Adversarial Training for Jamming-robust Channel Estimation in OFDM Systems

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.

This paper deals with channel estimation for orthogonal frequency-division multiplexing (OFDM) systems with transmit diversity. Space time coded OFDM systems, which can provide transmit diversity, require perfect channel estimation to improve communication quality. In actual OFDM systems, training sequences are usually used for channel estimation. The authors propose a training based channel estimation strategy suitable for space time coded OFDM systems. This novel strategy provides enhanced performance, high spectrum efficiency and relatively low computation complexity.

Multi carrier modulation is Orthogonal Frequency Division Multiplexing (OFDM), dividing the large band spectrum into small (narrow) band spectrum.OFDM offers flexibility in adaptation to time varying channel condition by adopting the parameters at each subcarrier accurately.Due to the multipath effect the OFDM system suffers Inter Symbol Interference (ISI).ISI can be reduced by introducing the guard band (cyclic prefix).Time-varying channel estimation is an important activity in next generation wireless communication.Channel estimation is required mainly for the significant signal processing operation in multiple input multiple output MIMO-OFDM systems.In this project DFT -based channel estimation based on block type arrangement is implemented in MAT Lab.The bit error rate (BER) of DFT (Discrete Fourier Transform)based channel estimation is less than the BER of LS (Least Square) and MMSE (Minimum Mean Square Error) based channel estimation with same signal to noise ratio (SNR).

ABSTRACTWhile inter-symbol interference is not of concern, inter-carrier interference that is caused by carrier frequency offset (CFO) is more concerned in orthogonal frequency division multiplexing (OFDM) systems. The estimation of channel impulse response (CIR) is another important parameter of interest in the system. Recently, a number of approaches for the joint estimation of CFO and CIR in OFDM systems have been proposed in the literature, and most of them are traditional maximum-likelihood-based approaches. In this paper, we propose a number of mixture cost-reference particle filtering (CRPF) approaches for joint estimation of CIR and CFO, and a couple of them can be applied without the knowledge of both state and measurement noise statistics. Conventional least mean squares algorithm or recursive least squares algorithm is jointly employed with recently developed CRPF for nonlinear and multiple parameters estimation in OFDM systems. The computer simulation results show that mixture CRPFs are more robust against particle impoverishment (PI) problem than standard mixture particle filtering (PF) and mixture regularized PF (RPF) approaches although RPF was particularly developed to tackle the PI problem. In this paper, we investigate a number of mixture PF approaches including ones that do not need the information of noise statistics for the joint estimation of CFO and channel in OFDM systems.

Conventional time-division duplex (TDD) orthogonal frequency division multiplexing (TDD-OFDM) system is vulnerable to the pilot spoofing attack as it mainly relies on employing the deterministic pilot to capture the channel state information (CSI). To solve the abovementioned issue, we in this paper propose an independent component analysis (ICA) based channel identification and estimation (ICA-CIE) mechanism which uses randomized pilot to paralyze the pilot spoofing attack. Specifically, we first convert the pilot spoofing attack to the pilot jamming attack by exploiting pilot randomization. Then, an eigenstructure-based detector (EID) is proposed to realize efficient pilot jamming attack detection. In particular, on one hand, Least Square (LS) method is adopted if no jamming attack is detected. On the other hand, if jamming attack is detected, we further design a channelseparation oriented joint approximate diagonalization of eigenmatrices (CS-JADE) algorithm for channel estimation and identification. Therein, an optimization problem is first formulated to optimize the fourth-order statistical information of the observation data, after which a pilot signal reconstruction scheme is further developed to help identify true sub-channels from the optimization output. Simulation results demonstrate that our proposed ICA-CIE mechanism can achieve highly-accurate channel estimation for the legitimate transceiver pair only by using 6 OFDM symbols within the coherence time. Moreover, we also observe that the estimation accuracy of our proposed mechanism is immune to Eve's transmit power, which further verifies superiority of our proposed mechanism.

Channel estimation is a critical component in orthogonal frequency division multiplexing (OFDM) systems for ensuring reliable wireless communication. In this study, we propose a fast super-resolution convolutional neural network (FSRCNN) model for channel estimation, designed to reduce computational complexity while maintaining high estimation accuracy. The proposed FSRCNN model incorporates modifications such as replacing linear interpolation with zero padding and leveraging a new fast CNN architecture to estimate channel coefficients. Our numerical experiments and simulations demonstrate that the FSRCNN model significantly outperforms traditional methods, such as least square (LS) and linear minimum mean square error (LMMSE), in terms of mean square error (MSE) across various signal-to-noise ratios (SNRs). Specifically, the FSRCNN model achieves MSE values comparable to MMSE estimation, particularly at higher SNRs, while maintaining lower computational complexity. At an SNR of 20 dB, the FSRCNN model shows a notable improvement in MSE performance compared to the ChannelNet and LS methods. The proposed model also demonstrates robust performance across different SNR levels, with optimal results observed when the training SNR is close to the operating SNR. These findings validate the effectiveness of the FSRCNN model in providing a low-complexity, high-accuracy alternative for channel estimation, making it suitable for real-time applications and devices with limited computational resources. This advancement holds significant promise for enhancing the reliability and efficiency of current and future wireless communication networks.

A Krylov subspace based low-rank channel estimation in OFDM systems

This paper analyzes and compares two time interpolators, i.e., time replica and time linear interpolator, for pilot aided channel estimation in orthogonal frequency division multiplexing (OFDM) systems. The mean square error (MSE) of two interpolators is theoretically derived for the general case. The equally spaced pilot arrangement is proposed as a special platform for these two time interpolators. Based on this proposed platform, the MSE of two time interpolators at the virtual pilot tones is derived analytically; moreover, the MSE of per channel estimator at the entire OFDM symbol based on per time interpolator is also derived. The effectiveness of the theoretical analysis is demonstrated by numerical simulation in both the time-invariant frequency-selective channel and the time varying frequency-selective channel.

This work pertains to the use of superimposed training (ST) for channel estimation in orthogonal frequency division multiplexing (OFDM) based systems. A time domain coherent averaging based channel estimator is derived from the least squares criterion. By exploiting the periodicity of the training sequences in the time domain and inserting zeros instead of data at some of the training sequence subcarrier locations depending on the desired estimation accuracy, a controlled superimposition technique is proposed. This method includes the flexibility to trade off between bandwidth efficiency and performance. The mean squared estimation error (MSEE) performance of such a system is mathematically analyzed and a training sequence selection criterion optimizing the same is proposed. The simulation performance of the scheme is presented in terms of the MSEE and the bit error rate (BER) of the OFDM system. Such a scheme is attractive in high data rate scenarios in closed loop OFDM systems.

The Fourth generation (4G) wireless networks are expected to afford high data rate transmission of multimedia services such as wireless video, wireless Internet access and mobile computing. Orthogonal frequency division multiplexing (OFDM) is an effective technique for the future 4G communications because of its great immunity to impulse noise and intersymbol interference. Ultra wide band (UWB) wireless technology is poised to replace high-speed data cables in homes and offices. UWB technology will be capable of transmitting hundreds of megabits per second over distances of several meters. Channel estimation in OFDM systems can conveniently be done by inserting a stream of pilot symbols at the transmitter and by using FIR interpolation filters at the receiver. One of the challenges in wireless system is the frequency selective fading caused due to multipath channel between the transmitter and receiver. To overcome such a multipath fading environment with low complexity and to increase the performance, this paper presents an importance of UWB OFDM for wireless fading channels.

To improve the bandwidth efficiency, a semi-blind channel estimation method using data nulling superimposed pilots (DNSP) is designed for orthogonal frequency division multiplexing (OFDM) system without data rate loss. However, the data distortion is introduced by rank-deficient precoding. To minimize the data distortion, the optimal precoder is found to minimize the Euclidean distance between precoded sequence and source sequence. Further, the impact of power allocation between training sequence and data information on effective signal noise ratio (SNR) is analytically derived, effective SNR is found to be a quadratic function for the percentage allocated for training sequence, and the optimal power allocation is provided to maximize the effective SNR. Simulation results show that our optimal precoder design and power allocation scheme obtain the optimal performance of symbol detection.

A time-varying channel estimation method for orthogonal frequency division multiplexing (OFDM) systems is presented. The proposed method makes use of two asymmetric pilot symbols to improve channel estimation performance and meanwhile obtain a reasonable pilot overhead. Complete simulations illustrate that the proposed method can have precise estimation result even under very large normalized Doppler frequency.

In orthogonal frequency division multiplexing (OFDM) systems, channel variations within an OFDM block destroy orthogonality between subcarriers, resulting in intercarrier interference (ICl), which increases an error floor in proportional to normalized Doppler frequency. To mitigate the effects of channel variations, many schemes have been proposed, but they are computationally complex or at the price of sacrificing spectral efficiency. In this paper, we first provide an ICI analysis in both time- and frequency-domain while existing literatures analyze the ICI effects mainly in the frequency domain. Based on this analysis, we then propose a novel ICI suppression technique, which uses iterative ICI cancellation in time domain and has a computational complexity that is linear in the OFDM symbol length. Channel estimation in rapidly time-varying scenarios is critical for ICl suppression and coherent demodulation. We also propose a scheme for estimating the channel parameters varying within an OFDM block. Along with the channel estimation scheme, we investigate the issue of optimum pilot tone placement. Theoretical analysis and simulation results show that the proposed ICl suppression method and channel estimation scheme have low computational complexity and good performance for most Doppler frequency of practical importance.

In this paper, an integrated Orthogonal Frequency Division Multiplexing (OFDM) system is developed to improve Bit Error Rate (BER) performance of communication systems in order to meet the requirements of advanced communication systems like long term evaluation advanced (LTE –A). The proposed OFDM system consists of channel estimation using comb type pilot arrangement and convolution encoder with the best known Coding Bounds and Maximum A Posteriori (MAP) decoder. Using pilot symbols, the channel quality is estimated. The BER performance of OFDM system is improved using pilot carriers, channel estimation schemes and MAP decoder at the best known coding bounds. The system performance is analyzed with recursive systematic and non-systematic convolution codes, ML and MAP decoders. From the results, it is evident that the proposed OFDM system with channel estimation and MAP decoder at the best known coding bounds improves the system performance significantly.

In the new generation wireless communication systems where high data rates are desired, orthogonal frequency division multiplexing (OFDM) has become the standard method because of its advantages over single carrier modulation schemes on multi-path, frequency selective fading channels. However, inter-carrier interference due to Doppler frequency shifts, and multi-path fading severely degrades the performance of OFDM systems. Estimation of channel parameters is required at the receiver. In this paper, we present a time-varying channel modeling and estimation method based on the discrete evolutionary transform that provides a time-frequency procedure to obtain a complete characterization of a multi-path, fading and frequency selective channel. Performance of the proposed method is tested on different levels of channel noise, and Doppler frequency shifts.