SUBSPACE METHOD FOR BLIND IDENTIFICATION OF CDMA TIME-VARYING CHANNELS

A new blind method is proposed for identification of CDMA Time-Varying (TV)channels in this paper. By representing the TV channel's impulse responses in the delay-Doppler spread domain, the discrete-time canonical model of CDMA-TV systems is developed and a subspace method to identify blindly the Time-Invariant (TI) coordinates is proposed. Unlike existing basis expansion methods, this new algorithm does not require .estimation of the base frequencies, neither need the assumption of linearly varying delays across symbols. The algorithm offers definite explanation of the expansion coordinates. Simulation demonstrates the effectiveness of the algorithm.

Adversarial Training-Aided Time-Varying Channel Prediction for TDD/FDD Systems

In this paper, a time-varying channel prediction method based on conditional generative adversarial network(CPcGAN) is proposed for time division duplexing/frequency division duplexing(TDD/FDD) systems. CPc GAN utilizes a discriminator to calculate the divergence between the predicted downlink channel state information(CSI) and the real sample distributions under a conditional constraint that is previous uplink CSI. The generator of CPcGAN learns the function relationship between the conditional constraint and the predicted downlink CSI and reduces the divergence between predicted CSI and real CSI.The capability of CPcGAN fitting data distribution can capture the time-varying and multipath characteristics of the channel well. Considering the propagation characteristics of real channel, we further develop a channel prediction error indicator to determine whether the generator reaches the best state. Simulations show that the CPcGAN can obtain higher prediction accuracy and lower system bit error rate than the existing methods under the same user speeds.

Robust Beamforming Under Channel Prediction Errors for Time-Varying MIMO System

The accuracy of acquired channel state information(CSI)for beamforming design is essential for achievable performance in multiple-input multiple-output(MIMO)systems.However,in a high-speed moving scene with time-division duplex(TDD)mode,the acquired CSI depending on the channel reciprocity is inevitably outdated,leading to outdated beamforming design and then performance degradation.In this paper,a robust beamforming design under channel prediction errors is proposed for a time-varying MIMO system to combat the degradation further,based on the channel prediction technique.Specifically,the statistical characteristics of historical channel prediction errors are exploited and modeled.Moreover,to deal with random error terms,deterministic equivalents are adopted to further explore potential beamforming gain through the statistical information and ultimately derive the robust design aiming at maximizing weighted sum-rate performance.Simulation results show that the proposed beamforming design can maintain outperformance during the downlink transmission time even when channels vary fast,compared with the traditional beamforming design.

Neural Network and GBSM Based Time-Varying and Stochastic Channel Modeling for 5G Millimeter Wave Communications

In this work,a frame work for time-varying channel modeling and simulation is proposed by using neural network(NN)to overcome the shortcomings in geometry based stochastic model(GBSM)and simulation approach.Two NN models are developed for modeling of path loss together with shadow fading(SF)and joint small scale channel parameters.The NN models can predict path loss plus SF and small scale channel parameters accurately compared with measurement at 26 GHz performed in an outdoor microcell.The time-varying path loss and small scale channel parameters generated by the NN models are proposed to replace the empirical path loss and channel parameter random numbers in GBSM-based framework to playback the measured channel and match with its environment.Moreover,the sparse feature of clusters,delay and angular spread,channel capacity are investigated by a virtual array measurement at 28 GHz in a large waiting hall.

Antenna calibration using channel prediction for time-varying channels

Traditional antenna calibration methods for time division duplex （TDD） systems asSume that the flee-space channel remains the same during calibration, which is unreasonable under the high-speed rail and other time-varying channel scenarios, and will cause calibration error due to time variability. This paper proposes an antenna calibration method for time-varying channels. In the proposed method, the transceiver first sequentially sends a pilot signal to ob- tain equivalent do^vnlink and uplink channel responses. Then, by predicting the downlink （uplink） channel response fed back from the receiver using the channel prediction algorithm, the transmitter obtains the channel response correspond- ing to the channel response on uplink （downlink）. Finally, the transmitter calculates the transmission calibration factor through the prediction value. Compared with the traditional antenna calibration method, this method can improve the accuracy of the calibration factor. Simulation results show that the performance degradation of antenna calibration can be caused by time-varying channels and the proposed method can well compensate for the performance loss and sig- nificantly improve the antenna calibration performance for time-varying channels.

Deep learning-based time-varying channel estimation with basis expansion model for MIMO-OFDM system

For high-speed mobile MIMO-OFDM system,a low-complexity deep learning(DL) based timevarying channel estimation scheme is proposed.To reduce the number of estimated parameters,the basis expansion model(BEM) is employed to model the time-varying channel,which converts the channel estimation into the estimation of the basis coefficient.Specifically,the initial basis coefficients are firstly used to train the neural network in an offline manner,and then the high-precision channel estimation can be obtained by small number of inputs.Moreover,the linear minimum mean square error(LMMSE) estimated channel is considered for the loss function in training phase,which makes the proposed method more practical.Simulation results show that the proposed method has a better performance and lower computational complexity compared with the available schemes,and it is robust to the fast time-varying channel in the high-speed mobile scenarios.

Pilot Placement for Time-Varying MIMO OFDM Channels with Virtual Subcarriers

The rapid time-variation of a fading multipath environment can impair the performance of multiple-input multiple-output orthogonal frequency division multiplexing (MIMO OFDM). This paper proposes a pilot placement method for MIMO OFDM systems under time-varying channels with the guard band. The time-varying channel is described by complex exponential basis expansion model (BEM). We discuss the least square (LS) channel estimation to obtain the minimum mean square error (MSE) and derive the pilot allocation that can satisfy the minimum MSE with regard to guard band in time-varying channels. It is shown that optimal pilot clusters can distribute non-uniformly in frequency domain and minimize the MSE. We generalize our scheme over G OFDM symbols and compare it with comb pilots. It is demonstrated that the proposed approach is more effective than previous work. Simulation results validate our theoretical analysis.

Multiple Vandermonde Decomposition Based Channel Estimation for Mm Wave MIMO High-Mobility Communication in 5G and Beyond

Millimeter wave(mmWave)massive massive multiple input multiple output(MIMO)technique has been regarded as the viable solution for vehicular communications in 5G and beyond.To achieve the substantial increase in date rates,it is important to take an effective channel state information(CSI).However,existing channel estimation strategies are unavailable since the users high-mobility.To solve above issues,in this paper,inspired by a specific antenna structure,we propose a novel approach for fast time-varying channel estimation.Specifically,by considering the vehicle scenario with high-mobility,a corresponding mathematical model is firstly established.Then,based on the special structural of the sparse array,the switch network is used to replace the convention phase shifter of mmWave hybrid system,which can effectively reduce the number of radio-frequency(RF)chains and antennas.Furthermore,by solving the semidefinite programming(SDP)duality problem,the Doppler frequency and path parameters are effectively estimated.Simulation results are shown that the computational complexity and estimation accuracy of the proposed algorithm is superior than that of the traditional schemes.

Fragmental Weight-Conservation Combining Scheme for Statistical Signal Transmissions under Fast Time-Varying Channels

Statistical Signal Transmission(SST)is a technique based on orthogonal frequency-division multiplexing(OFDM)and adopts cyclostationary features,which can transmit extra information without additional bandwidth.However,the more complicated environment in 5G communication systems,especially the fast time-varying scenarios,will dramatically degrade the performance of the SST.In this paper,we propose a fragmental weight-conservation combining(FWCC)scheme for SST,to overcome its performance degradation under fast time-varying channels.The proposed FWCC scheme consists of three phases:1、incise the received OFDM stream into pieces;2、endue different weights for fine and contaminated pieces,respectively;3、combine cyclic autocorrelation function energies of all the pieces;and 4、compute the final feature and demodulate data of SST.Through these procedures above,the detection accuracy of SST will be theoretically refined under fast time-varying channels.Such an inference is confirmed through numerical results in this paper.It is demonstrated that the BER performance of proposed scheme outperforms that of the original scheme both in ideal channel estimation conditions and in imperfect channel estimation conditions.In addition,we also find the experiential optimal weight distribution strategy for the proposed FWCC scheme,which facilitates practical applications.

CHANNEL ESTIMATION OF MULTI-RATE DS-CDMA SIGNALS IN SLOW FADING MULTIPATH CHANNELS

In Direct-Sequence Code Division Multiple Access(DS-CDMA) mobile communi-cation systems, it is very important to obtain accurate estimation of the channel parameters,especially that of the propagation delay. But the near-far problem may make the estimationcomplicated and can degrade the estimation performance significantly. In this paper, an efficientMaximum Likelihood (ML) method is presented for channel parameter estimation of multi-rateDS-CDMA systems in slow fading multipath channels in a near-far scenario. The algorithmextended the ML approach to multi-rate DS-CDMA systems, and proposes decomposing a multi-dimensional optimization problem into a series of one-dimensional optimization and has improvedcomputational efficiency. Theoretical analysis and numerical examples show that the estimatorproposed is effective and near-far resistant.

Sparse Recovery of Linear Time-Varying Channel in OFDM System

In order to improve the performance of linear time-varying（LTV）channel estimation,based on the sparsity of channel taps in time domain,a sparse recovery method of LTV channel in orthogonal frequency division multiplexing（OFDM）system is proposed.Firstly,based on the compressive sensing theory,the average of the channel taps over one symbol duration in the LTV channel model is estimated.Secondly,in order to deal with the inter-carrier interference（ICI）,the group-pilot design criterion is used based on the minimization of mutual coherence of the measurement.Finally,an efficient pilot pattern optimization algorithm is proposed by a dual layer loops iteration.The simulation results show that the new method uses less pilots,has a smaller bit error ratio（BER）,and greater ability to deal with Doppler frequency shift than the traditional method does.

Methods to Improve the Long Distance Time-Varying Channel Transmission Performance of Expendable Profiler

To improve the transmission performance of XCTD channel, this paper proposes a method to measure directly and fit the channel transmission characteristics by using frequency sweeping method. Sinusoidal signals with a frequency range of 100 Hz to 10 k Hz and an interval of 100 Hz are used to measure transmission characteristics of channels with lengths of 300 m, 800 m, 1300 m, and 1800 m. The correctness of the fitted channel characteristics by transmitting square wave, composite waves of different frequencies, and ASK modulation are verified. The results show that when the frequency of the signal is below 1500 Hz, the channel has very little effect on the signal. The signal compensated for amplitude and phase at the receiver is not as good as the uncompensated signal.Alternatively, when the signal frequency is above 1500 Hz, the channel distorts the signal. The quality of signal compensated for amplitude and phase at receiver is better than that of the uncompensated signal. Thus, we can select the appropriate frequency for XCTD system and the appropriate way to process the received signals. Signals below1500 Hz can be directly used at the receiving end. Signals above 1500 Hz are used after amplitude and phase compensation at the receiving end.

TRAFFIC CHANNEL SIR ESTIMATION BASED ON REVERSE PILOT CHANNEL IN cdma2000

Signal-to-Interference Ratio(SIR) is a very important metric of communication link quality. For wireless cellular systems, several control mechanisms, such as power control mechanisms, rate control mechanisms, and allocation of radio resource, are based on SIR estimation.In previous researches, most of researchers concentrated on WCDMA systems, in which pilot symbol is time-multiplexed with data symbol; the method developed in this case is not feasible for cdma2000 systems where pilot symbol is code-multiplexed with data symbol. This paper first develops the SIR estimators based on the reverse pilot channel and then derives the approximate analytic expression for its Mean Squared Error (MSE) function, the accuracy of which is validated through simulation. It is shown that the MSE of the new SIR estimator is significantly smaller than that of other widely used SIR estimators, especially in low SIR case. Finally, the estimate quality of the proposed method is further improved by long-termly averaging the sample interference.

A MATCHED FILTER BANK BASED DOA ESTIMATION FOR ASYNCHRONOUS MULTIPATH CDMA CHANNELS

In this paper, a Direction Of Arrival (DOA) estimation algorithm is proposed for multiuser signals through uplink asynchronous multipath Code Division Multiple Access (CDMA) channels. The algorithm is based directly on the correlation matrices of matched filter bank outputs of desired user’s multipath signals and it does not require that the elements of base station antenna array outnumber the multipath signals, which is necessary for the conventional sub-space based direction-finding algorithm. Simulation results show that the proposed algorithm estimates the DOA of multipath signals effectively and acceptably. The proposed algorithm has the prominent advantages of low complexity, simpleness and practicality, which make it much more suitable for practical application.

Performance of MC-CDMA Systems with Orthogonal Transmit Diversity over Rayleigh Fading Channel

Transmit diversity has been recently proposed to reduce the effects of fading channels in various wireless applications. Orthogonal transmit diersity (OTD) is one of the standardized techniques in 3G systems. In this paper, we apply orthogonal transmit diversity technique to multicarrier CDMA systems. Andlysis and simulation results show that performance benefits can be achieved compared with conventioal MC-CDMA systems in multipath fading channels.

Channel Estimation for Powerline MC-CDMA System

Successful development of broadband over powerline is obviously a potential solution for wired communication systems with the existence of the powerline network. From past research, it is known that the powerline channel suffers from multipath fading, frequency selectivity and also impulsive noise. Multi Carrier Code Division Multiple Access (MC-CDMA) is a promising solution for an impulsive noise powerline channel. This paper starts with the MC-CDMA transmitter structure and focuses on powerline channel model, noise model and various types of available channel estimators. The main concern in Powerline Communication Systems is the existence of impulsive noise. The proposed pilot assisted channel estimation uses the modified least square estimator that reduces the effect of impulsive noise in the estimated channel impulse response.

A Receiver Structure for Frequency-Flat Time-Varying Rayleigh Channels and Performance Analysis

This paper proposes a wavelet based receiver structure for frequency-flat time-varying Rayleigh channels, consisting of a receiver front-end followed by a Maximum A-Posteriori (MAP) detector. Discretization of the received continuous time signal using filter banks is an essential stage in the front-end part, where the Fast Haar Transform (FHT) is used to reduce complexity. Analysis of our receiver over slow-fading channels shows that it is optimal for certain modulation schemes. By comparison with literature, it is shown that over such channels our receiver can achieve optimal performance for Time-Orthogonal modulation. Computed and Monte-Carlo simulated performance results over fast time-varying Rayleigh fading channels show that with Minimum Shift Keying (MSK), our receiver using four basis functions (filters) lowers the error floor by more than one order of magnitude with respect to other techniques of comparable complexity. Orthogonal Frequency Shift Keying (FSK) can achieve the same performance as Time-Orthogonal modulation for the slow-fading case, but suffers some degradation over fast-fading channels where it exhibits an error floor. Compared to MSK, however, Orthogonal FSK provides better performance.

正交序列扩频多码CDMA系统在AWGN信道的性能分析

在直接序列扩频通信（ＤＳ－ＣＤＭＡ）系统中，为了有效地实现用户高数据率的传输，本文提出了一种正交扩频多码ＣＤＭＡ系统（称为ＯＭＣ－ＣＤＭＡ）。相似于多载波调制，传输的高数据率首先进行串－并转换，然后对转换后的低数据流用正交序列进行扩频调制。不同于多载波调制，各支路扩频信号用同一载波进行调制。这里，我们对此系统在ＡＷＧＮ信道的性能进行了计算，并对数值结果进行了分析。

利用边信息嵌入的CDMA水印信道性能研究

稳健性是数字水印的重要指标之一.为了改善水印稳健性,CDMA技术已被引入到数字水印中.但是,目前基于CDMA扩频技术的水印算法基本都是通过实验方式来确定嵌入强度以及相关参数.本文分析了把载体作为边信息情况下CDMA水印信道的性能.研究了PSNR值,嵌入强度参数β,正交码码长N以及用户数K之间的关系,给出了PSNR关于这三者的显式表达式.根据PSNR值,给出了水印嵌入强度参数β的估计算法,仿真实验结果表明估计的有效性.并指出CDMA水印信道中,用户数不影响PSNR值的大小,实验结果有力地支持了这个结论.通过分析CDMA水印信道的误码形成过程,给出了信道误码率表达式,并得出,在给定PSNR值的情况下,CDMA正交扩频码码长N的选择不影响信道误码率值.

WPDM-CDMA系统中的LS与MMSE信道估计算法仿真分析

针对无线衰落信道工作下的WPDM-CDMA(小波包变换多载波码分多址)系统特点建立系统仿真模型。探讨在WPDM-CDMA系统中的信道估计问题。分析了2种常见信道估计方法:最小平方误差(LS)和最小均方误差(MMSE)信道估计算法。在Matlab环境下编写相关信道估计算法程序,通过仿真分析比较两种算法的均方差和误码率。结果表明:性能上MMSE算法远优于LS算法,但MMSE算法的运算量比LS算法大很多。