Comb-type Pilot Research Articles

Machine Learning-Based Channel Estimation Techniques for ATSC 3.0

Channel estimation accuracy significantly affects the performance of orthogonal frequency-division multiplexing (OFDM) systems. In the literature, there are quite a few channel estimation methods. However, the performances of these methods deteriorate considerably when the wireless channels suffer from nonlinear distortions and interferences. Machine learning (ML) shows great potential for solving nonparametric problems. This paper proposes ML-based channel estimation methods for systems with comb-type pilot patterns and random pilot symbols, such as ATSC 3.0. We compare their performances with conventional channel estimations in ATSC 3.0 systems for linear and nonlinear channel models. We also evaluate the robustness of the ML-based methods against channel model mismatch and signal-to-noise ratio (SNR) mismatch. The results show that the ML-based channel estimations achieve good mean squared error (MSE) performance for linear and nonlinear channels if the channel statistics used for the training stage match those of the deployment stage. Otherwise, the ML estimation models may overfit the training channel, leading to poor deployment performance. Furthermore, the deep neural network (DNN)-based method does not outperform the linear channel estimation methods in nonlinear channels.

Capacity and BER performance improvement in integrated MIMO‐OFDM system using optimal power allocation, channel estimation, and turbo coding

SummaryAmong communication systems, multiple input multiple output (MIMO) system has the capability of providing spectral efficiency, high data rates, diversity gain, and improved reliability. Suitably designed orthogonal frequency division multiplexing (OFDM) transmits the signal without inter symbol interference and multipath fading. Hence, MIMO‐OFDM is a strong candidate for 4G and 5G wireless systems. However, variations in signal‐to‐noise ratio (SNR) due to the random nature of the channel and poor capacity at low SNR are critical issues in conventional MIMO‐OFDM system. This paper explains how optimal power allocation (OPA), channel estimation, and coding improve the capacity and bit error rate (BER) performance of MIMO‐OFDM system. In OPA, the transmitter power is distributed adaptively to the channels based on the SNR statistics using singular value decomposition and water filling algorithm. In case of low SNR, less number of channels are selected for power allocation. Least squares (LS), minimum mean square error (MMSE), and least mean square (LMS) estimators are considered in comb type pilot channel estimation while turbo code is used with code rates of 1/2 and 1/3. From the simulation results, capacity improvement of 5 b/s/Hz and 11 b/s/Hz is observed for MIMO‐OFDM systems with four antennas and eight antennas, respectively. It is also found that performance of LMS estimator improved by 3.5‐dB SNR over LS and 1 dB SNR over MMSE. In this paper is shown how LMS estimator and 1/3 turbo code have been integrated with MIMO‐OFDM, and this has resulted in around 4‐dB SNR improvement over conventional MIMO‐OFDM.

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.

Joint Channel and Phase Noise Estimation and Data Detection for GFDM

Generalized frequency division multiplexing (GFDM), an enabler of beyond-5G wireless networks, can be critically impaired due to radio frequency (RF) phase noise. However, joint channel estimation and phase noise compensation for GFDM systems have not been addressed before. Hence, we tackle this problem. To this end, we propose an iterative algorithm for joint channel and phase noise estimation and two algorithms for joint data detection and phase noise compensation. These algorithms use linear and non-linear least-squares (NLS) methods and employ block-type and comb-type pilots. The complexity of these algorithms is also analyzed. Moreover, to reduce their complexity, interpolation techniques are deployed to decrease the number of unknowns. We also analyze the signal-to-interference-plus noise ratio (SINR) and sum-rate of GFDM contaminated with phase noise. Furthermore, the accuracy of the channel and phase noise estimates is established via Cramer-Rao lower bounds (CRLBs). The simulation results illustrate that the mean-squared error (MSE) performance of the proposed joint channel and phase noise estimator reaches the CRLB. Moreover, the proposed joint data symbol detection and phase noise compensation algorithms nearly eliminate the impacts of phase noise in GFDM systems.

OFDM-IDMA Sistemi İçin Genetik Algoritmaya Dayalı Biyo-İlhamlı Pilot Dizayn Yaklaşımı

It is well known that the efficiency of a channel estimator employing the strategy of comb-type pilot placement can be controlled by adjusting the positions of pilot tones. In this paper, by considering this situation, in order to maximize the estimation precision of the least squares (LS) algorithm utilized as a channel estimator in orthogonal frequency division multiplexing – interleave division multiple access (OFDM-IDMA) scheme, the genetic algorithm (GA) possessing a wide range of uses due to its powerful problem solving capability was utilized in the optimization of pilot positions. Besides, the computational load of mean square error (MSE) which is used as the objective function of GA was avoided by employing its upper bound during the optimization process. The upper bound of MSE was achieved by utilizing the Gershgorin disc theorem. In the simulations, the suggested pilot arrangement strategy based on the GA was compared to the conventional techniques like equispaced and random pilot placements in point of two criteria known as bit error rate (BER) and MSE. Simulation results put forth that GA-based pilot design strategy establishes a very clear superiority over the other considered methods by providing significant MSE and BER performances.

Estimation of UFMC Fading Channels Using H∞ Filter

Universal filtered multi-carrier (UFMC) modulation is a very powerful candidate to be employed for future 5G mobile systems. It overcomes the limitations and restrictions in current modulation techniques employed in 4G mobile systems and supports future applications, such as machineto-machine (M2M), device-to-device (D2D), and vehicle-tovehicle (V2V) communications. In this paper, we address the estimation of UFMC fading channels based on the comb-type pilot arrangement in the frequency domain. The basic solution is to estimate the fading channel based on the mean square error (MSE) or least square (LS) criteria with adaptive implementation using least mean square (LMS) or recursive least square (RLS) algorithms. However, these adaptive filters seem not to be effective, as they cannot fully exploit fading channel statistics, particularly at high Doppler rates. To take advantage of these statistics, time-variations of the fading channel are modeled by an autoregressive process (AR), and are tracked by an H∞ filter. This, however, requires that AR model parameters be known, which are estimated by solving the Yule-Walker equation (YWE), based on the Bessel autocorrelation function (ACF) of the fading channel with a known Doppler rate. Results of Matlab simulations show that the proposed H∞ filter-based channel estimator is more effective when compared with existing estimators

Pilot Based Channel Estimation and Synchronization in OFDM System

Channel estimation and synchronization are considered the most challenging issues in Orthogonal Frequency Division Multiplexing (OFDM) system. OFDM is highly affected by synchronization errors that cause reduction in subcarriers orthogonality, leading to significant performance degradation. The synchronization errors cause two issues: Symbol Time Offset (STO), which produces inter symbol interference (ISI) and Carrier Frequency Offset (CFO), which results in inter carrier interference (ICI). The aim of the research is to simulate Comb type pilot based channel estimation for OFDM system showing the effect of pilot numbers on the channel estimation performance and propose a modified estimation method for STO with less number of pilot to mitigate ISI effect. Channel estimation is simulated for different pilot number with 16QAM modulation in Ped-A Rayleigh channel. The STO effect assumed less than the cyclic prefix length to minimize ISI and maintain the orthogonality between subcarriers. The simulation results show that the high number of pilots are needed to achieve good channel estimation in case no synchronization used while similar results are achieved with smaller number of pilots if the propose modification on the synchronization method are used aligned with the channel estimation. The proposed system is evaluated in terms of BER and SNR.

Pilot spacing controller in orthogonal frequency division multiplexing systems

As the backbone of the fifth generation, 5G communications, Orthogonal Frequency Division Multiplexing, OFDM is seen to be reliable in addressing Inter-symbol Interference, ISI issues as well as providing high-speed access to broadband. Channel estimation and tracking are generally carried out by transmitting known pilot symbols in given positions of the frequency-time grid. However, the use of a fixed amount of pilot for all channel circumstances is hugely detrimental. Several methods, especially on block-type and comb-type pilot arrangement, have presented. In this paper, the method of determining the pilot space depends on the current channel quality. The proposed technique focused on improving estimation and bandwidth in time-varying and frequency-selective fading channels without increasing the complexity and sacrifice the bandwidth efficiency of the OFDM system.

A general framework for joint estimation-detection of channel, nonlinearity parameters and symbols for OFDM in IoT-based 5G networks

Despite being a strong candidate also for future cellular networks, OFDM’s main drawback is the high peak-to-average power ratio. This requires transmitters to deploy high dynamic range power amplifiers which are difficult to manufacture and thereby expensive. It is particularly problematic in future IoT-based 5G networks, in which a lot of presumably low-cost low-power devices transmit data to a high-quality receiver. In order to make such transmitters as simple and cheap as possible, we consider receiver-side nonlinearity compensation and symbol detection. In particular, we study the problem of joint maximum-likelihood estimation-detection of channel and nonlinearity parameters and symbols using frequency-domain comb-type pilots in multi-path fading OFDM systems, and propose an iterative optimization algorithm to solve it. We also calculate the Cramér-Rao lower bound for a general type of memoryless nonlinearity and show that the proposed algorithm attains it, for high signal-to-noise ratios. We then show by numerical evaluations that the algorithm converges fast and the difference of its performance with the one of the genie-aided scenario, with perfect a priori knowledge of nonlinearity parameters and channel, is negligible.

Singular Value Decomposition Channel Estimation in STBC MIMO-OFDM System

The multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) technology is the combination of the OFDM and MIMO technologies, which could improve the system capacity and make efficient utilization of the frequency spectrum. This paper utilizes space-time block coding (STBC) to achieve diversity gains and combat the channel fading. However, channel estimation is an essential block for space-time block decoding (STBD). Many channel estimation methods are utilized for the single antenna OFDM system, but they cannot be directly applied to the multiple antennas system due to the interference from other antennas. In this paper, orthogonal pilot sequences are designed to suppress the interference of pilot symbols from other transmit antennas. This paper also derives a minimum mean square error (MMSE) channel estimation method in MIMO-OFDM systems. The MMSE method involves the inverse operation of the channel autocorrelation matrix, which has a large calculation complexity. To further reduce the complexity of the MMSE method, the singular value decomposition (SVD) is used to decompose the channel autocorrelation matrix, which avoids the inverse operation. Simulation results verify that the SVD channel estimation method with comb-type pilots and STBC can be effectively adapted to multipath propagation conditions.

Channel Estimation Based on IOTA Filter in OFDM/OQPSK and OFDM/OQAM Systems

In this paper, we present a study of bit error rate (BER) for orthogonal frequency division multiplexing/offset quadrature phase shift keying (OFDM/OQPSK) and OFDM/offset quadrature amplitude modulation (OQAM) systems with an isotropic orthogonal transfer algorithm (IOTA) filter. The novel noise suppression method based on an IOTA filter is proposed to reduce the error of channel estimation caused by additive white Gaussian noise (AWGN). The OFDM/OQPSK and OFDM/OQAM systems do not insert the guard interval (GI) and pilots in the signal frames, thus they possess transmission efficiency. An analysis was carried out for convolutional coded OFDM/OQPSK and OFDM/OQAM systems in Rayleigh fading channels with generator polynomials and constraint lengths. Compared with conventional OFDM/QPSK and OFDM/QAM systems with the insertion of comb-type pilots, the proposed IOTA filter-based channel estimation method can provide significant energy per bit to time-varying noise power spectral density ratio gains over time and frequency-selective propagation Rayleigh fading channels in OFDM/OQPSK and OFDM/OQAM systems.

A Universal Channel Estimation Algorithm Based on DFT Smoothing Filtering

Channel estimation is a virtual component to ensure the performance in the orthogonal frequency division multiplexing (OFDM). Smoothing filter is often used to suppress noise to improve the estimation performance. However, the conventional smoothing filtering methods have paid little attention on the virtual subcarriers, which is required in practical system but will introduce interference. Therefore, in this paper, we proposed a universal channel estimation algorithm in which the discrete Fourier transform (DFT) smoothing filtering is used when the virtual subcarriers is considered. What is more, the proposed method is applicable to the OFDM system with either block-type or comb-type pilot, and it can be easily extended to multiple input multiple output (MIMO) system. The proposed method employs windowing, extraction and adaptive filter modules one or more based on conventional DFT-based channel estimation for different pilot patterns. The simulation results show that the proposed method has better performance than the conventional DFT-based channel estimation under the same complexity.

Channel estimation using a reduced rate of pilot subcarriers for OFDM systems over doubly‐selective channels

This study presents an improved channel estimation method for orthogonal frequency division multiplexing (OFDM) over doubly-selective channels. Channel variation has been approximated by the basis expansion model using a specific comb-type pilot approach. Since the data are transmitted as successive symbols in OFDM systems, the authors derive a channel estimation technique exploiting the additional information provided by adjacent symbols pilots. The main idea of the proposed method is to reduce the pilots to useful data ratio in order to improve the effective throughput and to increase the model accuracy in high mobility situations. The proposed algorithm has been investigated by considering both the conventional linear minimum mean square error and the least squares estimator. Various simulations have been conducted by considering different pilot rates with high Doppler effects and additive white Gaussian noise. The obtained results, in terms of the mean square error and binary error rate, show that the proposed algorithm outperforms the conventional techniques which are based on comb pilot-assisted estimation.

Comparative Study of MIMO-OFDM Channel Estimation in Wireless Systems

Determining the channel characteristics and how it affects transmitted signals is known as channel estimation. MIMO OFDM is a combination of MIMO and OFDM techniques. In this paper, comparative studies of MIMO, MISO and SISO channel estimation, using OFDM was performed. The block type and the comb type pilot arrangements were compared, and also various interpolation techniques were also compared to determine the optimum performance. The Bit Error Rate and MSE were employed as the performance metrics. This research was carried out by modeling and simulating the wireless communication system using MATLAB. It was discovered that the FFT interpolation has the best performance compared to other interpolation techniques. It was also shown that the MMSE outperformance the LS, but this is achieved at the cost of system complexity. An improvement in system performance was also observed with an increase in the number of antennas (i.e SISO, MISO and MIMO respectively), and also the OFDM helps combat interference and improves the bandwidth efficiency.

Non-orthogonal basis expansion based laser phase noise suppression in CO-OFDM systems

A laser phase noise suppression approach, based on non-orthogonal basis expansion (NOBE), is proposed for coherent optical orthogonal frequency division multiplexing (CO-OFDM) systems. In the NOBE approach, the time-varying laser phase noise is (sub-) optimally reconstructed using a bank of non-orthogonal expansion bases. Theoretical derivation of the non-orthogonal basis expansion matrices using the minimum mean-square error (MMSE) criteria is presented analytically. Compared with the conventional inverse discrete Fourier transform (IDFT)-based orthogonal basis expansion (OBE) method, the proposed NOBE approach, with the same expansion order L, offers higher accuracy in carrier phase estimation. Numerical analysis shows that the system’s tolerance to laser phase noise is significantly enhanced by the new method thanks to the lower modeling error. For example, the laser linewidth-symbol period product in an ∼ 100-Gbps 16QAM CO-OFDM system at an optical signal-to-noise-ratio (OSNR) of 22 dB achieves 3.87×10−2 with the NOBE (L=3), which is approximately twice that with the OBE. The impact of residual carrier frequency offset (CFO) on the NOBE is also semi-analytically investigated, which shows that the NOBE has robust performance for the residual CFO up to 2 MHz under a subcarrier spacing of 31.25 MHz. By taking advantage of the elaborately-designed comb-type pilot subcarriers pattern, the computational complexity of NOBE is also lower than that of the OBE. Since the NOBE with a sub-optimal basis expansion matrix does not require a priori knowledge of the product of laser linewidth and symbol period, it is well-suited for practical implementations.

Pilot-Based Time Domain SNR Estimation for Broadcasting OFDM Systems

The estimation of signal-to-noise ratio (SNR) is a major issue in wireless orthogonal frequency-division multiplexing (OFDM) system. In OFDM system, each frame starts with a preamble symbol that facilitates the SNR estimation. However, the performance of preamble-based SNR estimation schemes worsens in the fast-changing environment where channel changes symbol to symbol. Accordingly, in this paper, we propose a novel pilot-based SNR estimation scheme that optimally exploits the pilot subcarriers that are inserted in each data symbol of the OFDM frame. The proposed scheme computes the circular correlation between the received signal and the comb-type pilot sequence to obtain the SNR. The simulation results are compared with the conventional preamble-based Zadoff-Chu sequence SNR estimator. The results indicate that the proposed scheme generates near-ideal accuracy; especially in low SNR regimes, in terms of the normalized mean square error (NMSE). Moreover, this scheme offers a significant saving of computation over a conventional time domain SNR estimator.

Enhanced brain image retrieval using carrier frequency offset compensated orthogonal frequency division multiplexing for telemedicine applications

AbstractWireless technology plays a vital role in the Electronic health (e‐health) applications such as telemedicine and remote patient monitoring. One of the major challenges of telemedicine applications is ensuring adequate quality of service and realizing precise diagnosis. Telemedicine employs image fusion to enhance the quality of medical image for better diagnosis. However, the transmission of medical image needs high data rate and bandwidth. Due to the robustness to multipath fading, high data rate transmission capability, high flexibility, high bandwidth efficiency, and easy implementation using fast Fourier transform, an orthogonal frequency division multiplexing (OFDM) is the suitable technique for medical image transmission in telemedicine applications This paper is focused on improving the quality of the fused brain image transmission over OFDM based telemedicine service using comb type pilot based carrier frequency offset compensation. The simulation results show that the proposed method offers better performance in terms of mean squared error, Euclidean distance, peak signal to noise ratio, bit error rate, carrier to interference ratio, and computational complexity.

An Efficient Preamble Design Based on Comb-Type Pilots for Channel Estimation in FBMC/OQAM Systems

In this paper, we propose an efficient preamble design based on comb-type pilots (CTP) for channel estimation in filter bank multicarrier with offset quadrature amplitude modulation (FBMC/OQAM) systems. The proposed preamble is similar to the CTP widely adopted in OFDM systems, within a specified window. Thus, it enables OFDM-like channel estimation with low complexity for FBMC/OQAM and removes the inter-symbol interference/inter-carrier interference in FBMC/OQAM channel estimation. Moreover, the proposed preamble design can be easily extended to support multiple antennas (MIMO). Simulation results demonstrate that the proposed preamble length could be very close to those of conventional preamble design such as the interference cancellation method, and the channel estimation with the proposed preamble could obtain good performance both in single antenna and MIMO systems.

Low Complexity Pilot Allocation Scheme for a Large OFDM Block with Null Subcarriers

A low complexity pilot allocation scheme is proposed for a large OFDM block with null subcarriers. The proposed scheme allocates pilots to the edge part of the active subcarrier region according to the 2nd order polynomial and to the middle part of the active subcarrier region according to the 1st order polynomial or the comb‐type pilot pattern. To find a parameter of the 2nd order polynomial, the proposed scheme applies exhaustive search of a single parameter by using an integer unit resolution. It is shown by simulation that the proposed scheme is a close‐to‐optimal pilot allocation scheme yielding better symbol error rate (SER) performance than the traditional 3rd and 5th order polynomial‐based schemes although the proposed scheme has lower computation and implementation complexity.

Channel estimation in ACO-OFDM employing different transforms for VLC

The pronounced eminency of assuring simultaneous illumination and communication has driven Visible Light Communication (VLC) to gain significant ubiquity in recent times. This paper proposes comb type pilot arrangement based channel estimation for Asymmetrically Clipped Optical OFDM (ACO-OFDM) and different multicarrier transmission systems like Discrete Hartley Transform (DHT)-based ACO-OFDM and Fast-Walsh Hadamard transform (FWHT)-based Hadamard Coded Modulation (HCM) over dispersive VLC channel. Various channel estimation algorithms like Least Square (LS), Minimum Mean Square Error (MMSE), and Interpolation techniques namely Linear, Spline, and Low-Pass are evaluated and compared for the aforesaid systems employing different orders of constellation. Here, an elaborate mathematical analysis is accomplished and Cramer Rao Lower Bound (CRLB) is derived for the channel estimation error. Simulated results emphasize that, ACO-OFDM and DHT-based ACO-OFDM have improved Bit Error Rate (BER) performance than HCM at lower Signal to Noise Ratio (SNR), while at higher SNRs HCM dominates the former. Furthermore, the simulated results evidences that, in all multicarrier systems MMSE algorithm has reducible probability of error than LS because, at higher SNRs LS is more susceptible to noise and Spline Interpolation outperforms both LS and MMSE. The simulated results are validated analytically demonstrating good agreement.