Linear Precoder Design for Correlated Rician Fading Channel Under Imperfect CSI

In this paper,we have modeled a linear precoder for indoor multiuser multiple input multiple output(MU-MIMO)system with imperfect channel state information(CSI)at transmitter.The Rician channel is presumed to be mutually coupled and spatially,temporarily correlated.The imperfection with CSI is primarily due to the channel estimation error at receiver and feedback delay amidst the receiver and transmitter in CSI transmission.Along with,the insufficient spacing between the antenna at transmitter and receiver persuades mutual coupling(MC)among the array elements.In addition,the MIMO channel is presumed to be jointly correlated(Weichselberger correlation model).When we look back on the existing precoder design,it considered spatial correlation alone disregarding joint correlation of antenna array elements.With all above assumption,we have designed a linear precoder which minimizes mean squared error(MSE)subjected to total transmit power constraint for MUMIMO system.The simulation results proven that proposed precoder shows substantial enhancement in bit error rate(BER)performance in comparison with the existing technique.The mathematical analysis corroborates the simulation results.

Coded Modulation Faster-than-Nyquist Transmission with Precoder and Channel Shortening Optimization

Faster-than-Nyquist(FTN)signaling can improve the spectrum efficiency(SE)of the transmission system.In this paper,we propose a coded modulation FTN(CM-FTN)transmission scheme with precoder and channel shortening(CS)optimization to improve bit error rate(BER)performance and reduce the complexity of FTN equalizer.In our proposal,the information rate(IR)or spectral efficiency(SE)is employed and verified as a better performance metric for CM-FTN than the minimum Euclidian distance(MED).The precoder of CM-FTN is optimized for maximizing the IR criterion using the bare-bones particle swarm optimization(BB-PSO)algorithm.Further,a three-carrier CM-FTN system model is used to capture the broadening effect of precoder.Also targeting for the IR maximization,the inter-symbol interference(ISI)length for CS is optimized to reduce the receiver complexity without performance loss.Simulation results demonstrate that our method has a 0.6dB precoding gain compared with the nonprecoding scheme and a maximum of 87.5%of the complexity of FTN equalizer is reduced without BER loss.

Precoder Design and Impulsive Noise Mitigation Scheme for Industrial Wireless Communications

In industrial wireless scenarios,the impulsive noise(IN)incurred by machine running or operation causes a serious influence on the powerlimited industrial wireless communications.It is challenging to ensure efficient and reliable transmission with quality of service(QoS)guarantee for machinetype communication devices(MTCDs).Considering the IN in the industrial process,this paper establishes the multiuser multiple-input single-output(MU-MISO)orthogonal frequency division multiplexing(OFDM)system model,which combines transmitter and receiver design.Two precoding schemes are designed to improve communication effectiveness at the transmitter.More specifically,the precoder design scheme which combines semi-definite relaxation(SDR)with difference-of-two-convex-function(D.C.)iterative algorithm,is developed by utilizing the Dinkelbach method to improve the system effectiveness.To decrease the computational complexity,we devise the quadratic-based fractional programming(QFP)algorithm,which decouples the variables by using a quadratic transform method.On this basis,the IN mitigation scheme is studied to reduce the system error rate(SER)at the receiver.With the goal of improving the reliability of industrial wireless communications,we propose a hybrid nonlinear IN mitigation(HNINM)scheme and then derive its closed-form expression of SER.The simulation results show that the proposed QFP algorithm achieves superior performance while the HNINM scheme decreases the SER of industrial wireless communications.

General precoder design for mitigation of intercarrier interference in OFDM mobile systems

For orthogonal frequency-division multiplexing(OFDM) communication systems,the frequency offset in mobile radio channels distorts the orthogonality between sub-carriers,which results in Intercarrier Interference(ICI) and seriously degrades the performance of systems.Based on ICI coefficients analysis,a novel precoder design scheme is proposed for mitigation of ICI.In this technique,precoder matrix is designed by the way of linear counteraction and inserted in the former transmitter signal.Computer simulation results show that this new scheme can effectively reduce ICI and significantly provide the carrier-interference power ratio improvement.Compared with existing ICI mitigation schemes with channel estimation,the proposed scheme has lower computational complexity,and compared with self-cancellation scheme,the bandwidth efficiency can be improved in this proposed scheme.The proposed scheme also has better convergence stability for time-varying frequency selective fading channel.

Hybrid Precoder and Combiner Design with Finite Resolution PSs for mmWave MIMO Systems

Hybrid precoding and combining have been considered as a promising technology, which can provide a compromise between hardware complexity and system performance in millimeter wave multiple-input multiple-output systems. However, most existing hybrid precoder and combiner designs generally assume that infinite resolution phase shifters(PSs) are used to produce the analog beamformers. In a practical scene, the design with accurate PSs can lead to high hardware cost and power consumption. In this paper, we investigate the hybrid precoder and combiner design with finite resolution PSs in millimeter wave systems. We employ alternate optimization as the main strategy to jointly design analog precoder and combiner. In addition, we propose a low complexity algorithm, where the analog beamformers are implemented only by finite resolution PSs to maximize spectral efficiency. Then, the digital precoder and combiner are designed based on the obtained analog beamformers to improve the spectral efficiency. Finally, simulation results and mathematical analysis show that the proposed algorithm with low-resolution PSs can achieve near-optimal performance and have low complexity.

An Enhanced Jacobi Precoder for Downlink Massive MIMO Systems

Linear precoding methods such as zero-forcing(ZF)are near optimal for downlink massive multi-user multiple input multiple output(MIMO)systems due to their asymptotic channel property.However,as the number of users increases,the computational complexity of obtaining the inverse matrix of the gram matrix increases.Forsolving the computational complexity problem,this paper proposes an improved Jacobi(JC)-based precoder to improve error performance of the conventional JC in the downlink massive MIMO systems.The conventional JC was studied for solving the high computational complexity of the ZF algorithm and was able to achieve parallel implementation.However,the conventional JC has poor error performance when the number of users increases,which means that the diagonal dominance component of the gram matrix is reduced.In this paper,the preconditioning method is proposed to improve the error performance.Before executing the JC,the condition number of the linear equation and spectrum radius of the iteration matrix are reduced by multiplying the preconditioning matrix of the linear equation.To further reduce the condition number of the linear equation,this paper proposes a polynomial expansion precondition matrix that supplements diagonal components.The results show that the proposed method provides better performance than other iterative methods and has similar performance to the ZF.

Design and Implementation of Nonlinear Precoding for MIMO-SDMA Toward 6G Wireless

In this paper,we present a novel and robust nonlinear precoding(NLP)design and detection structure specifically tailored for multiple-input multipleoutput space division multiple access(MIMO-SDMA)systems toward 6G wireless.Our approach aims to effectively mitigate the impact of imperfect channel estimation by leveraging the channel fluctuation mean square error(MSE)for reconstructing a highly accurate precoding matrix at the transmitter.Furthermore,we introduce a simplified receiver structure that eliminates the need for equalization,resulting in reduced interference and notable enhancements in overall system performance.We conduct both computer simulations and experimental tests to validate the efficacy of our proposed approach.The results reveals that the proposed NLP scheme offers significant performance improvements,making it particularly well-suited for the forthcoming 6G wireless.

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.

High Energy Efficiency Dynamic Connected Hybrid Precoding for mm Wave Massive MIMO Systems

This paper considers a high energy efficiency dynamic connected(HEDC)structure,which promotes the practicability and reduces the power consumption of hybrid precoding system by lowresolution phase shifters(PSs).Based on the proposed structure,a new hybrid precoding algorithm is presented to optimize the energy efficiency,namely,HP-HEDC algorithm.Firstly,via a new defined effective optimal precoding matrix,the problem of optimizing the analog switch precoding matrix is formulated as a sparse representation problem.Thus,the optimal analog switch precoding matrix can be readily obtained by the branch-and-bound method.Then,the digital precoding matrix optimization problem is modeled as a dictionary update problem and solved by the method of optimal direction(MOD).Finally,the diagonal entries of the analog PS precoding matrix are optimized by exhaustive search independently since PS and antenna is one-to-one.Simulation results show that the HEDC structure enjoys low power consumption and satisfactory spectral efficiency.The proposed algorithm presents at least 50%energy efficiency improvement compared with other algorithms when the PS resolution is set as 3-bit.

Joint linear precoder and power allocation design for uplink MIMO systems with limited feedback

In this article, the authors consider joint design of a linear precoder and power allocation for uplink multiuser multiple input multiple output （MIMO） communication systems with limited feedback to improve the bit error rate （BER） performance for all users. Precoder selection from the codebook set is directly based on the exact BER performance, instead of other suboptimal criteria, to achieve the optimal precoder matrix, but closed-form expressions may not exist in the view of power allocation based directly on the BER criterion. From this perspective, the authors propose the joint transmitter optimization algorithm for the consideration of precoder design, with total power constraint for asymptotic MBER （AMBER） criterion. In this AMBER criterion, a closed-form solution has been derived for power allocation with an optimal precoder. The simulation results show that the proposed joint design algorithm can achieve a much better performance than precoding with uniform power allocation and only consideration of power allocation.

MMSE based joint Tomlinson-Harashima source and linear relay precoder design in non-regenerative MIMO relay system

This paper proposes a joint nonlinear transceiver design scheme based on minimum mean square error （MMSE） criterion for non-regenerative multiple input multiple output （MIMO） relay system. The proposed scheme decomposes the error covariance matrix, reformulates the original joint design problem as two separate optimization problems, and then provides a closed-form solution with only local channel state information （CSI） available at the source and destination. Performance evaluation shows that the proposed scheme significantly outperforms linear schemes, and has a competitive performance compared with existing global CSI based nonlinear schemes, both iterative and non-iterative.

Joint Tomlinson-Harashima Source and Linear Relay Precoder Design in Amplify-and-Forward Multiple-Input Multiple-Output Two-Way Relay Systems

Existing minimum-mean-squared-error (MMSE) transceiver designs in amplified-and-forward (AF) multiple-input multiple-output (MIMO) two-way relay systems all assume a linear precoder at the sources. Non-linear source precoders in such a system have not been considered yet. In this paper, we study the joint design of source Tomlinson-Harashima precoders (THPs), relay linear precoder and MMSE receivers in two-way relay systems. This joint design problem is a highly nonconvex optimization problem. By dividing the original problem into three sub-problems, we propose an iterative algorithm to optimize precoders and receivers. The convergence of the algorithm is ensured since the updated solution is optimal to each sub-problem. Numerical simulation results show that the proposed iterative algorithm outperforms other algorithms in the high signal-to-noise ratio (SNR) region.

Doubling Phase Shifters for Efficient Hybrid Precoder Design in Millimeter-Wave Communication Systems

Hybrid precoding is a cost-effective approach to support directional transmissions for millimeter-wave(mmWave)communications,but its precoder design is highly complicated.In this paper,we propose a new hybrid precoder implementation,namely the double phase shifter(DPS)implementation,which enables highly tractable hybrid precoder design.Efficient algorithms are then developed for two popular hybrid precoder structures,i.e.,the fully-and partially-connected structures.For the fully-connected one,the RF-only precoding and hybrid precoding problems are formulated as a least absolute shrinkage and selection operator problem and a low-rank matrix approximation problem,respectively.In this way,computationally efficient algorithms are provided to approach the performance of the fully digital one with a small number of radio frequency(RF)chains.On the other hand,the hybrid precoder design in the partially-connected structure is identified as an eigenvalue problem.To enhance the performance of this cost-effective structure,dynamic mapping from RF chains to antennas is further proposed,for which a greedy algorithm and a modified K-means algorithm are developed.Simulation results demonstrate the performance gains of the proposed hybrid precoding algorithms over existing ones.It shows that,with the proposed DPS implementation,the fully-connected structure enjoys both satisfactory performance and low design complexity while the partially-connected one serves as an economic solution with low hardware complexity.

Deep Reinforcement Learning Based Power Minimization for RIS-Assisted MISO-OFDM Systems

In this paper,we investigate the downlink orthogonal frequency division multiplexing(OFDM)transmission system assisted by reconfigurable intelligent surfaces(RISs).Considering multiple antennas at the base station(BS)and multiple single-antenna users,the joint optimization of precoder at the BS and the phase shift design at the RIS is studied to minimize the transmit power under the constraint of the certain quality-of-service.A deep reinforcement learning(DRL)based algorithm is proposed,in which maximum ratio transmission(MRT)precoding is utilized at the BS and the twin delayed deep deterministic policy gradient(TD3)method is utilized for RIS phase shift optimization.Numerical results demonstrate that the proposed DRL based algorithm can achieve a transmit power almost the same with the lower bound achieved by manifold optimization(MO)algorithm while has much less computation delay.

A Precoding Scheme to Reduce the Effect of Channel Correlation for MIMO-PLC System

MIMO technique can provide higher information throughput and transmission reliability for the PLC system.However,the MIMO-PLC system based on three-conductor cable has a high correlation among its sub-channels.Spatial multiplexing technology will be affected by the spatial correlation between MIMO-PLC sub-channels.To reduce the system bit error rate caused by MIMO-PLC correlation among sub-channels,this paper proposed a phase rotation precoding scheme for the 2×2 closed-loop MIMO-PLC system.According to the channel transfer function of high correlation MIMO-PLC system,the phase rotation precoding matrix F is calculated,and the transmission signal matrix S is modulated with the F,the code distance at the receiving point with smallest code distance is increased by phase rotation.Simulation results show that the scheme can effectively reduce the bit error rate of the 2×2 MIMO-PLC system based on ML detection,and significantly improve the system performance.

Evaluation of Linear Precoding Schemes for Cooperative Multi-Cell MU MIMO in Future Mobile Communication Systems

In Mobile Communication Systems, inter-cell interference becomes one of the challenges that degrade the system’s performance, especially in the region with massive mobile users. The linear precoding schemes were proposed to mitigate interferences between the base stations (inter-cell). These schemes are categorized into linear and non-linear;this study focused on linear precoding schemes, which are grounded into three types, namely Zero Forcing (ZF), Block Diagonalization (BD), and Signal Leakage Noise Ratio (SLNR). The study included the Cooperative Multi-cell Multi Input Multi Output (MIMO) System, whereby each Base Station serves more than one mobile station and all Base Stations on the system are assisted by each other by shared the Channel State Information (CSI). Based on the Multi-Cell Multiuser MIMO system, each Base Station on the cell is intended to maximize the data transmission rate by its mobile users by increasing the Signal Interference to Noise Ratio after the interference has been mitigated due to the usefully of linear precoding schemes on the transmitter. Moreover, these schemes used different approaches to mitigate interference. This study mainly concentrates on evaluating the performance of these schemes through the channel distribution models such as Ray-leigh and Rician included in the presence of noise errors. The results show that the SLNR scheme outperforms ZF and BD schemes overall scenario. This implied that when the value of SNR increased the performance of SLNR increased by 21.4% and 45.7% for ZF and BD respectively.

Closed-form interference alignment with heterogeneous degrees of freedom

Interference alignment(IA) has been recognized as a promising technique for obtaining the optimal degrees of freedom(DOF) in interference networks.A closed-form interference alignment design is proposed for three-cell uplink transmissions with heterogeneous DOFs.By exploiting the heterogeneity of DOFs from different transmission links,full or partial interference alignment precoders are calculated at each base station(BS).Aided by information exchange among BSs,the precoders can be finally obtained for all transmission links.Comparing to existing IA methods,the proposed scheme has a closed-form expression.Furthermore,there is no need to go through the iterative adaptation or jointly calculate the precoder and the equalizer.Simulation results show that the proposed design is able to achieve the optimal DOF performance with the advantage of perfect alignment capabilities.

Low Complexity Joint Hybrid Precoding for Millimeter Wave MIMO Systems

In millimeter wave(mmWave) multiple-input multiple-output(MIMO) systems, hybrid precoding has been widely used to overcome the severe propagation loss. In order to improve the spectrum efficiency with low complexity, we propose a joint hybrid precoding algorithm for single-user mmWave MIMO systems in this paper. By using the concept of equivalent channel, the proposed algorithm skillfully utilizes the idea of alternating optimization to complete the design of RF precoder and combiner. Then, the baseband precoder and combiner are computed by calculating the singular value decomposition of the equivalent channel. Simulation results demonstrate that the proposed algorithm can achieve satisfactory performance with quite low complexity. Moreover, we investigate the effects of quantization on the analog components and find that the proposed scheme is effective even with coarse quantization.

Fairness-Oriented Hybrid Precoding for Massive MIMO Maritime Downlink Systems with Large-Scale CSIT

Different from conventional cellular networks, a maritime communication base station(BS) has to cover a much wider area due to the limitation of available BS sites. Accordingly the performance of users far away from the BS is poor in general. This renders the fairness among users a challenging issue for maritime communications. In this paper, we consider a practical massive MIMO maritime BS with hybrid digital and analog precoding. Only the large-scale channel state information at the transmitter(CSIT) is considered so as to reduce the implementation complexity and overhead of the system. On this basis, we address the problem of fairness-oriented precoding design. A max-min optimization problem is formulated and solved in an iterative way. Simulation results demonstrate that the proposed scheme performs much better than conventional hybrid precoding algorithms in terms of minimum achievable rate of all the users, for the typical three-ray maritime channel model.

Hybrid Precoding for mm Wave Massive MIMO Systems with Different Antenna Arrays

In this paper, the performance of hybrid precoding is investigated for mmWave massive MIMO systems with different antenna arrays. The hybrid precoding with partially connected architecture (PCA) is adopted. The spectral efficiency (SE) and received energy efficiency (EE) are investigated by considering four types of antenna arrays, including uniform linear array (ULA), uniform rectangular planar array (URPA), uniform hexagonal planar array (UHPA), and uniform circular planar array (UCPA), respectively. We focus on analysis at the antenna response vector and utilize the idea of orthogonal matching pursuit algorithm to seek the optimal hybrid precoder. Furthermore, the trade-off of precoding architectures is studied between SE and received EE. Simulation results show that if the uniform planar array antenna is more concentrated, the SE and receive EE will be higher. Considering SE and received EE, the performance of planar arrays outperform linear array. There exist different optimal radio-frequency chain numbers to maximize the SE for planar array and linear array. In addition, the PCA can achieve relatively higher received EE while the SE is close to the fully connected architecture and the full digital architecture.