Compressed sensing based channel estimation used in non-sample-spaced multipath channels of OFDM system

By virtue of an increase in spectral efficiency by reducing the transmitted pilot tones, the compressed sensing （CS） has been widely applied to pilot-aided sparse channel estimation in orthogonal frequency division multiplexing （OFDM） systems. The researches usually assume that the channel is strictly sparse and formulate the channel estimation as a standard compressed sensing problem. However, such strictly sparse assumption does not hold true in non-sample-spaced multiple channels. The authors in this article proposed a new method of compressed sensing based channel estimation in which an over-complete dictionary with a finer delay grid is applied to construct a sparse representation of the non-sample-spaced multipath channels. With the proposed, the channel estimation was formulated as the model-based CS problem and a modified model-based compressed sampling matching pursuit （CoSaMP） algorithm was applied to reconstruct the discrete-time channel impulse response （CIR）. Simulation indicates that the new method proposed here outperforms the traditional standard CS-based methods in terms of mean square error （MSE） and bit error rate （BER）.

Physical-Layer Key Generation Based on Multipath Channel Diversity Using Dynamic Metasurface Antennas

Physical layer key generation(PKG)technology leverages the reciprocal channel randomness to generate the shared secret keys.The low secret key capacity of the existing PKG schemes is due to the reduction in degree-of-freedom from multipath fading channels to multipath combined channels.To improve the wireless key generation rate,we propose a multipath channel diversity-based PKG scheme.Assisted by dynamic metasurface antennas(DMA),a two-stage multipath channel parameter estimation algorithm is proposed to efficiently realize super-resolution multipath parameter estimation.The proposed algorithm first estimates the angle of arrival(AOA)based on the reconfigurable radiation pattern of DMA,and then utilizes the results to design the training beamforming and receive beamforming to improve the estimation accuracy of the path gain.After multipath separation and parameter estimation,multi-dimensional independent path gains are utilized for generating secret keys.Finally,we analyze the security and complexity of the proposed scheme and give an upper bound on the secret key capacity in the high signal-to-noise ratio(SNR)region.The simulation results demonstrate that the proposed scheme can greatly improve the secret key capacity compared with the existing schemes.

The influence of PRF on BER performance of THSS UWB radio systemwith PPM in dense multipath fading environments

The influence of pulse repetition frequency(PRF) on performance of wireless digital time hopping spread spectrum(THSS) ultrawide bandwidth(UWB) radio systems with PPM in dense multipath fading environments is firstly investigated. The receiver used in this UWB system is a hybrid selection/maximal-ratio combining(H-S/MRC) diversity receiver in which L strongest multipath components out of N multipath diversity branches are selected and combined using maximal-ratio combining. The exact expressions for the bit error rate(BER) of this UWB system are firstly derived by using the virtual branch technique in term of PRF, the number of multipath components selected and combined L, and multipath spread of the channel and then this BER performance is evaluated. With the computer simulation for impulses having different pulse shapes, numerical results show that PRF, as well as pulse shape and the number of multipath diversity branches selected and combined L, has much effect on the BER performance of this UWB system in dense multipath fading environments. As PRF increases, the BER performance of this UWB system is much degraded under the conditions of fixed L and pulse shape.

FIXED-POINT BLIND ADAPTIVE MULTIUSER DETECTION ALGORITHM FOR IR UWB SYSTEMS IN MULTIPATH CHANNEL

Using the hypothesis that data transmitted by different users are statistically independent of each other,this paper proposes a fixed-point blind adaptive multiuser detection algorithm for Time-Hopping (TH) Impulse Radio (IR) Ultra Wide Band (UWB) systems in multipath channel,which is based on Independent Component Analysis (ICA) idea. The proposed algorithm employs maximizing negentropy criterion to separate the data packets of different users. Then the user characteristic se-quences are utilized to identify the data packet order of the desired user. This algorithm only needs the desired user’s characteristic sequence instead of channel information,power information and time-hoping code of any user. Due to using hypothesis of statistical independence among users,the proposed algorithm has the outstanding Bit Error Rate (BER) performance and the excellent ability of near-far resistance. Simulation results demonstrate that this algorithm has the performance close to that of Maximum-Likelihood (ML) algorithm and is a suboptimum blind adaptive multiuser detection algorithm of excellent near-far resistance and low complexity.

EFFECT OF MULTIPATH CHANNEL MODELS TO THE RECOVERY ALGORITHMS ON COMPRESSED SENSING IN UWB CHANNEL ESTIMATION

Multipath arrivals in an Ultra-WideBand (UWB) channel have a long time intervals between clusters and rays where the signal takes on zero or negligible values. It is precisely the signal sparsity of the impulse response of the UWB channel that is exploited in this work aiming at UWB channel estimation based on Compressed Sensing (CS). However, these multipath arrivals mainly depend on the channel environments that generate different sparse levels (low-sparse or high-sparse) of the UWB channels. According to this basis, we have analyzed the two most basic recovery algorithms, one based on linear programming Basis Pursuit (BP), another using greedy method Orthogonal Matching Pursuit (OMP), and chosen the best recovery algorithm which are suitable to the sparse level for each type of channel environment. Besides, the results of this work is an open topic for further research aimed at creating a optimal algorithm specially for application of CS based UWB systems.

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.

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.

Adaptive Turbo Equalization for Probabilistic Constellation Shaped Underwater Acoustic Communications

To increase the spectral efficiency of the underwater acoustic(UWA)communication system,the high order quadrature amplitude modulations(QAM)are deployed.Recently,the prob-abilistic constellation shaping(PCS)has been a novel technology to improve the spectral efficiency.The PCS with high-order QAM is introduced into the UWA communication system.A turbo equal-ization scheme with PCS was proposed to cancel the severe inter-symbol interference(ISI).The non-zero a priori information is available for the equalizer and decoder before turbo iteration.A pri-ori hard decision approach is proposed to improve the detection performance and the equalizer con-vergence speed.At the initial turbo iteration,the relation between the a priori information and the probability of the amplitude of 16QAM symbols in one dimension is given.The simulation results verified the efficiency of the proposed method,and compared to the uniform distribution(UD),the PCS-16QAM had a significant improvement of the bit error rate(BER)performance with PCS-ad-aptive turbo equalization(PCS-ATEQ).The UWA communication experiments further verified the performance superiority of the proposed method.

Performance of Adaptive Subchannel Assignment-Based MIMO/OFDM Systems over Multipath Fading Channels

Adaptive antenna arrays at both the base and mobile stations can further increase system capacity and improve the quality of service of conventional orthogonal frequency division multiplexing （OFDM） systems. Conventional adaptive antenna array-based multiple-input multiple-output （MIMO）/OFDM systems use the sub-carriers characterized by the largest eigenvalue to transmit the OFDM symbols. This paper describes the performance of adaptive subchannel assignment-based MIMO/OFDM systems over multipath fading channels, The system adaptively selects the eigenvectors associated with the relatively large subchannel eigenvalues to generate the antenna array weights at the base and mobile stations and then adaptively assigns the corresponding best subchannels to transmit the OFDM symbols. Simulation results show that the proposed system can achieve better performance than the conventional adaptive antenna arraybased MIMO/OFDM system over multipath fading channels.

Underwater acoustic multipath sparse channel estimation via gridless relevance vector machine method

In the scenario of underwater acoustic sparse channel estimation with training sequences,grid points in the measuring matrix are caused by discretizing procedure.Estimated accuracy might not be guaranteed with the state-of-the-art methods when multipath delays don't exactly locate on the grid points.In this paper,we construct a gridless measuring matrix for sparse channel estimation which contains an off-grid adjusting factor.The Relevance Vector Machine(RVM) algorithm is employed to estimate this factor.The numerical experiments for two different underwater channels are performed to testify the newly proposed method.The results demonstrate that this method outperforms conventional ones in terms of estimating error and bit error rate,especially when the grid gets coarser.

BDS B1I multipath channel statistical model comparison between static and dynamic scenarios in dense urban canyon environment

Global Navigation Satellite System(GNSS)multipath channel models are fundamental and critical for signal simulation and receiver performance evaluation.They also aid the designing of suitable multipath error mitigation algorithms when the properties of multipath channel are available.However,there is insufficient existing research on BeiDou Navigation Satellite System(BDS)signal multipath channel models.In this study,multipath channel statistical models are established on the basis of extensive datasets of the BDS B1I signal.A multipath parameter estimation algorithm is designed to extract information of multipath rays from the intermediate frequency data.The delay,power loss,Doppler fading frequency,and lifetime distribution models for static and dynamic vehicle platforms are established and compared,and the effects of the satellite orbit type and platform speed on the models are analyzed.The results reveal the detailed distribution and variation characteristics of the multipath parameters and are valuable for the development of accurate urban navigation systems.

Blind Multipath Identification: A Weighted Linear Prediction Approach

Blind channel identification exploits the measurable channel output signaland some prior knowledge of the statistics of the channel input signal. However, in many scenarios,more side information is available, In digital communication systems, the pulse-shaping filter inthe transmitter and the anti-aliasing filter in the receiver are often known to the receiver.Exploitation of this prior knowledge can simplify the channel identification problem. In this paper,we pose the multipath identification problem as solving a group of linear equations. While we solvethe linear equations in the least-square meaning, a weight matrix can be introduced to improve theperformance of the estimator. The optimal weight matrix is derived. Compared with the existingLinear Prediction (UP) based multipath identification approach, the proposed approach offers asubstantial performance gain.

Propagation Properties of Radio Wave in Multipath Scattering Mobile Channel

Based on a physical model for the radio wave propagation in multipath scattering environments, this paper analyses and simulates the propagation properties as well as time-selective behavior of radio waves in different urban microcellular mobile radio channels. The approach of propagation properties causes a generation of complex impulse responses to be like that given by the statistics of the underlying channel behavior. Fading characteristics of the multipath structures can be efficiently simulated by reproducing the physical wave interference process, thereby incorporating the different channel characteristics that are observed in different urban environments.

Response of adaptive matched filter to multipath channel

Response of adaptive matched filter, also called adaptive correlator, to multipath channel is discussed in this paper. It has been proved that the new type processor can better match with multipath chan -nel. The results of experiment carried out on lake and in laboratory are presented. It shows that the processor has good detecting performance in time domain.

Radio propagationmeasurement and cluster-based analysis formillimeter-wave cellular systems in dense urban environments

The deployment of millimeter-wave(mmWave)cellular systems in dense urban environments with an acceptable coverage and cost-efficient transmission scheme is essential for the rollout of fifth-generation and beyond technology.In this paper,cluster-based analysis of mmWave channel characteristics in two typical dense urban environments is performed.First,radio propagation measurement campaigns are conducted in two identified mmWave bands of 28 and 39 GHz in a central business district and a dense residential area.The customdesigned channel sounder supports high-efficiency directional scanning sounding,which helps collect sufficient data for statistical channel modeling.Next,using an improved auto-clustering algorithm,multipath clusters and their scattering sources are identified.An appropriate measure for inter-and intra-cluster characteristics is provided,which includes the cluster number,the Ricean K-factor,root-mean-squared(RMS)delay spread,RMS angular spread,and their correlations.Comparisons of these parameters across two mmWave bands for both line-of-sight(LoS)and non-light-of-sight(NLoS)links are given.To shed light on the blockage effects,detailed analysis of the propagation mechanisms corresponding to each NLoS cluster is provided,including reflection from exterior walls and diffraction over building corners and rooftops.Finally,the results show that the cluster-based analysis takes full advantage of mmWave beamspace channel characteristics and has further implications for the design and deployment of mmWave wireless networks.

Multiple Input Multiple Output CDSK Chaotic Communication System and Its Performance Analysis

This paper propose a novel noncoherent chaotic com- munication scheme named multiple-input multiple-output correlation-delay-shill- keying （MIMO-CDSK）. In this scheme, multiple antennas are employed to strengthen the robustness in transmission, and to get more diversity gain. The bit error rate （BER） of the MIMO-CDSK is studied analytically in AWGN channel model and multipath fading channel model. The theory and simulation results show that, the performance gain can be obtained with multiple antennas allocated in the transmitter and receiver. Moreover, it is observed that MIMO-CDSK system can effectively reduce the multipath interference.

Distributed space-time-frequency coding for cooperative OFDM systems

A distributed space-time-frequency （STF） coding scheme is proposed for cooperative OFDM （C-OFDM） systems with three terminals over quasi-static frequency-selective Rayleigh fading channels, The outage probability is derived and its tight closed-form lower bound is presented. Asymptotic analysis indicates that the proposed scheme can achieve both spatial and multipath （frequency） diversity. The theoretical analysis of the proposed STF coded scheme is further implemented by the distributed group STF block coding （D-GSTFBC） scheme based on the subcarrier grouping technique, Simulation results confirm the previously introduced theoretical analysis.

Estimating Time Delays With Antenna Array

This paper discusses the problem of estimating the time delays of multipath signals in wireless communications. The new multipath channel model is presented. And based on this new channel model, we generalize the classical MUSIC algorithm to estimate the time delays of multipath signals. Simulation examples are included to illustrate the algorithm performance.