高速移動單輸入單輸出/多輸入多輸出正交分頻多工系統的子載波間干擾消除:低複雜度演算法及效能分析

OFDM(Orthogonal Frequency Division Multiplexing) 시스템에서 직교 불균형 문제는 송수신기의 front-end에서 발생하며, 성상도에 영향을 주게 되어 BER(Bit Error Rate)을 증가시킨다. 또한, 위상 잡음은 송수신시 국부 발진기에서 발생되는 잡음으로 각 부반송파의 직교성을 깨뜨림으로써 시스템 성능을 크게 저하시킨다. 기존 방식인 PNS(Phase Noise Suppression) 알고리즘은 이러한 위상 잡음을 효과적으로 제거하는 방법이지만 직교 불균형 이동시에 적용되면 오히려 성능이 감소된다. 본 논문에서는 OFDM 시스템의 수신기에서 하향 변환 시 발생하는 직교 불균형과 위상 잡음의 영향을 분석하고, 수신기 FFT(Fast Fourier Transform) 후단에서 파일럿 심볼을 사용하여 CPE를 먼저 제거하고 직교 불균형과 위상 잡음의 성분을 검출하여 등화기의 판정 기준으로 사용하여 보상하는 방법을 제시하였다. 또, 다른 기존 방식들은 FFT 후단에서 추정하고 피드백 시키거나 프리엠블과 같은 시퀀스를 사용하는 방식이지만, 본 논문에서는 FFT 후단에서 MMSE 등화기만을 사용하여 제거하므로 기존의 방법보다 복잡도가 줄어든다. 기존의 위상 잡음 제거 방식에 ICI(Inter Carrier Interference) 제거 기능을 추가하고 직교 불균형 성분을 추출하여 MMSE(Minimum Mean Square Error) 과정 중에 적응 forgetting factor를 적용하면 성능 개선과 직교 불균형 성분의 영향이 줄어들며 성능이 개선됨을 보인다. In the OFDM system, IQ imbalance problem happens at the RF front-end of transceiver, which degrades the BER(bit error rate) performance because it affects the constellation in the received signal. Also, phase noise is generated in the local oscillator of transceivers and it destroys the orthogonality between the subcarriers. Conventional PNS algorithm is effective for phase noise suppression, but it is not useful anymore when there are jointly IQ(In-phase and Quadrature) imbalance and phase noise. Therefore, in this paper, we analyze the effect of IQ imbalance and phase noise generated in the down-conversion of the receiver. Then, we estimate and compensate the IQ imbalance and phase noise at the same time. Compared with the conventional method that IQ imbalance after IFFT is estimated and compensated in front of FFT via the feedback, this proposed method extracts and compensates effect of IQ imbalance after FFT stage. In case IQ imbalance and phase noise exist at the same time, we can decrease complexity because it is needless to use elimination of IQ imbalance in time domain and training sequences and preambles. Also, this method shows that it reduces the ICI and CPE component using adaptive forgetting factor of MMSE after FFT.

In this paper, we derive the achievable rate of single-carrier frequency domain equalizer (SC-FDE) and orthogonal frequency division multiplexing (OFDM) systems, constrained on low resolution analog to digital converters (ADCs). We assume that there is a full knowledge of channels at both transmitter and receiver sides. We model low resolution ADCs with an additive uniform quantization noise. We consider an ultra-wide band millimeter wave (mm-Wave) system with a frequency selective channel. The channel is based on practical results at mm-Wave frequencies. Our numerical results show that SC-FDE systems with minimum mean square error (MMSE) equalizers outperform OFDM and SC-FDE systems with zero forcing (ZF) equalizers at high signal to noise ratio (SNR) regimes. Moreover, benefits of increasing the ADCs resolution are not significant due to exponentially increment in the power consumption of ADCs.

Signal detection is crucial in multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) systems, yet classical detection methods often struggle with nonlinear issues in wireless channels. To handle this challenge, we propose a novel signal detection method for MIMO-OFDM system based on the fractional Fourier transform (FrFT), leveraging the robust time series processing capabilities of long short-term memory (LSTM) networks. Our innovative approach, termed IM-LSTMNet, integrates LSTM with convolutional neural networks (CNNs) and incorporates a Squeeze and Excitation Network to emphasize critical information, enhancing neural network performance. The proposed IM-LSTMNet is applied to the FrFT-based MIMO-OFDM system to improve signal detection performance. We compare the detection results of IM-LSTMNet with zero forcing (ZF), minimum mean square error (MMSE), simple LSTM neural network, and CNN–LSTM network by evaluating the bit error rate. Experimental results demonstrate that IM-LSTMNet outperforms ZF, MMSE, LSTM, and other methods, significantly enhancing system signal detection performance. This work offers a promising advancement in MIMO-OFDM signal detection, presenting a deep learning-based solution that effectively improves the system signal detection performance.

It is well known that Orthogonal Frequency Division Multiplexing (OFDM) systems suffer from intercarrier interference (ICI) in mobile environment due to loss of orthogonality among subcarriers caused by Doppler shifts. There exist many ICI mitigation techniques in the literature to improve the performance of OFDM systems. However, most of the existing ICI mitigation techniques assume the OFDM transmission bandwidth is narrow enough that the frequency offsets on all subcarriers are identical. In a wideband OFDM transmission or a non-contiguous OFDM spanning over large bandwidth, the Doppler shifts on different subcarriers are different, especially in high speed aerial vehicle communication systems. In this paper, we analyze the wideband OFDM system in high mobility environment where the frequency offsets vary from subcarrier to subcarrier. We then propose a novel ICI cancellation scheme to eliminate the ICI effect and offer the wideband OFDM system significantly improved BER performance. Simulation results in AWGN channel and multipath fading channel confirm the effectiveness of the proposed scheme in the presence of frequency offset and time variations in the channel, offering the best BER performance available which matches the BER performance of wideband OFDM system without ICI. To our knowledge, this paper is the first to address the ICI problem of varying frequency offsets across subcarriers in wideband OFDM system.

Orthogonal frequency division multiplexing (OFDM) systems may experience significant intercarrier interference (ICI) when used in time- and frequency-selective, or doubly-selective, channels. In such cases, the classical symbol estimation schemes, e.g., minimum mean-squared error (MMSE) and zero-forcing (ZF) estimation, require matrix inversion that is prohibitively complex for large symbol lengths. An analysis of the ICI generation mechanism leads us to propose a novel two-stage equalizer whose complexity (apart from the FFT) is linear in the OFDM symbol length. The first stage applies optimal linear preprocessing to restrict ICI support and the second stage uses iterative MMSE estimation to estimate finite-alphabet frequency-domain symbols. Simulation results indicate that our equalizer has significant performance and complexity advantages over the classical linear MMSE estimator in doubly-selective channels.

In comparison to Orthogonal Frequency Division Multiplexing (OFDM), Wavelet Packet Modulation (WPM) offers much lower side lobes in transmitted signal, which reduces inter-carrier interference (ICI) and narrowband interference (NBI). It is also spectrally efficient since it does not utilize cyclic prefix (CP), nevertheless, it requires an efficient equalization technique to counter the inter symbol interference (ISI) and ICI created by the channel. In this paper, performance comparison of OFDM and WPM for several multipath wireless channels is presented. We propose a novel application of zero-forcing (ZF) and minimum mean square error (MMSE) algorithms as time-domain channel equalization techniques for WPM systems. It is shown that, for a multipath wireless channel, WPM using MMSE-equalizer has a better bit error rate (BER) performance as compared to ZF-equalizer in WPM, as well as OFDM system.

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.

Orthogonal frequency division multiplexing (OFDM) systems work well if the subcarriers are orthogonal to each other. However, the orthogonality among subcarriers may not exist and result in inter-carrier interference (ICI) at the receiver. This may cause by residual carrier frequency offset, time variations due to Doppler shift or phase noise. Further developing the parallel cancellation (PC) scheme to mitigate the ICI of OFDM systems, we expand this OFDM symbol-based PC scheme into a space-frequency (SF) coded system. This new simple space- frequency parallel cancellation (SFPC) scheme is a technique that combines the SF and PC schemes together. Computer simulations indicate that OFDM systems using the SFPC scheme outperform the regular PC and SF systems in slow and fast frequency selective fading channels, specifically at a high signal-noise-ratio (SNR). Furthermore, the error floor of the SFPC-OFDM system is significantly lower than that of the PC and SF systems without increasing computational load. Additionally, the SFPC scheme is a simple multiple input and multiple output (MIMO) system.

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.

Severe time-dispersion of the channel is one of the limiting factors for high data rate acoustic communications in shallow water. To overcome the large time spread, the research community has devoted enormous effort in the design of high efficient, low complexity equalizers. The goal of these equalizers is to convert the time-dispersive channel into a unit-tap impulse function. In another research direction, code division multiple access (CDMA) and orthogonal frequency division multiplexing (OFDM) systems are designed to combat the multi-path effect. However, using OFDM or CDMA alone to combat the multi-path effect often forces system designers to reduce the data rate in such severe time-dispersive channels. In this paper, we propose to adopt a class of generalized equalizers to generate an effective channel with a desired length. These equalizers are referred to as channel-shortening equalizers. Then, other advanced modulation schemes, such as OFDM and CDMA, can be employed to overcome the remaining time-dispersion of the channel. Compared to the unit-tap equalization, channel-shortening equalizers can provide quality performance at low computation cost. Examples of current channel-shortening equalizers are based on minimum mean-squared error (MMSE) and maximum shortening signal-to-noise ratio (MSSNR) criteria. In this paper, these algorithms are compared in the context of underwater acoustic communications. Their performance, complexity, and implementation in acoustic communications are investigated. In the digital subscriber line (DSL) channel, where channel-shortening equalizers are often applied to, MSSNR algorithms perform better than MMSE algorithms. However, we show that the MMSE algorithm is more suitable for the underwater acoustic channels with lower complexity and robustness to noise. With the MMSE method, a channel-shortening equalizer with 20 taps can convert a typical 120-tap acoustic channel into a 33-tap shortened channel. Using data obtained from the Kauai experiment, June-July 2003, it shows that the mean of the effective signal-to-interference ratio (SIR) achieves 15.7 dB. For the same channel, the optimum unit-tap equalization needs more than 200 taps to achieve the same effective SIR

The nonlinearity of high power amplifiers (HPAs) exhibits amplitude and phase distortions, which cause loss of orthogonality among the subcarriers in orthogonal frequency division multiplexing (OFDM) systems, and hence, inter-carrier interference (ICI) is introduced in the transmitted signal. The ICI power is proportional to the amplitude of the signal at the amplifier input and it may cause a considerable bit error rate (BER) degradation. Due to the ICI is a random process and has unknown distribution function, it is difficult to evaluate the theoretical BER when the ICI is taken into account. This paper evaluates the BER analytically using sequence development approach (SDA) for OFDM systems perturbed by the HPA. In comparison to the state-of-the-art technique, the evaluation of the BER using this approach achieves superior approximation at the expense of additional computational complexity.

A bstract—To overcome the inter-carrier interference (ICI) of orthogonal frequency division multiplexing (OFDM) systems due to the carrier frequency offset (CFO), an ICA-based carrier synchronization method is proposed. Independent component analysis (ICA) is also known as blind source separation (BSS), which depends on the independence of source signals to separate or extract latent signals of interest. In this paper, we build an analogous ICA model for OFDM systems with the CFO. By virtue of this model, the ICA technique can be utilized to compensate corresponding loss of performance due to imperfect CFO estimation in the conventional method. Theoretical analysis shows that the ICA-based carrier synchronization method not only has maximum likelihood (ML) source recovery ability, but also can improve signal to noise ratio (SNR) of OFDM systems. Simulation results demonstrate the validity of the proposed method.

OFDM (orthogonal frequency division multiplexing) systems are very sensitive to carrier frequency offset. Although frequency offset is generally compensated for by an automatic frequency control (AFC), residual frequency offset remains after the AFC. Moreover, OFDM signals are also affected by phase noise. Thus, a kind of phase tracking is needed to compensate for these effects. In an OFDM system such as IEEE 802.11a, a phase tracking scheme that uses pilot subcarriers to detect the phase rotation caused by residual frequency offset and phase noise is employed. However, the spectrum of the AFC output signal is shifted by residual frequency offset. That is, the detected phase is the composite phase of the pilot subcarrier and the adjacent subcarrier because of inter-carrier interference (ICI). The compensation based on the composite phase sometimes overcorrects or undercorrects the phase rotation. In this paper, we propose a phase tracking scheme using iterative estimation of residual frequency offset in OFDM systems. The proposed phase tracking scheme estimates residual frequency offset in the frequency domain, and compensates for it in the time domain. The compensation in the time domain mitigates the spectrum shift of the AFC output. Therefore, the proposed scheme can reduce ICI, and track phases more accurately than the conventional phase tracking scheme.

Orthogonal frequency division multiplexing (OFDM) system is robust against inter-symbol interference (ISI) by increasing the symbol duration. However, for high-speed application, time variation of a multipath channel result in inter-carrier interference (ICI). It leads to the performance degradation. This works propose a low-complexity successive detection algorithm combined with the techniques of Newton's iterative matrix inversion method and successive detection method according to signal to noise ratio (SNR) in OFDM system. With the assumption of linearly varying channel impulse responses under fast fading conditions, the proposed algorithm reduces the complexity from O(N <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> ) of conventional zero-forcing algorithm to O(N <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ) , meantime it mitigates the noise enhancement problem. In all, it surpasses the performance bound of zero-forcing (ZF) equalization.

The paper proposes a new iterative method to estimate the carrier frequency offset (CFO) with scattered pilot symbols inserted for channel estimation in orthogonal frequency division multiplexing (OFDM) systems. Assuming that the channel remains constant during a few consecutive OFDM blocks, the new method uses the correlations of the pilot symbols in these consecutive OFDM blocks. And an iterative concept is also employed to reduce the inter-carrier interference (ICI) that deteriorates the CFO estimation performance. After a few iterations, the proposed method can achieve the accuracy with no ICI. The mean square error (MSE) of the new method is analyzed and simulation results show the new method outperforms existing methods.