Quantized Principal Component Selection Precoding for Spatial Multiplexing with Limited Feedback

In this paper, for spatial multiplexing with limited feedback, a quantized principal component selection (QPCS) precoding scheme is proposed that achieves comparable capacity to the closed-loop multiple-input multiple-output (MIMO) and furthermore adapts to various fading channel conditions without any additional feedback bits and transmit channel state information (CSI). We propose a systematic design method for a codebook consisting of a finite number of unitary matrices based on a maximizing minimum distance criterion in the one- dimensional angular domain and show that the method outperforms the Grassmannian subspace packing method in various fading channel conditions. The proposed QPCS precoding scheme allows for adjustment of the precoding matrix based on limited feedback information on the principal vectors approximating a MIMO channel in the angular domain according to various channel conditions. Furthermore, for practical implementation of the QPCS precoding scheme, we propose a structured precoder optimization procedure and show that the proposed procedure induces a negligible capacity loss compared with the exhaustive precoder optimization, even with considerably reduced complexity.     

Efficient Near‐Optimal Detection with Generalized Sphere Decoder for Blind MU‐MIMO Systems

In this letter, we propose an efficient near‐optimal detection scheme (that makes use of a generalized sphere decoder (GSD)) for blind multi‐user multiple‐input multiple‐output (MU‐MIMO) systems. In practical MU‐MIMO systems, a receiver suffers from interference because the precoding matrix, the result of the precoding technique used, is quantized with limited feedback and is thus imperfect. The proposed scheme can achieve near‐optimal performance with low complexity by using a GSD to detect several additional interference signals. In addition, the proposed scheme is suitable for use in blind systems.     

Antenna selection and power control in MIMO systems with continuously varying channels

Existing limited feedback methods for Multiple- Input Multiple-Output (MIMO) systems focus largely on block fading conditions whereas, in practice, channels change continuously over time. In this paper, we investigate adaptive transmission over a continuously varying channel (CVC). A combination of Kalman channel tracking, truncated channel inversion (TCI) antenna selection, and power control, is used to achieve bit error rates that are lower than those obtained with existing schemes. Using Kalman filtering for pilot-based channel tracking as well as decision-directed channel tracking, our scheme achieves about 3.6dB gain over the eigen-mode antenna selection scheme and 1.5dB gain over the unitary precoding scheme, when operating at a BER of 10?5.     

Peak‐to‐average power ratio reduction in space–time coded MIMO‐OFDM via preprocessing

In this paper, we propose a trellis exploration algorithm based preprocessing strategy to lower the peak‐to‐average power ratio (PAPR) of precoded MIMO‐OFDM. We first illustrate the degradation in PAPR due to optimal linear precoding in MIMO‐OFDM systems. Then we propose two forms of multi‐layer precoding (MLP) schemes to reduce PAPR. In both schemes, the inner‐layer precoder is designed to optimize system capacity/BER performance. In the first MLP scheme (MLP‐I), a common outer‐layer polyphase precoding matrix is employed. In the second MLP scheme (MLP‐II), data stream corresponding to every transmit antenna is precoded with a different outer‐layer polyphase precoding matrix. Both outer‐layer precoders are custom designed using the trellis exploration algorithm by applying the aperiodic autocorrelation of OFDM data symbols as the metric to minimize. Simulation results indicate that both MLP schemes show superior PAPR performance over conventional MIMO‐OFDM with and without precoding. In addition, MLP better exploits frequency diversity resulting in BER performance gains in multi‐path environments. Copyright © 2010 John Wiley & Sons, Ltd.     

Design of Multiuser Downlink Linear MIMO Precoding Systems With Quantized Feedback

We treat the problem of sum-rate maximization via scheduling and linear precoding in multiuser (MU) multiple-input–multiple-output (MIMO) systems with quantized feedback. We formulate the optimal quantized linear precoder design problem and provide the numerical procedure for finding the solution. We also provide a simple scheduling scheme that exploits the MU diversity gain. With the aim of sum-rate maximization, we further address the quantization codebook design based on the capacity measure by introducing a new distance metric. It is demonstrated that, with or without scheduling, the proposed optimal linear precoding scheme achieves significant gain over the conventional linear precoder designs with similar feedback overhead, such as the zero-forcing precoder. Moreover, although the proposed quantization codebook design improves the performance of other existing MU-MIMO precoding schemes, the performance gain offered by it is typically much higher when it is coupled with the proposed linear precoding design.      

Experiments on MIMO-OFDM system combined with adaptive beamforming based on IEEE 802.16e WMAN standard

This paper presents field experiments on a Multi-Input Multi-Output (MIMO) system that combines Adaptive Beamforming (ABF) and Spatial Multiplexing (SM) procedures. The combination of SM signal processing with ABF is applied to WiBro, the South Korean Orthogonal Frequency Division Multiplexing (OFDM) system that follows the IEEE 802.16e standard. The field experimental results show that ABF-MIMO OFDM system outperforms a simple MIMO OFDM system by 2 dB (1.5 dB) in the signal to noise ratio (SNR) for 16-QAM (64-QAM) under low correlated fading channel and 4 dB (2.5 dB) in the SNR for 16-QAM (64-QAM) under highly correlated fading channel, respectively, at the frame error rate (FER) of 1%. Details on the implementation of ABF-MIMO OFDM system is also presented in this paper. Through the system implementation and its field experimental results, we verify that the combination of MIMO OFDM system with ABF provides improved performance over a simple MIMO OFDM system in real propagation channel environment and, in particular, it is more effective in highly correlated fading channel.     

Approximate Minimum BER Power Allocation for MIMO Spatial Multiplexing Systems

Precoding for multiple-input multiple-output (MIMO) spatial multiplexing generally requires high feedback overhead and/or high-complexity processing. Simultaneous reduction in transmitter complexity and feedback overhead is proposed by imposing a diagonal structural constraint to precoding, i.e., power allocation. Minimum bit-error rate (MBER) is employed as the optimization criterion, and an approximate MBER (AMBER) power-allocation algorithm is proposed for a variety of receivers, including zero-forcing (ZF), successive interference cancellation (SIC), and ordered SIC (OSIC). While previously proposed precoding schemes either require ZF equalization for MBER, or use a minimum mean-squared error (MMSE) criterion, we provide a unified MBER solution to power allocation for ZF, SIC, and OSIC receiver structures. Improved error-rate performance is shown both analytically and by simulation. Simulation results also indicate that SIC and OSIC with AMBER power allocation offer superior performance over previously proposed MBER precoding with ZF equalization, as well as over MMSE precoding/decoding. Performance under noisy channels and power feedback is analyzed. A modified AMBER algorithm that mitigates error propagation in interference cancellation is developed. Compared with existing precoding methods, the proposed schemes significantly reduce both transmit processing complexity and feedback overhead, and improve error-rate performance     

Improved Multiuser MIMO Unitary Precoding Using Partial Channel State Information and Insights from the Riemannian Manifold

Multiple-input multiple-output (MIMO) systems can be leveraged to increase capacity in fading channels. Especially in multiuser downlink communication systems, it has been shown that knowledge of channel state information at the transmitter (CSIT) is critical to leverage the capacity gain available from multiple antennas. When duplexing is performed using time division, CSIT can often be successfully obtained when channel reciprocity is available. CSIT acquisition, however, is much more difficult in frequency division duplexing. Sending feedback on the uplink has been shown to be a powerful technique to improve downlink performance in single user MIMO systems. The basic idea is to restrict the CSIT to a B bit codebook so that the mobiles can easily transmit these bits on the uplink. In this paper, we consider the multiuser downlink model with unitary precoding when there is a codebook consisting of 2^B unitary matrices that the precoder is restricted to lie in. This codebook is designed offline and known to both the basestation and all users. Each user sends back signal-to-interference plus noise ratio (SINR) information along with binary feedback about the unitary precoder. Based on the CSIT received on the uplink, the basestation selects one of the unitary matrices in the codebook to maximize the sum-rate. For this set-up, we first analyze the sum-rate performance of the unitary precoding scheme. We then show that the codebook of unitary precoders represents a collection of points in a special kind of manifold and show how the achievable sum-rate performance relates to the minimum distance of the codebook points in this space. Finally, we present a framework for constructing the codebook to maximize this minimum distance. Monte Carlo simulation results are presented to show the sum-rate performance of the proposed codebook design.     

Performance analysis of linear precoding based on field trials results of MIMO-OFDM system

We use field trial results obtained from a multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) wireless system with two transmitter and three receiver antennas (2/spl times/3), to first validate the properties of the transmit correlation matrix in a macro-cellular environment. We find that approximately 20% of the locations have well-defined transmit correlation matrices. Furthermore, the eigenvectors of the transmit correlation matrix vary slowly over distance with 60% of the locations having eigenvector variation of less than 1 dB over a distance of 20 m. Next, we quantify the performance of the optimal statistical linear precoding (OSLP) , and statistical one-dimensional (1-D) eigenbeamforming (SEB) based on transmit correlation matrices, and the 1-D eigenbeamforming (EB)-based on perfect channel knowledge at the transmitter. We find that the OSLP and SEB schemes obtain array gain over the Alamouti scheme at lower signal-to-noise ratio (SNR) with a median gain of 2.0 (1.5) dB at the 1.0-(3.5) km cell-radii. However, the SEB scheme (unlike the OSLP scheme) looses diversity order at higher SNR that leads to a performance loss. The EB scheme provides the best performance over the Alamouti scheme, at the expense of increased feedback requirements.     

Improved 16-QAM constellation labeling for BI-STCM-ID with the Alamouti scheme

We design constellation labeling maps for bit-interleaved space-time coded modulation with iterative decoding (BI-STCM-ID) over Rayleigh block-fading channels using the Alamouti scheme and N/sub r/ receive antennas. To achieve the largest asymptotic coding gain from the constellation labeling, we propose a new design criterion that maximizes the (-2N/sub r/)-th power mean of the squared Euclidean distances associated with all "error-free feedback" events in the constellation. Based on this power mean criterion, we show that the labeling optimization problem falls into the category of quadratic assignment problems. We propose two novel 16-QAM labeling maps that are particularly designed for N/sub r/=1 and N/sub r/=2, respectively. Numerical results show that both labeling maps achieve about 1 dB coding gain over the conventional 16-QAM modified set partitioning labeling.     

Cellular Downlink Performance with Covariance-CSIT-Based MIMO Precoding

The nature of the trade-off between reduced overhead of channel state information (CSI) and resultant performance losses influences the design of frequency-division duplexed practical cellular systems. One candidate for CSI feedback reduction is the use of covariance-matrix-based CSI at the transmitter (CSIT) in conjunction with linear precoding techniques. This paper analyzes the performance of such systems in the downlink for both single-user (SU-) and multiuser (MU-) multiple-input multiple output (MIMO) in comparison to those using optimal perfect-instantaneous-CSIT-based precoding. In addition, the effectiveness of techniques enforcing frequency domain diversity versus those based on the maximal ergodic channel capacity criterion is evaluated. A novel precoding scheme using covariance matrix information that supports spatial multiplexing in both SU- and MU-MIMO is proposed. Simulation results show that the spectral efficiency loss from covariance-CSIT-based techniques from those utilizing perfect, instantaneous CSIT is shown to be about 1 dB in a highly correlated urban channel environment for both SU- and MU-MIMO, whereas for microcell environments it is between 3 and 4 dB.     

3D MIMO系统下水平和垂直维联合预编码的研究

第五代(5G)移动通信网络将会在很大程度上提高无线通信的速率。由于多入多出系统(MIMO)能够满足5G网络中对信息速率越来越高的要求,现在正受到广泛的关注。然而,传统意义的二维(2D)MIMO技术仅仅能控制水平维的波束。为了满足5G的需求,需要引入能同时考虑水平维和垂直维波束的三维(3D)MIMO技术。本文基于3D MIMO信道模型,在分析3D MIMO信道相关性的基础上,针对发射相关和接收相关矩阵在水平维和垂直维的分解,提出了一种利用3D MIMO信道相关性的有限反馈预编码方案。并在此基础上,结合2D MIMO信道下的DFT码本和Grassmannian码本,提出了两种新的3D MIMO信道下的码本。实验结果表明,提出的3D MIMO预编码方案整体性能优于传统2D MIMO和现有的3D MIMO预编码方案。在3D MIMO系统中,由于可以动态调节天线的下倾角,故充分发掘了空间三维自由度。3D MIMO预编码技术减小小区间干扰,增加了系统容量,有效地提高了整个通信系统的性能。      

两跳中继分布式预编码码字选择方案

针对两跳分布式预编码MIMO中继系统,为了克服码字选择复杂度较高的缺点,提出一种基于单跳信道右奇异特征向量反馈的最小距离准则码本选择策略。首先给出基于均方误差矩阵的两跳分布式预编码设计方法,选取单跳信道右奇异特征向量作为反馈量,利用RVQ码本对其量化,最后采用最小距离准则对码字进行选择。仿真结果表明,在反馈比特数目相同的情况下,得到的系统BER性能与现有算法相近,但系统的和速率性能优于已有算法,且计算复杂度降低大约一半。     

一种基于GMD分解的混合预编码算法

提出了毫米波大规模MIMO系统中一种利用几何均值分解(GMD)设计模拟和数字预编码矩阵的算法.首先根据初始模拟预编码矩阵列向量相互正交,利用GMD分解计算出模拟预编码矩阵后,取其元素相位构成的矩阵为最终的模拟预编码矩阵,然后设计数字预编码矩阵.仿真结果表明,频谱效率和误码率较正交匹配追踪(OMP)算法分别有大约3dB和2.5dB的增益.     

基于粒子群算法的预编码设计

针对多用户多输入多输出系统的下行链路传输,提出了一种基于粒子群算法的预编码设计方案。该方案首先通过理论分析,推导出错误符号概率的函数,该函数是将平均符号错误概率构造为预编码矩阵和各用户信道信息的函数,并以最小符号错误概率为判断准则。然后利用模拟鸟群觅食的粒子群方法对其进行优化搜索,得到最佳效果。理论分析与仿真结果表明,该方案性能比传统的预编码性能更优。     

A Novel Uplink MIMO Transmission Scheme in a Multicell Environment

Uplink multiple-input multiple-output (MIMO) transmission scheme is developed for time division duplex (TDD) systems in a multicell environment. We propose a precoding scheme that maximizes the total achievable rate and works in the decentralized manner with only locally available channel state information (CSI) at each transmitter. We first establish and solve a decentralized optimization problem for the case of multiple-input single-output (MISO) channels, introducing a new precoding design metric called signal to generated interference plus noise ratio (SGINR). By extending the result to general MIMO channels, we propose an SGINR-based precoding scheme where the number of transmit streams is selected adaptively to the surrounding environments. Simulation results confirm that the proposed precoding scheme offers significant throughput enhancement in multicell environments.     

Design of reduced complexity feedback precoding for MIMO‐OFDM

Beamforming technique is applied to significantly increase the performance of a MIMO system, if the channel information (CI) of the communication system is available at the transmitter. For the transmitter to obtain the entire CI, however, a considerable reverse‐link bandwidth is required. To save the bandwidth, a limited‐rate closed‐loop system, therefore, uses a predetermined codebook which is derived from the CI. The codebook consists of a finite number of precoders out of which the index of the best one is transmitted from the receiver to the transmitter using only a few bits saving substantial bandwidth. However, the amount of bits that need to be fed back can still be significantly large for MIMO‐OFDM systems when the precoding matrix index (PMI) for each subcarrier should be transmitted. Such per‐subcarrier precoding scheme has high feedback overhead and also incurs huge computational cost to determine the best PMI for each subcarrier. We, therefore, propose a per‐band precoding scheme that precodes a band (group) of subcarriers by only one precoder. More importantly, we develop, for the proposed per‐band scheme, reduced‐complexity precoding selection methods that lead to the design of efficient receivers. The effectiveness of the proposed scheme is investigated through computer simulations. Copyright © 2014 John Wiley & Sons, Ltd.     

Joint precoding and scheduling algorithm for massive MIMO in FDD multi-cell network

Massive multiple-input multiple-output (MIMO) systems, in which base stations are equipped with a large number of antennas in a two-dimensional antenna array, is one of the most promising technologies to improve the spectral efficiency of the fifth generation mobile communication systems (5G). Since there is no short-term channel reciprocity, the frequency-division duplexing (FDD) massive MIMO system has to obtain channel state information with the help of uplink feedback with acceptable overhead. To cope with this issue, we propose the design of joint precoding and scheduling algorithm in FDD multi-cell network. In the algorithm, all the users are firstly grouped by the statistics of channel correlation matrix, then the inter-group interference exiting among intra-cell and inter-cell is eliminated at the first precoding stage. Then users are adaptively scheduled and beamformed at the second precoding stage based on the low dimension effective channel. Finally, the effectiveness of the proposed algorithm is presented through simulations.

     

Noncooperative Multimode Precoding with Limited Feedback in MIMO Interference Channels

This letter proposes an iterative multimode precoding scheme with limited feedback for nonreciprocal MIMO interference channels. Based on analysis of game theory, we model the iterative multimode precoding as a noncooperative game with a finite set of strategies. Numerical results are presented to verify the sum rate performance of the proposed scheme.     

A Markov-Kronecker model for analysis of closed-loop MIMO systems

Closed-loop MIMO systems have gained much interest recently due to their ability in improving performance. Although many spatial-temporal MIMO channel models have been proposed, system limitations are not considered and the effects of a time varying channel on MIMO systems with a realistic feedback delay are also not available in an analytically tractable form. In this letter, we propose a composite model where both propagation and system factors are considered thus providing a simple and analytically tractable model for the performance evaluation and design of closed-loop MIMO systems.