Channel Correlation Based User Grouping Algorithm for Nonlinear Precoding Satellite Communication System

Low Earth Orbit(LEO)multibeam satellites will be widely used in the next generation of satellite communication systems,whose inter-beam interference will inevitably limit the performance of the whole system.Nonlinear precoding such as Tomlinson-Harashima precoding(THP)algorithm has been proved to be a promising technology to solve this problem,which has smaller noise amplification effect compared with linear precoding.However,the similarity of different user channels(defined as channel correlation)will degrade the performance of THP algorithm.In this paper,we qualitatively analyze the inter-beam interference in the whole process of LEO satellite over a specific coverage area,and the impact of channel correlation on Signal-to-Noise Ratio(SNR)of receivers when THP is applied.One user grouping algorithm is proposed based on the analysis of channel correlation,which could decrease the number of users with high channel correlation in each precoding group,thus improve the performance of THP.Furthermore,our algorithm is designed under the premise of co-frequency deployment and orthogonal frequency division multiplexing(OFDM),which leads to more users under severe inter-beam interference compared to the existing research on geostationary orbit satellites broadcasting systems.Simulation results show that the proposed user grouping algorithm possesses higher channel capacity and better bit error rate(BER)performance in high SNR conditions relative to existing works.

Lattice-reduction-aided MMSE precoding for correlated MIMO channels and performance analysis

The lattice-reduction （LR） has been developed to im- prove the performance of the zero-forcing （ZF） precoder in multiple input multiple output （MIMO） systems. Under the assumptions of uncorrelated flat fading channel model and perfect channel state information at the transmitter （CSIT）, an LR-aided ZF precoder is able to collect the full transmit diversity. With the complex Lenstra- Lenstra-Lov^sz （LLL） algorithm and limited feedforward structure, an LR-aided linear minimum-mean-square-error （LMMSE） pre- coder for spatial correlated MIMO channels and imperfect CSIT is proposed to achieve lower bit error rate （BER）. Assuming a time division duplexing （TDD） MIMO system, correlated block flat fad- ing channel and LMMSE uplink channel estimator, it is proved that the proposed LR-aided LMMSE precoder can also obtain the full transmit diversity through an analytical approach. Furthermore, the simulation results show that with the quadrature phase shift keying （QPSK） modulation at the transmitter, the uncoded and coded BERs of the LR-aided LMMSE precoder are lower than that of the traditional LMMSE precoder respectively when Eb-No is greater than 10 dB and 12 dB at all correlation coefficients.

Correlated channel model-based secure communications in dual-hop wireless communication networks

This article is focused on secure relay beamformer design with a correlated channel model in the relay-eavesdropper network. In this network, a single-antenna source-destination pair transmits secure information with the help of an amplify-and-forward (AF) relay equipped with multiple antennas, and the legitimate and eavesdropping channels are correlated. The relay cannot obtain the instantaneous channel state information (CSI) of the eavesdropper, and has only the knowledge of correlation information between the legitimate and eavesdropping channels. Depending on this information, we derive the conditional distribution of the eavesdropping channel. Two beamformers at the relay are studied for the approximate ergodic secrecy rate:(1) the generalized match-andforward (GMF) beamformer to maximize the legitimate channel rate, and (2) the general-rank beamformer (GRBF).In addition, one lower-bound-maximizing (LBM) beamformer at the relay is discussed for maximizing the lower bound of the ergodic secrecy rate. We find that the GMF beamformer is the optimal rank-one beamformer, that the GRBF is the iteratively optimal beamformer, and that the performance of the LBM beamformer for the ergodic secrecy rate gets close to that of the GRBF for the approximate secrecy rate. It can also be observed that when the relay has lower power or the channel gain of the second hop is low, the performance of the GMF beamformer surpasses that of the GRBF. Numerical results are presented to illustrate the beamformers' performance.

Dense coding capacity in correlated noisy channels with weak measurement

Capacity of dense coding via correlated noisy channel is greater than that via uncorrelated noisy channel.It is shown that the weak measurement and reversal measurement need to further improve their quantum dense coding capacity in correlated amplitude damping channel,but this improvement is very small in correlated phase damping channel and correlated depolarizing channel.

Robustness of two-qubit and three-qubit states in correlated quantum channels

We investigate how the correlated actions of quantum channels affect the robustness of entangled states.We consider the Bell-like state and random two-qubit pure states in the correlated depolarizing,bit flip,bit-phase flip,and phase flip channels.It is found that the robustness of two-qubit pure states can be noticeably enhanced due to the correlations between consecutive actions of these noisy channels,and the Bell-like state is always the most robust one.We also consider the robustness of three-qubit pure states in correlated noisy channels.For the correlated bit flip and phase flip channels,the result shows that although the most robust and most fragile states are locally unitary equivalent,they exhibit different robustness in different correlated channels,and the effect of channel correlations on them is also significantly different.However,for the correlated depolarizing and bit-phase flip channels,the robustness of two special three-qubit pure states is exactly the same.Moreover,compared with the random three-qubit pure states,they are neither the most robust states nor the most fragile states.

RIS-Assisted Communications in Correlated Rayleigh Channels:Comparison of Training Overhead Reduction Schemes

Channel training in reconfigurable intelligent surface(RIS)-assisted communications is usually conducted in an on-off manner,resulting in unaffordable training time overhead when the number of RIS elements is large.In this paper,for correlated Rayleigh channels,we compare three typical training overhead reduction schemes,namely RIS element selection(Scheme 1),element grouping(Scheme 2),and statistical CSI-based phase shifts design(Scheme3).For Scheme 1 and Scheme 2,we propose two algorithms to select RIS elements(or form element groups) and determine the optimal number of activated elements(or formed groups),based on the channel correlation information only;for Scheme 3,we consider a semi-definite programming-based approach in the literature,and propose an alternative dominant eigenvector-based method for determining the RIS phase shifts vector.Via extensive simulations,we compare the achievable ergodic rates of these schemes versus the signal-to-noise ratio,the channel correlation level,and the element number-to-coherent time ratio,respectively,and discuss possible switching of the three schemes over these system parameters.At last,operation regions of the considered training overhead reduction schemes are shown in the plane characterized by the system parameters,which provides useful guidelines for practical scheme determination.

Nonlocal advantage of quantum coherence in a dephasing channel with memory

We investigate nonlocal advantage of quantum coherence(NAQC)in a correlated dephasing channel modeled by themultimode bosonic reservoir.We obtain analytically the dephasing and memory factors of this channel for the reservoirhaving a Lorentzian spectral density,and analyze how they affect the NAQC defined by the l1 norm and relative entropy.It is shown that the memory effects of this channel on NAQC are state-dependent,and they suppress noticeably the rapiddecay of NAQC for the family of input Bell-like states with one excitation.For the given transmission time of each qubit,we also obtain the regions of the dephasing and memory factors during which there is NAQC in the output states.

Single foggy image restoration based on spatial correlation analysis of dark channel prior

Focusing on the degradation of foggy images, a restora- tion approach from a single image based on spatial correlation of dark channel prior is proposed. Firstly, the transmission of each pixel is estimated by the spatial correlation of dark channel prior. Secondly, a degradation model is utilized to restore the foggy image. Thirdly, the final recovered image, with enhanced contrast, is obtained by performing a post-processing technique based on just-noticeable difference. Experimental results demonstrate that the information of a foggy image can be recovered perfectly by the proposed method, even in the case of the abrupt depth changing scene.

Performance of VBLAST Systems Based on Spatial Correlated MIMO Channels

Vertically-layered Bell Laboratories Layered Space-Time (VBLAST) is one of the most promising techniques for realizing high spectral efficiencies over wireless link. In previously published work, the performance of VBLAST has been primarily investigated in uncorrelated Rayleigh fading channels. However in real environments some correlation between antenna elements can be presented. In this paper, we study the impact of transmit correlation on the performance of VBLAST systems. Finally we provide simulation results demonstrating the impact of spatial fading correlation on the symbol error rate of VBLAST.

BER analysis of MPSK space-time code with differential detection over correlated block-fading Rayleigh channel

MIMO technology proposed in recent years can effectively combat the multipath fading of wireless channel and can considerably enlarge the channel capacity, which has been investigated widely by researchers. However, its performance analysis over correlated block-fading Rayleigh channel is still an open and challenging objective. In this article, an analytic expression of bit error rate （BER） is presented for multiple phase shift keying （MPSK） space-time code, with differential detection over correlated block-fading Rayleigh channel. Through theoretical analysis of BER, it can be found that the differential space-time scheme without the need for channel state information （CSI） at receiver achieves distinct performance gain compared with the traditional nonspace-time system. And then, the system simulation is complimented to verify the above result, showing that the diversity system based on the differential space-time block coding （DSTBC） outperforms the traditional nonspacetime system with diversity gain in terms of BER. Furthermore, the numerical results also demonstrate that the error floor of the differential space-time system is much lower than that of the differential nonspace-time system.

Layered space time codes and capacity analysis in correlated fading channels with distributed antenna system

In this paper we have investigated the performance of downlink generalized distributed antenna system （GDAS）. Under the assumption of spatial correlated fading conditions, we have derived the numeric expression of correlated coefficients according to series of Bessel function, and have lifted the range restriction of the mean angle of incident. Moreover, the architecture of distributed generalized layered space time codes （GLST） has been considered in order to achieve both multiplexing gain and diversity gain while we have used basis vector from null space instead of orthogonal set to obtain the same system performance but with lower complexity. Furthermore, in order to maximize the capacity, Gerschgorin circles based fast antenna selection algorithms have been evaluated including a discussion of those simulation results.

Optimal precoding for full-duplex base stations under strongly correlated self-interference channels

We study the optimal precoding for a full-duplex (FD) system, where one FD multi-antenna base station (BS) respectively transmits to and receives from two half-duplex single-antenna mobile users (MUs) on the same time slot and frequency band. At the FD BS, the received signal from the desired MU is severely affected by the extremely strong self-interference (SI) from its transmit antennas to the receive antennas. In the presence of residual SI after imperfect SI cancellation, the downlink transmission rate maximization problem subject to a targeted uplink rate is formulated as a non-convex optimization problem to characterize the achievable rate region for the considered system. Considering the case in which the SI channel is strongly correlated, the above problem is transformed into a convex problem by exploiting the rank-one property of the SI channel, which can be solved efficiently. Finally, numerical results validate the effectiveness of the proposed scheme.

A cross-layer adaptive transmission scheme over correlated fading channels

Conventional adaptive transmission schemes perform poorly in wireless correlated slow-fading channels.A cross-layer adaptive transmission scheme combined with selective repeat automatic repeat request(SR-ARQ)is proposed.We apply a multi-state Markov system model for analyzing the performance of systems and optimizing the selection of modulation levels and packet sizes in correlated fading channels,which is also described by a finite-state Markov chain.A general closed-form expression of the average throughput for our suggested scheme is presented.Numerical results show that our adaptive scheme combined with SR-ARQ can obtain good performance in correlated fading channels.

Distinguishing Computer-Generated Images from Natural Images Using Channel and Pixel Correlation

With the recent tremendous advances of computer graphics rendering and image editing technologies,computergenerated fake images,which in general do not reflect what happens in the reality,can now easily deceive the inspection of human visual system.In this work,we propose a convolutional neural network(CNN)-based model to distinguish computergenerated(CG)images from natural images(NIs)with channel and pixel correlation.The key component of the proposed CNN architecture is a self-coding module that takes the color images as input to extract the correlation between color channels explicitly.Unlike previous approaches that directly apply CNN to solve this problem,we consider the generality of the network(or subnetwork),i.e.,the newly introduced hybrid correlation module can be directly combined with existing CNN models for enhancing the discrimination capacity of original networks.Experimental results demonstrate that the proposed network outperforms state-of-the-art methods in terms of classification performance.We also show that the newly introduced hybrid correlation module can improve the classification accuracy of different CNN architectures.

Correlation equalizer and its simulation for underwater acoustic channels

A robust correlation equalizer is presented to resolve the equalization divergence,which is caused by the distribution of channel response function's zero points outside the unit circle. The equalizer is robust except that the channel response function has zero points just on the wht circle. Noncausal two-side prediction is also proposed. Based on the prediction and FFT the transversal form of the correlation equdrier and the fast algorithIn are developed. The simulation results of the correlation equallzer of transversal form are given.