-carrier frequency-division multiple access (SC-FDMA) systems through rigorous computer simulations.

Comb Type Pilot Based Channel Estimation using Dft Based Interpolation for Spatial Modulated OFDM Systems

An integration of Spatial Modulation with Orthogonal Frequency Division Multiplexing (SM OFDM) is a recently evolved transmission technique. In practical scenarios, channel estimation is significant for detecting transmitted data coherently. Impulse response based interpolation technique that provides channel frequency response estimate with reduction in noise error is proposed for comb type pilot based channel estimation of SM OFDM system along with 1D interpolation techniques under frequency selective channel. This scheme focus on carrying out smoothing and estimation in time domain and transforming output back to the frequency domain. BER performance is investigated for Rayleigh channel employing COST 207 project model on two test urban environments (Typical and Bad) for 4 and 16 QAM SM OFDM systems. Results show that the Least Square estimator with DFT interpolation performs finer compared to all one dimensional interpolation methods with less computational complexity by employing FFT algorithms.

Two-Stage Method for Joint Estimation of Information Symbols and Channel Frequency Response in OFDM Communication Systems

The optimal and quasi-optimal algorithms of two-stage joint estimation of information symbols and frequency response (FR) of multibeam channels in OFDM-based communication systems have been synthesized. They involve the calculation of a posteriori probability density of estimated processes. At the first stage, the recurrent calculation of joint a posteriori distributions of information symbols and the frequency response is performed from two sides of the measurement vector. At the second stage, a posteriori distributions are combined on each of subcarriers that are obtained as a result of the first stage estimation. Based on the obtained a posteriori distributions, estimates of the information symbol and channel FR are determined by the criteria of a posteriori probability maximum and the average mean squared error minimum, respectively. The performance of synthesized algorithms similar to the well-known MMSE algorithm involves the need of knowledge of statistical properties of communication channel. The device implementing the optimal algorithm is multichannel, each channel of which is matched with the corresponding value of symbol from the modulation constellation. The quasi-optimal algorithm was obtained by using the Gaussian approximation of a posteriori probability density. It should be noted that this algorithm preserves its multichannel structure. The approbation of the presented algorithm was conducted using the computer-aided statistical simulation for different parameters of multibeam communication channels and the comparison of the obtained results with the results obtained by the MMSE and LS algorithms. The simulation results showed that the error probability decreases by about 2 times with a maximum signal propagation delay of 100 μs.

Two-Stage Channel Frequency Response Estimation in OFDM Systems

This paper proposes two-stage channel frequency response estimation algorithm in communication systems with OFDM technology. Algorithm is based on Kalman filter. Pilots from current and previous OFDM symbols are used for channel estimation. At the first stage data is processed in time and frequency directions. Pilots from the current OFDM symbol are filtered and at the position, where the pilots from the previous OFDM symbols should be placed, predictions are made. Predictions are based on the pilots and channel correlation characteristics. The data processing carried out on both sides relative to the array of processed data in frequency direction and on one side at processing in time direction. The results of processing are optimally combined at the second stage. The autoregressive process was used as a channel model. The analysis of the developed algorithm carried out on a model example by statistical modeling. Modeling showed that application of designed algorithm allows reducing the standard deviation of the estimation error of channel frequency response. The efficiency of designed algorithm studied using Rayleigh channel with Doppler spectrum described by Jakes model. The autocorrelation characteristics of the channel were considered as known. Modeling showed a decrease in the probability of a bit error during reception using the proposed algorithm. It is also shown that an increase in the order of the autoregressive model reduces the error in estimating the frequency response of the communication channel.

Weighted TSVR Based Nonlinear Channel Frequency Response Estimation for MIMO-OFDM System

A channel frequency response estimation method based on weighted twin support vector regression (TSVR) for pilot-aided multi-input multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) system is proposed in this work. Nonlinearity of channel in wireless communication system is considered. The channel is fading in time domain produced by Doppler effect and in frequency domain by propagation multipath. An improved TSVR-weighted TSVR is adopted to estimate channel parameters in MIMO-OFDM system. The weights obtained by wavelet transform method are used to improve the regression performance of TSVR. The characteristic of the proposed algorithm is that different training samples are given weights calculated according to the distance from the samples to the mean values filtered by wavelet transform method. Due to the regression characteristics of TSVR, the channel frequency response estimation algorithm proposed in this work has good estimation performance and anti noise ability. Experimental results show that compared with the classical pilot aided channel estimation method, the proposed algorithm has better performance in estimating mean square error.

Nonlinear Channel Estimation for OFDM System by Wavelet Transform Based Weighted TSVR

An efficient nonlinear channel estimation method for pilot-aided orthogonal frequency division multiplexing system is proposed in this work. The considered channel is selective in time and frequency domain, that is doubly selective channel. Wavelet transform based weighted twin support vector regression is used for channel frequency response estimation, which is suitable for the regression of nonlinear system. Different from traditional support vector regression algorithm, the proposed algorithm gives samples different weights according to their variance calculated based on wavelet transform. The weights are added into both first and quadratic terms of the objective functions to reduce the impact of outliers, which is likely to appear in the received pilot signal polluted by noise. The proposed channel estimation algorithm has good generalization ability and can reduce the influence of overfitting problem. The results of computational tests show that the proposed algorithm is with better estimating performance compared to the classical pilot-aided channel estimation methods.

Channel frequency response estimation method based on pilot’s filtration and extrapolation

Introduction. Mobility is one of the main requirements for modern communication system. For OFDM systems it means spreading the wideband signals thru the multipath channel with variable in time parameters. Receiver should estimate channel parameters for demodulation the received signal. Problem statement. The pilots from current and previous received OFDM symbols are used for channel estimation. Development of channel frequency response estimation method that use only pilots from current received symbol is the task. Method development. This paper proposes a channel frequency response estimation method based on pilot’s filtration and extrapolation. Method consists of two stages. At first stage performs pilot’s filtration in forward and backward directions by Kalman filter and combining the results in each point. It allows increase the accuracy of channel estimation. At second stage performs extrapolation the channel frequency response between pilots in forward and backward directions and combining the results. Experimental results. Performed analysis of developed method by statistical modeling on example of communication system with channel frequency response described as second order autoregressive model. The standard deviation of estimation error for developed algorithm and Kalman algorithm was calculated. Mean square error of channel estimation for developed method and method of least square was compared. Conclusions. Developed algorithm allows decrease the standard deviation of channel frequency response estimation error in comparing with Kalman algorithm. Mean square error of channel frequency response estimation for developed method is lower than for method of least square. Key words: OFDM, digital communication system, wireless channel, channel frequency response, estimation, autoregressive model, Kalman filter.

Sparse Reconstruction Off-grid OFDM Time Delay Estimation Algorithm Based on Bayesian Automatic Relevance Determination

Aiming at the problem of single measurement vector (SMV) OFDM signal delay estimation in complex environment, a sparse reconstruction off-grid delay estimation algorithm based on Bayesian automatic correlation determination (OGBARD) is proposed. The algorithm adopts Bayesian framework, from the perspective of further mining useful information, introduces asymmetric autocorrelation to determine a priori parameters and off-grid parameters, and integrates them into the parameter estimation process, which improves the delay estimation accuracy under SMV and low signal-to-noise ratio (SNR) condition. Firstly, based on the channel frequency response (CFR) estimation value of the OFDM signal physical layer protocol data unit, the algorithm constructs a sparse representation model with off-grid parameters, and then introduces the probability hypothesis of noise vector, off-grid parameters and sparse coefficient vector in the model. Finally, based on Bayesian inference, the expectation maximization (EM) algorithm is used to estimate the hyperparameters. Simulation experiments show that the proposed algorithm has better estimation performance than the comparison algorithm and is closer to the Cramer–Rao Bound (CRB).

Research on the Intelligent Signal Channel Sensing Based ICI Elimination Algorithm of the OFDM System

This paper investigated the channel estimation based inter-carrier interference (ICI) cancellation algorithm elimination of the orthogonal frequency division multiplexing (OFDM) system. Compared to the traditional technologies, this new algorithm would be processed as part of ICI as noise, and to reduce the effects of interference between the carrier frequency offset by simultaneous judgment and impulse channel frequency response (CFR). At the same time, the algorithm considered the CFR estimate of the frequency-offset effect, the closest to the actual frequency offset value, thereby reducing the ICI. To simplify the calculation, the frequency-offset hypothesis was determined utilizing a binary search method, and matrix interference was simplified. Simulation results demonstrated the effectiveness and superiority of the algorithm.

Golay-Correlator Window-Based Noise Cancellation Equalization Technique for 60-GHz Wireless OFDM/SC Receiver

In this paper, a Golay-correlator window-based noise cancellation (GC-WNC) technique with frequency-domain equalizer (FDE) is proposed. The GC-WNC is a cooperative scheme in the time and frequency domains to combat the multipath effect in nonline-of-sight (NLOS) and LOS channels for orthogonal frequency-division multiplexing (OFDM) and single-carrier mode baseband inner receiver over 60-GHz environment for IEEE 802.15.3c and 802.11ad. According to mean-square error criterion, WNC approach is to minimize the estimation error between the ideal and the estimated channel frequency response (CFR) on each subchannel. The CFR is precisely obtained as coefficients of FDE to compensate multipath effect even in NLOS channel. The GC-WNC FDE with 8X-parallelism is designed as a part of digital baseband inner receiver with 40-nm CMOS general-purpose process. Because of area restriction of tape-out chip, only the OFDM mode is fabricated in the chip. The GC-WNC FDE has an equivalent gate count of 230k occupying 11.3% of the baseband inner receiver. Based on the chip measurement results, the baseband inner receiver with GC-WNC FDE provides 24-Gb/s throughput with 500-MHz operating clock and 0.94 V supply voltage. The power consumption of GC-WNC FDE is 69.79 mW. The baseband inner receiver with GC-WNC FDE can deliver a multigigabit per second throughput with the power dissipation of 2.91/2.26 mW/Gb/s at 500-/330-MHz operating clock for the OFDM mode.

Analysis of the Effect of Coherence Bandwidth on Leakage Suppression Methods for OFDM Channel Estimation

In this paper, we analyze the effect of the coherence bandwidth of wireless channels on leakage suppression methods for discrete Fourier transform (DFT)-based channel estimation in orthogonal frequency division multiplexing (OFDM) systems. Virtual carriers in an OFDM symbol cause orthogonality loss in DFT-based channel estimation, which is referred to as the leakage problem. In order to solve the leakage problem, optimal and suboptimal methods have already been proposed. However, according to our analysis, the performance of these methods highly depends on the coherence bandwidth of wireless channels. If some of the estimated channel frequency responses are placed outside the coherence bandwidth, a channel estimation error occurs and the entire performance worsens in spite of a high signal-to-noise ratio.

Efficient co-channel interference suppression in MIMO-OFDM systems

In this paper, we investigate channel frequency response (CFR) matrix and interference-plus-noise covariance matrix (ICM) estimation in multiple-input multiple-output (MIMO) and orthogonal frequency division multiplexing (OFDM) systems to suppress co-channel interference at the receiver side. We employ least square criterion to perform the initial CFR estimation. Then we estimate the autocorrelation function of interference-plus-noise in the time domain, instead of estimating the ICM in the frequency domain directly. The autocorrelation function estimation has two steps. Firstly, we present the inherent relationship between the expectation of the sample autocorrelation function of the residual (SAFR) and the true autocorrelation function, which is actually a linear transformation. Based on this, we propose a compensating method. This compensation brings significant performance gains when the pilot OFDM symbol number is small. Secondly, since the compensated SAFR cannot be guaranteed to be an autocorrelation sequence (ACS), which will make the obtained ICM loss the positive semidefinite property, we utilize semidefinite programming (SDP) to find an ACS that is the nearest to the compensated SAFR. The SDP is solved in its dual form, which yields a significant reduced complexity. Finally the estimated ICM is reutilized to revise the CFR estimation. The estimated CFR and ICM show excellent interference suppression performances when being applied in an interference rejection combining receiver.

Blind ICA detection based on second-order cone programming for MC-CDMA systems

The multicarrier code division multiple access (MC-CDMA) technique has received considerable interest for its potential application to future wireless communication systems due to its high data rate. A common problem regarding the blind multiuser detectors used in MC-CDMA systems is that they are extremely sensitive to the complex channel environment. Besides, the perturbation of colored noise may negatively affect the performance of the system. In this paper, a new coherent detection method will be proposed, which utilizes the modified fast independent component analysis (FastICA) algorithm, based on approximate negentropy maximization that is subject to the second-order cone programming (SOCP) constraint. The aim of the proposed coherent detection is to provide robustness against small-to-medium channel estimation mismatch (CEM) that may arise from channel frequency response estimation error in the MC-CDMA system, which is modulated by downlink binary phase-shift keying (BPSK) under colored noise. Noncoherent demodulation schemes are preferable to coherent demodulation schemes, as the latter are difficult to implement over time-varying fading channels. Differential phase-shift keying (DPSK) is therefore the natural choice for an alternative modulation scheme. Furthermore, the new blind differential SOCP-based ICA (SOCP-ICA) detection without channel estimation and compensation will be proposed to combat Doppler spread caused by time-varying fading channels in the DPSK-modulated MC-CDMA system under colored noise. In this paper, numerical simulations are used to illustrate the robustness of the proposed blind coherent SOCP-ICA detector against small-to-medium CEM and to emphasize the advantage of the blind differential SOCP-ICA detector in overcoming Doppler spread.

NEURO FUZZY BASED PERFORMANCE ANALYSIS OF MULTIBAND ULTRA WIDE BAND ORTHOGONAL FREQUENCY DIVISION MULTIPLEXING SYSTEM

This study proposes an efficient channel-estimation scheme for Multiband (MB) Orthogonal Frequency Division Multiplexing (OFDM)-based Ultra Wide Band (UWB) communication systems. One of the challenges in wireless system is the frequency selective fading caused due to multipath channel between the transmitter and receiver. The signal bandwidth in broad band cellular wireless systems typically exceeds the coherence bandwidth of the multipath channel. To overcome such a multipath fading environment with low complexity and to increase the performance, UWB OFDM system is used. To practically realize MB-OFDM UWB, one needs to cope with numerous design challenges, particularly in receiver designs such as symbol timing, Carrier Frequency Offset (CFO) and sampling frequency offset compensation, as well as Channel Frequency Response (CFR) estimation. A channel estimation scheme using a Takagi-Sugeno (T-S) fuzzy based neural network under the time varying velocity of the mobile station in a UWB OFDM system is proposed in this study. In our proposal, by utilizing the learning capability of Adaptive Neuro-Fuzzy Inference System (ANFIS), the ANFIS is trained with correct channel state information then the trained network is used as a channel estimator. To validate the performance of our proposed method, simulation results are given and found that it gives more accurate prediction of channel coefficients as compared with fuzzy channel estimator under various highly noisy multipath channel conditions.

빗 형태 패턴을 가지는 OFDM 시스템을 위한 파일럿 심볼 기반 채널 주파수 응답의 추정

The pilot assisted channel frequency response (CFR) estimation schemes for an OFDM-based system with virtual subcarriers are analyzed under the assumption that pilot symbols are located according to a comb-type pattern in the OFDM block. In particular, as the minimum mean square error (MMSE) based scheme aiming to directly predict the channel impulse response and the MMSE based scheme aiming to suppress the leakage have not been clearly compared, by proving that the mean square errors (MSEs) of the latter scheme is always larger than that of the former scheme, this paper shows that the former scheme is superior to the latter scheme. Moreover, the impact of the number of pilots on the performances of the MMSE and least-square based channel estimation schemes are investigated. The performance analyses of the presented schemes are confirmed by computer simulation. 논문 14-39A-06-04 The Journal of Korea Information and Communications Society '14-06 Vol.39A No.06 http://dx.doi.org/10.7840/kics.2014.39A.6.333 333 ※ 본 논문은 2013학년도 중소기업 융복합기술개발사업을 수행 중인 산업체 위월드(주)의 위탁연구개발 지원에 의하여 연구되었음. ※ 본 논문은 2013학년도 건국대학교의 연구년 교원 지원에 의하여 연구되었음. First Author : Department of Electronics Engineering, Konkuk University, woongk88@konkuk.ac.kr, 학생회원 ° Corresponding Author : Department of Electronics Engineering, Konkuk University, ecyoon@konkuk.ac.kr, 종신회원 * 건국대학교 전자공학부, mc3359@konkuk.ac.kr, 학생회원 논문번호:KICS2014-04-125, Received April 8, 2014; Revised May 27, 2014; Accepted May 27, 2014 The Journal of Korea Information and Communications Society '14-06 Vol.39A No.06

Estimation and compensation for the influence of interchannel interference in reception of OFDM signals

The algorithms intended for estimating and compensating for the distortions of orthogonal frequency-division multiplexing signals are discussed under the conditions of reception in frequency-selective fading channels. The results of computer simulation thereof are presented. These algorithms are based on a multidimensional digital Kalman filter (DKF) and involve interpolation of the channel frequency response estimates obtained with the help of the DKF and compensation for distortions, which are optimal in terms of the minimum mean squared error, and estimation of the variance of noise and disturbance induced by interchannel interference via Doppler spectrum analysis.

Biased estimators with adaptive shrinkage targets for orthogonal frequency division multiple access channel estimation

In orthogonal frequency division multiple access-based systems where channel frequency response (CFR) estimation has to be carried out using only the user-specific (localised) pilots within a small time frequency block, the accuracy of the estimates suffer because of the limited number of pilots and imperfect knowledge of the channel statistics. A biased estimator is proposed for the estimation of CFR over the time frequency block. Hypothesis tests are designed to ascertain the time and frequency selectivity of the CFR within the region of interest, and the outcome of these tests are used to determine a vector shrinkage target for the biased estimator. Simulation results indicate that the performance of the proposed estimator is comparable to that of the optimal minimum mean square error estimator, even though it does not have any knowledge of the channel statistics.