Unsupervised receiver processing techniques for linear space-time equalization of wideband multiple input / multiple output channels

In this paper, we address the problem of unsupervised (blind) space-time equalization of frequency-selective multiple-input multiple-output (MIMO) channels. The motivation behind this work is that in order to provide the high transmission rates that data-demanding applications require, wireless multiple antenna (MIMO) systems will have to operate in wide bandwidths. In such scenarios, frequency selectivity may induce important intersymbol interference (ISI), in addition to the interuser interference (IUI) that each antenna's transmitted stream of data suffers from the other antennas. Under these conditions, channel estimation of the frequency-selective MIMO channel may become a daunting task that ultimately reduces the effective transmission rate. We present a family of globally convergent blind space-time equalization techniques, developed from multiuser kurtosis output-based criteria, which allow the recovery of the MIMO channel inputs without the training overhead that channel estimation typically requires, thus improving the MIMO channel's spectral efficiency.     

On Issues about the Application of MIMO in Mobile Cellular Communications

1　Introduction　Thenewgeneration (beyond 3G/4G)mobilecel lularcommunicationsystemneedstosatisfythehighcapacitydemandsdrivenbysomeapplicationssuchasInternetandmultimediaapplications.Insuchasystem ,thekeytoachievetherequiredratesinahighlylimitedradiospectrumresourceisinadoptionofnoveltransmissiontechniques,whichofferhighspectralefficiencyandhightransmissionreliabilityrelativetothecurrentsystems.Multiple InputMul tiple Output(MIMO)systemusingmultipleantennasattransmitandreceiveendcanincrease…     

Channel Capacity of TDD-OFDM-MIMO for Multiple Access Points in a Wireless Single-Frequency-Network

The multiple-input-multiple-output (MIMO) technique is the most attractive candidate to improve the spectrum efficiency in the next generation wireless communication systems. However, the efficiency of MIMO techniques reduces in the line of sight (LOS) environments. In this paper, we propose a new MIMO data transmission scheme, which combines Single-Frequency-Network (SFN) with TDD-OFDM-MIMO applied for wireless LAN networks. In our proposal, we advocate to use SFN for multiple access points (MAP) MIMO data transmission. The goal of this approach is to achieve very high channel capacity in both LOS and non line of sight (NLOS) environments. The channel capacity of the proposed method is derived for the direct path environments and it confirms the effectiveness of the proposed scheme in the LOS scenario. Moreover, solid computer simulation results confirm the effectiveness of the proposed method in both, single user and multiuser scenarios.     

Capacity enhancement in coherent optical MIMO (COMIMO) multimode fiber links

In this paper, we study a coherent optical MIMO (COMIEMO) multi-mode fiber link proposed for enhancing the fiber information capacity. We examine the statistical characterization of the equivalent MIMO channel and the improvement in the fiber capacity due to MIMO transmission. It is shown that the equivalent channel behaves similarly to a complex Gaussian MIMO channel, suggesting that the available results on wireless MIMO communication systems can be applied to optical fiber links for capacity enhancement.     

Maximum-throughput delivery of SVC-based video over MIMO systems with time-varying channel capacity

In this paper, we present a novel scalable video transmission strategy over multi-input multi-output (MIMO) wireless systems with time-varying channel capacity. It is a great challenge to simultaneously guarantee the QoS for video delivery and maximize the system throughput over time-varying MIMO channel. We demonstrate that, by making full use of estimated channel state information (CSI) through feedback, a cascade of adaptive operations can be designed to satisfy maximum throughput for scalable video over MIMO systems. These operations include power allocation based on water-filling (WF), adaptive channel selection (ACS), and novel throughput maximizing power reallocation (PR). The proposed ACS transmission scheme enables overall increase in data throughput among enhancement layers by adaptively launching base layer bit-stream to proper sub-channel. Then, after initial power allocation with WF and proper adaptive mode selection, we obtain the surplus power across enhancement layer sub-channels which can be reallocated to some sub-channels by the proposed PR scheme. With such power reallocation, certain enhancement layers will be able to reach new level of QAM modulation through PR so as to maximize the system data throughput. We present in this paper some detailed analysis on these adaptive operations. We also present some simulation results to demonstrate that maximum throughput video transmission over MIMO wireless systems indeed can be achieved based on scalable video coding (SVC) and a sequence of appropriately designed adaptive operations.     

Design Guidelines for Training-Based MIMO Systems With Feedback

In this paper, we study the optimal training and data transmission strategies for block fading multiple-input multiple-output (MIMO) systems with feedback. We consider both the channel gain feedback (CGF) system and the channel covariance feedback (CCF) system. Using an accurate capacity lower bound as a figure of merit that takes channel estimation errors into account, we investigate the optimization problems on the temporal power allocation to training and data transmission as well as the training length. For CGF systems without feedback delay, we prove that the optimal solutions coincide with those for nonfeedback systems. Moreover, we show that these solutions stay nearly optimal even in the presence of feedback delay. This finding is important for practical MIMO training design. For CCF systems, the optimal training length can be less than the number of transmit antennas, which is verified through numerical analysis. Taking this fact into account, we propose a simple yet near optimal transmission strategy for CCF systems, and derive the optimal temporal power allocation over pilot and data transmission.     

Near-optimum soft decision equalization for frequency selective MIMO channels

In this paper, we develop soft decision equalization (SDE) techniques for frequency selective multiple-input multiple-output (MIMO) channels in the quest for low-complexity equalizers with error performance competitive to that of maximum likelihood (ML) sequence detection. We demonstrate that decision feedback equalization (DFE) based on soft-decisions, expressed via the posterior probabilities associated with feedback symbols, is able to outperform hard-decision DFE, with a low computational cost that is polynomial in the number of symbols to be recovered and linear in the signal constellation size. Building on the probabilistic data association (PDA) multiuser detector, we present two new MIMO equalization solutions to handle the distinctive channel memory. The first SDE algorithm adopts a zero-padded transmission structure to convert the challenging sequence detection problem into a block-by-block least-square formulation. It introduces key enhancement to the original PDA to enable applications in rank-deficient channels and for higher level modulations. The second SDE algorithm takes advantage of the Toeplitz channel matrix structure embodied in an equalization problem. It processes the data samples through a series of overlapping sliding windows to reduce complexity and, at the same time, performs implicit noise tracking to maintain near-optimum performance. With their low complexity, simple implementations, and impressive near-optimum performance offered by iterative soft-decision processing, the proposed SDE methods are attractive candidates to deliver efficient reception solutions to practical high-capacity MIMO systems. Simulation comparisons of our SDE methods with minimum-mean-square error (MMSE)-based MIMO DFE and sphere decoded quasi-ML detection are presented.     

Multiuser MIMO receivers for space frequency block coded SC‐FDMA systems

Single carrier‐frequency division multiple access (SC‐FDMA) has been adopted as the uplink transmission standard in fourth generation cellular network to enable the power efficiency transmission in mobile station. Because multiuser MIMO (MU‐MIMO) is a promising technology to fully exploit the channel capacity in mobile radio network, this paper investigates the uplink transmission of SC‐FDMA systems with orthogonal space frequency block codes (SFBC). Two linear MU‐MIMO receivers, orthogonal SFBC (OSFBC) and minimum mean square error (MMSE), are derived for the scenarios with limited number of users or adequate receive antennas at base station. In order to effectively eliminate the multiple access interference (MAI) and fully exploit the capacity of MU‐MIMO channel, we propose a turbo MU‐MIMO receiver, which iteratively utilizes the soft information from maximum a posteriori decoder to cancel the MAI. By the simulation results in several typical MIMO channels, we find that the proposed MMSE MU‐MIMO receiver outperforms the OSFBC receiver over 1 dB at the cost of higher complexity. However, the proposed turbo MU‐MIMO receivers can effectively cancel the MAI under overloaded channel conditions and really achieve the capacity of MU‐MIMO channel. Copyright © 2014 John Wiley & Sons, Ltd.     

Experimental validation of analytical MIMO channel models

The promise of multiple-input multiple-output systems (MIMO) to overcome the radio bottleneck in high-speed data transmission requires detailed models of the spatio-temporal MIMO channel to come true. In this paper, popular MIMO channel models are compared with two independent measurement campaigns at 2 and 5 GHz by using four different, mostly novel performance figures (or metrics). Each of these metrics describes one or more different aspects of MIMO, such as multiplexing gain, spatial diversity, or beamforming. Of the models investigated, the Weichselberger model performs overall best, whereas the Kronecker model should be used only for limited antenna numbers, such as 2 × 2, and “the virtual channel representation” only for very large antenna numbers.     

一种基于深度学习的FDD大规模MIMO系统CSI反馈方法

针对频分双工（Frequency Division Duplexing,FDD）大规模多入多出（Multiple-Input Multiple-Output,MIMO）系统中现有信道状态信息（Channel State Information,CSI）反馈方法复杂度高、反馈精度低的问题,本文提出一种基于深度学习的CSI压缩反馈方法.该方法首先采用卷积神经网络（Convolutional Neural Network,CNN）提取信道特征矢量,然后利用最大池化（Maxpooling）网络压缩CSI,最后考虑到大规模MIMO信道存在空间相关性的特点,分别对单用户和多用户场景使用双向长短期记忆（Bidirectional Long Short-Term Memory,Bi-LSTM）网络和双向卷积长短期记忆（Bidirectional Convolutional Long Short-Term Memory,Bi-ConvLSTM）网络对CSI进行重构.本文利用大规模MIMO信道数据对所提的深度学习网络进行离线训练,该网络学习到的信道信息能充分表征信道的状态.仿真结果表明,与已有的典型CSI反馈方法相比,本文所提方法反馈精度更高,运行时间更短,系统性能提升明显.     

基于多项式内插的MIMO时间-频率双选择性信道的信道估计

数据的高速率传输以及终端的高速移动,导致无线通信信道具有时间选择性与频率选择性两个特征。该文主要研究了数据分组传输方式下,基于导频符号辅助调制(PSAM)的多输入多输出(MIMO)时间-频率双选择性信道的信道估计问题。首先,将时间-频率双选择性MIMO信道,建模为一个随时间变化的多项式内插信道模型;然后,根据信道Doppler衰落速率、多项式模型中的误差项,确定出模型的阶数以及整个数据块的长度;最后,基于该多项式内插信道模型,提出了采用PSAM的MIMO双选择性信道估计方法。实验结果表明该算法在时间-频率双选择性衰落信道下具有较好的性能。     

On the cooperative MIMO communication for energy-efficient cluster-to-cluster transmission at wireless sensor network

Energy-efficient data transmission is one of the key factors for energy-efficient wireless sensor networks (WSN). Cooperative multiple input multiple output (MIMO) explores the wireless communication schemes between multiple sensors emphasizing the MIMO structure. In this paper, an energy-efficient cooperative technique is proposed for a WSN where selected numbers of sensors at the transmitting end are used to form a MIMO structure wirelessly connected with a selected number of sensors at the receiving end. The selection of nodes in the transmitting end is based on a selection function, which is a combination of channel condition, residual energy, inter-sensor distance in a cluster, and geographical location, whereas the selection in the receiving side is performed on the basis of channel condition. Data are sent by the sensors in a cluster to a data-gathering node (DGN) using a multihop transmission. We are concentrating our design on the intermediate hop, where sensors in a cluster transmit their data to the sensors in another cluster with MIMO communication. Energy models are evaluated for both correlated and uncorrelated scenarios. The delay model of the proposed cooperative MIMO is also derived. Experimental results show that the selected MIMO structure outperforms the unselected MIMO in terms of total energy consumption. They also show energy-efficient performance by around 20% over unselected MIMO when they are compared with single-input-single-output structure. Also, the proposed approach takes around 50 more rounds than the geographically selected approach before dying at distance d?>?20 m.     

Joint channel estimation and turbo equalisation for MIMO-OFDM-IM systems

Multiple-Input Multiple-Output (MIMO) communications are frequently employed to improve the transmitted data rate and the link quality. Index modulated orthogonal frequency division multiplexing (OFDM-IM) improves the error rate performance and the peak-to-average power ratio (PAPR) compared with those of the conventional OFDM system due to the activation of partial subcarriers. The MIMO OFDM-IM can transmit additional information bits via the indices of active subcarriers. Also, in order to reduce the transmission power of the OFDM system, the MIMO OFDM-IM scheme can be employed to approach the demanded data transmission rate and the error rate performance. Multiple-input multiple-output orthogonal frequency division multiplexing index modulation (MIMO-OFDM-IM) is an effective multicarrier transmission scheme and can be proposed as an alternative to conventional MIMO-OFDM system. In this scheme, OFDM-IM is combined with MIMO transmission to take the benefits of these two techniques. In this paper, we propose a joint channel estimation and turbo equalisation receiver for MIMO-OFDM-IM system. Some simulation examples are given to demonstrate the effectiveness of the proposed receiver.     

基于序贯蒙特卡罗滤波的MIMO快时变信道跟踪

高数据传输速率以及终端的高速移动,导致无线通信信道具有时间选择性与频率选择性两个特征.本文主要研究了基于训练序列的多输入多输出（MIMO）时变频率选择性衰落信道的估计与跟踪问题.首先,根据时变无线信道的动态性,将信道冲击响应近似看作一个低阶的自回归矢量过程（AR）,以便于进行时变信道的跟踪.接着在此模型的基础上,利用序贯蒙特卡罗滤波对MIMO通信系统中的双选择性信道进行了跟踪;跟踪过程中需要与信号检测交替进行,即在状态变量的预测和新息修正的中间要进行一次码元的检测,所采用的方法是极大似然序列检测,最后与扩展卡尔曼滤波作了比较.仿真结果表明,在信道噪声是非高斯的情形下,序贯蒙特卡罗滤波的跟踪性能更优越于扩展卡尔曼滤波.     

An optimal scheduling and routing under adaptive spectrum-matching framework for MIMO systems

Multi-users (MUs) along the communication links cause noise and traffic in the channel. The prediction of availability and the optimal usage of channels are the main objectives of the multi-input multi-output (MIMO) system. Several optimisation algorithms select the optimal channel for the users effectively. But the high-error rate and the probability values are the two major problems in traditionally optimised channel selection methods. The bandwidth allotted for information transmission is minimum. Moreover, the outage probability values are maximum in traditional scheduling algorithms. This paper proposes the new optimisation algorithm that predicts the channels for transmission and adaptive spectrum matching concept to predict the suitable channel from allocated bands. Also, the prioritisation on high-spectrum intensity basis assures an efficient data delivery to the receiver. The scheduling of available channels and data prioritisation minimises the error probability rates. This paper investigates the effectiveness of proposed optimal channel utilisation against the different modulation schemes such as three-dimensional complementary codes, linear network coding with the quadrature phase shift keying in terms of the average block error probability and bit error rate.     

无线通信系统的MIMO信道测量与建模

在多径信道中,使用多天线的M IMO(多输入多输出)无线系统能够比单天线系统提供更高的信道容量,而信道测量与建模是决定通信性能的一个重要因素。文中对目前国际范围内现有的M IMO信道测量和建模进行了研究,并进行了归纳和分类,同时分析了M IMO信道测量和建模的方法,指出了目前信道测量和建模中存在的问题,并给出了一些针对M IMO信道测量系统设计的建议。     

Spatio-temporal channel characterization: theoretical framework and applications in MIMO system design

The utilization of multiple antennas and space–time codes in multiple-input and multiple-output (MIMO) communication systems significantly improves the transmission channel capacity without using additional bandwidth and power. The improvement is achieved by decomposing the spatial structure of transmission channels and performing appropriate temporal and spatial multiplexing. In this paper, we propose a novel theoretical framework for MIMO channel modeling and characterization in order to facilitate the MIMO system design and performance evaluation. The channels are represented in space, time, wave vector, and frequency domains while the space–time and wave vector–frequency interdependences are considered. A realization of the theoretical framework, in a form of a practical framework, is also proposed to address the channel modeling and characterization at both transmitter and receiver sides. The utilization of the practical framework in MIMO communication system design is discussed to illustrate its applications in realistic scenarios. The angle of arrival estimation based on the proposed practical framework using field test measurement data is also presented as illustrative examples.     

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.     

Filter Bank precoding for FIR equalization in high-rate MIMO communications

In this paper, the problem of designing finite-impulse-response (FIR) equalizers for multiple-input multiple-output (MIMO) FIR channels is considered. It is shown that an arbitrary MIMO frequency-selective channel can be rendered FIR equalizable by a suitable filter bank (FB) precoding operation that introduces redundancy at the transmitter. The expression for the minimum redundancy required to ensure FIR invertibility is derived. The analysis is extended to the case of MIMO multicarrier modulation. Optimum zero-forcing (ZF) and minimum mean-squared error (MMSE) solutions for the FIR equalizer are derived. Simulation results are provided to demonstrate that the proposed scheme achieves better performance than the block-processing methods while supporting a higher data rate.     

Dynamic Resource Allocation for Scalable H.264/AVC Video Transmission over MIMO Wireless Systems

In this study, a channel selection algorithm is proposed to enhance the transmission rate for scalable video coding (SVC) source transmission over multi-input multi-output (MIMO) wireless systems. The proposed algorithm allows each layer of SVC video to choose its appropriate channel in wireless MIMO systems based on channel state information for transmission rate enhancement. Here, this difficult problem is converted into mathematical optimization problem to improve the performance of SVC video transmission. Experimental results show that the transmission rate of the proposed method outperforms the existing scheme.