Unquantized and uncoded channel state information feedback in multiple-antenna multiuser systems

We propose a channel state information (CSI) feedback scheme based on unquantized and uncoded (UQ-UC) transmission. We consider a system where a mobile terminal obtains the downlink CSI and feeds it back to the base station using an uplink feedback channel. If the downlink channel is an independent Rayleigh fading channel, then the CSI may be viewed as an output of a complex independent identically distributed Gaussian source. Further, if the uplink feedback channel is an additive white Gaussian noise channel, and the downlink CSI is perfectly known at the mobile terminal, it can be shown that UQ-UC CSI transmission (that incurs zero delay) is optimal in that it achieves the same minimum mean-squared error distortion as a scheme that optimally (in the Shannon sense) quantizes and encodes the CSI, while theoretically incurring infinite delay. Since the UQ-UC transmission is suboptimal on correlated wireless channels, we propose a simple linear CSI feedback receiver that can be used to improve the performance of UQ-UC transmission while still retaining the attractive zero-delay feature. We provide bounds on the performance of such UQ-UC CSI feedback and study its impact on the achievable information rates. Furthermore, we explore its application and performance in multiple-antenna multiuser wireless systems, and also propose a corresponding pilot-assisted channel-state estimation scheme.     

Outage-based design of robust Tomlinson–Harashima transceivers for the MISO downlink with QoS requirements

We consider a broadcast channel in which the base station is equipped with multiple antennas and each user has a single antenna, and we study the design of transceivers based on Tomlinson–Harashima precoders with probabilistic quality of service (QoS) requirements for each user, in scenarios with uncertain channel state information (CSI) at the transmitter. Each user's QoS requirement is specified as a constraint on the maximum allowed outage probability of the receiver's mean square error (MSE) with respect to a specified target MSE, and we demonstrate that these outage constraints are associated with constraints on the outage of the received signal-to-interference-plus-noise-ratio (SINR). We consider four different stochastic models for the channel uncertainty, and we design the downlink transceiver so as to minimize the total transmitted power subject to the satisfaction of the probabilistic QoS constraints. We present three conservative approaches to solving the resulting chance constrained optimization problems. These approaches are based on efficiently solvable deterministic convex design formulations that guarantee the satisfaction of the probabilistic QoS constraints. We also demonstrate how to apply these approaches in order to obtain computationally efficient solutions to some related design problems. Our simulations indicate that the proposed methods can significantly expand the range of QoS requirements that can be satisfied in the presence of uncertainty in the CSI.     

Robust Tomlinson-Harashima Precoders for Multiuser MISO Downlink with Imperfect CSI

In this paper, we consider robust non-linear precoding for the downlink of a multiuser multiple-input single-output (MISO) communication system in the presence of imperfect channel state information (CSI). The base station (BS) is equipped with multiple transmit antennas and each user terminal is equipped with a single receive antenna. We propose two robust Tomlinson-Harashima precoder (THP) designs. The first design is based on the minimization of the total BS transmit power under constraints on the mean square error (MSE) at the individual user receivers. We show that this problem can be solved by an iterative procedure, where each iteration involves the solution of a pair of convex optimization problems that can be solved efficiently. A robust linear precoder with MSE constraints can be obtained as a special case of this robust THP. The second design is based on the minimization of a stochastic function of the sum MSE under a constraint on the total BS transmit power. We formulate this design problem as an optimization problem that can be solved by the method of alternating optimization, the application of which results in a second-order cone program that can be numerically solved efficiently. Simulation results illustrate the improvement in performance of the proposed precoders compared to other robust linear and non-linear precoders in the literature.     

A novel prefiltering technique for downlink transmissions in TDD MC-CDMA systems

We discuss a prefiltering technique for interference mitigation in the downlink of a time division duplex (TDD) multicarrier code-division multiple access (MC-CDMA) system. The base station (BS) is equipped with multiple transmit antennas, and channel state information (CSI) is obtained at the transmitter side by exploiting the channel reciprocity between uplink and downlink transmissions. The prefiltering coefficients are designed so as to minimize a proper cost function that depends on the signal-to-interference-plus-noise ratios (SINRs) at the mobile terminals (MTs). The resulting scheme allows using a simple despreading receiver, thereby eliminating the need for channel estimation and equalization. Numerical results show the advantages of the proposed scheme over some existing solutions.     

Multiple antenna MMSE based downlink precoding with quantized feedback or channel mismatch

In this paper, we consider the downlink of a multiuser wireless communication system with multiple antennas at the base station and users each with a single receive antenna. It is known that when channel state information (CSI) is available at the transmitter a large performance gain can be achieved. In a system employing time-division duplexing (TDD), CSI can be obtained at the base station if there is reciprocity between the forward and reverse channels. CSI can also be conveyed from the users to the base station via a limited-rate feedback channel in a frequency-division duplexing (FDD) system. In any case, channel estimation errors are inevitable due to the presence of background noise in the estimated signal and due to the finite number of feedback bits used in a limited-rate feedback system model. In this paper, we first consider the general case when partial CSI is available at the transmitter. We derive an MMSE based precoding technique that considers channel estimation errors as an integral part of the system design. Using rate-distortion theory and the generalized Lloyd vector quantization algorithm, we then specialize our results for the more practical limited-rate feedback system model. Compared to previously proposed precoding techniques such as channel inversion and regularized channel inversion, it is shown that the proposed precoding technique significantly improves the average bit error rate (BER) in the system. Furthermore, the performance of the proposed technique is investigated in the high signal-tonoise ratio (SNR) regime, and similar to [1], [2], it is shown that the proposed technique suffers from a ceiling effect that asymptotically limits the system performance.     

统计和瞬时CSI混合的3D MIMO预编码

本文针对分别具有统计信道状态信息（Channel State Information,CSI）和瞬时CSI的用户,研究了两类用户在三维多输入多输出（Three-Dimension Multiple-Input Multiple-Output,3D MIMO）系统中的下行链路传输模式,解决了混合利用统计和瞬时CSI的下行预编码的设计问题。利用3D MIMO信道的克罗内克积的性质,提出了一种用于最小化基站总发射功率的扩展迫零预编码的方法,并分别求解其最优水平预编码矩阵和最优垂直预编码矩阵。仿真结果表明,该方案具有更低的复杂度和良好的速率。      

基于FDD-OFDMA系统的多用户下行传输跨层优化

该文针对FDD-OFDMA移动通信下行系统受限干扰的问题,提出了一种资源调度跨层设计方法。所提方法在满足目标误包率的前提下,以最大化系统goodput(发射端成功发射的比特率)为准则建立优化模型,能在发射端完全不知道信道状态信息(CSI)的情况下,利用反馈的确认/否定确认(ACK/NAK)信息实现用户调度以及速率分配的优化。仿真结果表明,所提算法在较低复杂度前提下获得很接近发射端完全已知信道状态信息的系统goodput。     

Channel estimation for multi-panel millimeter waveMIMO based on joint compressed sensing

Channel state information (CSI) is essential for downlink transmission in millimeter wave( mmWave) multipleinput multiple output (MIMO) systems. Multi-panel antenna array is exploited in mmWave MIMO system due to itssuperior performance. Two channel estimation algorithms are proposed in this paper, named as generalized jointorthogonal matching pursuit (G-JOMP) and optimized joint orthogonal matching pursuit (O-JOMP) for multi-panelmmWave MIMO system based on the compressed sensing (CS) theory. G-JOMP exploits common sparsity structureamong channel response between antenna panels of base station ( BS) and users to reduce the computationalcomplexity in channel estimation. O-JOMP algorithm is then developed to further improve the accuracy of channelestimation by optimal panel selection based on the power of the received signal. Simulation results show that theperformance of the proposed algorithms is better than that of the conventional orthogonal matching pursuit (OMP)based algorithm in multi-panel mmWave MIMO system.     

基于人工智能的大规模MIMO信道状态信息反馈综述

大规模多输入多输出(Multiple-Input Multiple-Output,MIMO)技术凭借其高能量效率和高频谱效率的优势成为下一代移动通信的核心技术之一,其系统增益的基础在于基站能够精确获知信道状态信息(Channel State Information,CSI).由于大规模MIMO系统中基站天线数量巨大,基站获取下行信道状态信息将造成巨大的系统开销,传统基于码本或矢量量化的反馈方法受到挑战,频分双工(Frequency Division Duplex,FDD)模式下5G通信的实际应用也受到制约,而人工智能技术尤其是深度学习(Deep Learning,DL)为解决大规模MIMO系统中的CSI反馈问题提供了新的思路.围绕大规模MIMO系统CSI反馈存在的问题,阐述了CSI反馈的背景,构建了FDD大规模MIMO系统模型,详细描述了代表性的国内外基于DL的CSI反馈方案,最后对基于人工智能的大规模MIMO信道状态信息反馈进行了展望和总结.     

A Partial CSI Estimation Approach for Downlink FDD massive-MIMO System with Different Base Transceiver Station Topologies

Massive multiple-input multiple-output (massive-MIMO) is a promising technology for next generation wireless communications systems due to its capability to increase the data rate and meet the enormous ongoing data traffic explosion. However, in non-reciprocal channels, such as those encountered in frequency division duplex (FDD) systems, channel state information (CSI) estimation using downlink (DL) training sequence is to date very challenging issue, especially when the channel exhibits a shorter coherence time. In particular, the availability of sufficiently accurate CSI at the base transceiver station (BTS) allows an efficient precoding design in the DL transmission to be achieved, and thus, reliable communication systems can be obtained. In order to achieve the aforementioned objectives, this paper presents a feasible DL training sequence design based on a partial CSI estimation approach for an FDD massive-MIMO system with a shorter coherence time. To this end, a threshold-based approach is proposed for a suitable DL pilot selection by exploring the statistical information of the channel covariance matrix. The mean square error of the proposed design is derived, and the achievable sum rate and bit-error-rate for maximum ratio transmitter and regularized zero forcing precoding is investigated over different BTS topologies with uniform linear array and uniform rectangular array. The results show that a feasible performance in the DL FDD massive-MIMO systems can be achieved even when a large number of antenna elements are deployed by the BTS and a shorter coherence time is considered.

     

Robust Relaying Schemes for Multiple-Antenna Multi-Relay Networks

The optimal beamforming weight matrix for amplify and forward multiple-antenna multiple-relay network is investigated. It is assumed that the partial first and second hop channel state information (CSI) is available at relays. In order to minimize the mean square error (MSE) at destination, all relay weight matrices must be designed simultaneously under individual relay power constraints. Using the Lagrange dual variables, it is shown that this general vector optimization problem can be converted into a scalar optimization problem whose scalar Lagrange multipliers can be obtained numerically. This is the generalized version of the scheme suggested for complete CSI. The proposed scheme is evaluated through computer simulation with various numbers of relays and antennas to obtain MSE and bit error rate (BER) metrics. It is also shown that the resulting MSE and BER are less than those of the schemes available in the literature by a good margin depending upon the amount of the utilized relay and antennas as well as the estimation error.     

Covariance-based linear precoding

This paper extends the self-contained theory of linear precoding to the field of covariance based spatio-temporal downlink processing for direct-sequence code-division multiple-access (CDMA) systems and shows the applicability to the release 6 of high-speed downlink packet access (HSDPA). To this end, a unifying theory is developed to formulate the three known linear filters, namely, the transmit matched filter, the transmit zero-forcing filter, and the transmit Wiener filter, as optimization problems even in systems, where only covariance knowledge is available at the transmitter. Second, the solutions of these transmit filters are given for such systems with partial channel state information (CSI). Finally, it is shown how covariance-based linear precoding can be employed in the new generation CDMA system HSDPA, i.e., how channel estimation on the secondary common pilot channel allows for optimum full rank linear precoding employing only partial CSI.     

Optimal user selection and power allocation for revenue maximization in non‐orthogonal multiple access systems

A novel algorithm for joint user selection and optimal power allocation for Stackelberg game‐based revenue maximization in a downlink non‐orthogonal multiple access (NOMA) network is proposed in this study. The condition for the existence of optimal solution is derived by assuming perfect channel state information (CSI) at the transmitter. The Lagrange multiplier method is used to convert the revenue maximization problem into a set of quadratic equations that are reduced to a regular chain of expressions. The optimal solution is obtained via a univariate iterative procedure. A simple algorithm for joint optimal user selection and power calculation is presented and exhibits extremely low complexity. Furthermore, an outage analysis is presented to evaluate the performance degradation when perfect CSI is not available. The simulation results indicate that at 5‐dB signal‐to‐noise ratio (SNR), revenue of the base station improves by at least 15.2% for the proposed algorithm when compared to suboptimal schemes. Other performance metrics of NOMA, such as individual user‐rates, fairness index, and outage probability, approach near‐optimal values at moderate to high SNRs.     

Convex-optimization-based precoding for MIMO downlinks

In this paper,the design of linear leakage-based precoders is considered for multiple-input multiple-output(MIMO) downlinks.Our proposed scheme minimizes total transmit power under each user's signal-to-leakage-plus-noise ratio(SLNR) constraint.When the base station knows perfect channel state information(CSI),suitable reformulation of design problem allows the successful application of semidefinite relaxation(SDR) techniques.When the base station knows imperfect CSI with limited estimation errors,the desig...     

基于双向中继和网络编码的NOMA网络性能分析

针对实际场景中存在的具有上下行双向传输任务的通信系统,本文提出了一种双向中继协作非正交多址接入(NOMA, non-orthogonal multiple access)传输方案,基于解码转发(DF, Decode and Forward)协议研究信号的上行和下行双向传输技术,与现有NOMA方案不同,本方案为近端用户分配较大的功率,利用网络编码(NC, network coding)原理在两个时隙内实现基站和用户之间的双向信息交换。进一步考虑不完美信道状态信息(CSI, Channel State Information)条件,分析系统的传输性能并推导了系统中断概率以及遍历和速率闭合表达式。仿真结果表明,在完美CSI和不完美CSI条件下,相比于现有文献所提方案、单向中继(OWR,One-Way Relay)和正交多址(OMA, Orthogonal Multiple Access)网络,本文所提方案有效降低了系统的传输中断概率,提高了系统的遍历和速率以及系统吞吐量。      

Robust Power Allocation Designs for Multiuser and Multiantenna Downlink Communication Systems through Convex Optimization

In this paper, we study the design of the transmitter in the downlink of a multiuser and multiantenna wireless communications system, considering the realistic scenario where only an imperfect estimate of the actual channel is available at both communication ends. Precisely, the actual channel is assumed to be inside an uncertainty region around the channel estimate, which models the imperfections of the channel knowledge that may arise from, e.g., estimation Gaussian errors, quantization effects, or combinations of both sources of errors. In this context, our objective is to design a robust power allocation among the information symbols that are to be sent to the users such that the total transmitted power is minimized, while maintaining the necessary quality of service to obtain reliable communication links between the base station and the users for any possible realization of the actual channel inside the uncertainty region. This robust power allocation is obtained as the solution to a convex optimization problem, which, in general, can be numerically solved in a very efficient way, and even for a particular case of the uncertainty region, a quasi-closed form solution can be found. Finally, the goodness of the robust proposed transmission scheme is presented through numerical results. Robust designs, imperfect CSI, multiantenna systems, broadcast channel, convex optimization.     

Robust MSE equalizer design for MIMO communication systems in the presence of model uncertainties

This paper considers a robust mean-square-error (MSE) equalizer design problem for multiple-input multiple-output (MIMO) communication systems with imperfect channel and noise information at the receiver. When the channel state information (CSI) and the noise covariance are known exactly at the receiver, a minimum-mean-square-error (MMSE) equalizer can be employed to estimate the transmitted signal. However, in actual systems, it is necessary to take into account channel and noise estimation errors. We consider here a worst-case equalizer design problem where the goal is to find the equalizer minimizing the equalization MSE for the least favorable channel model within a neighborhood of the estimated model. The neighborhood is formed by placing a bound on the Kullback-Leibler (KL) divergence between the actual and estimated channel models. Lagrangian optimization is used to convert this min-max problem into a convex min-min problem over a convex domain, which is solved by interchanging the minimization order. The robust MSE equalizer and associated least favorable channel model can then be obtained by solving numerically a scalar convex minimization problem. Simulation results are presented to demonstrate the MSE and bit error rate (BER) performance of robust equalizers when applied to the least favorable channel model.     

MUSIC-Based Pilot Decontamination and Channel Estimation in Multiuser Massive MIMO System

This paper addresses the problem of channel estimation in a multiuser multi-cell wireless communications system in which the base station (BS) is equipped with a very large number of antennas (also referred to as “massive multiple-input multiple-output (MIMO)”). We consider a time-division duplexing (TDD) scheme, in which reciprocity between the uplink and downlink channels can be assumed. Channel estimation is essential for downlink beamforming in massive MIMO, nevertheless, the pilot contamination effect hinders accurate channel estimation, which leads to overall performance degradation. Benefitted from the asymptotic orthogonality between signal and interference subspaces for non-overlapping angle-of arrivals (AOAs) in the large-scale antenna system, we propose a multiple signals classification (MUSIC) based channel estimation algorithm during the uplink transmission. Analytical and numerical results verify complete pilot decontamination and the effectiveness of the proposed channel estimation algorithm in the multiuser multi-cell massive MIMO system.     

Channel-Aware ALOHA-Based OFDM Subcarrier Assignment in Single-Cell Wireless Communications

Usually, centralized channel state information (CSI) is assumed to exploit the multiuser diversity with a smart transmission scheduler. However, such centralized CSI can be impractical for a broadband wireless communication system with a large number of mobile users (MUs). In this paper, we propose a decentralized method to exploit the multiuser diversity in a single cell scenario with orthogonal frequency-division multiplexing (OFDM) based downlink. The central part of our approach is the channel-aware ALOHA-based OFDM subcarrier assignment. According to it, each MU measures the channel at all OFDM subcarriers and tries to obtain proper ones by sending a service-request packet through the corresponding orthogonal uplink subchannel. This packet is sent when the measured channel-fading level exceeds a predetermined threshold xi. The base station processes these request packets with a collision-reception model, and assigns the corresponding subcarrier(s) to the MU whose request packet has been successfully received. Two implementation algorithms are developed, by solving the problem of optimization of xi under different system configurations. Computer simulations show that in comparison with the standard round-robin method, the proposed algorithms offer a substantial data-rate improvement, especially when the correlation property of the OFDM subcarriers is properly exploited     

Adaptive Interference Suppression for the Downlink of a Direct Sequence CDMA System with Long Spreading Sequences

A simple approach for adaptive interference suppression for the downlink (base-to-mobile link) of a direct sequence (DS) based cellular communication system is presented. The base station transmits the sum of the signals destined for the different mobiles, typically attempting to avoid intra-cell interference by employing orthogonal spreading sequences for different mobiles. However, the signal reaching any given mobile passes through a dispersive channel, thus destroying the orthogonality. In this paper, we propose an adaptive linear equalizer at the mobile that reduces interference by approximately restoring orthogonality. The adaptive equalizer uses the pilot's spreading sequence (which observes the same channel as the spreading sequence for the desired mobile) as training. Simulation results for the linear Minimum Mean Squared Error (MMSE) equalizer are presented, demonstrating substantial performance gains over the RAKE receiver. Long spreading sequences (which vary from symbol to symbol) are employed, so that the equalizer adapts not to the time-varying spreading sequences, but to the slowly varying downlink channel. Since the inter-cell interference from any other base station also has the structure of many superposed signals passing through a single channel, the adaptive equalizer can also suppress inter-cell interference, with the tradeoff between suppression of intra- and inter-cell interference and noise enhancement depending on their impact on the Mean Squared Error (MSE).