HTRCI and Channel Ranking Based Joint Symbols Detection for MQRD-PCM/MIMO-OFDM

MIMO-OFDM is considered a key technology in emerging high-data rate systems. In MIMO-OFDM systems, channel estimation and signal detection are important to distinguish transmit signals from multiple transmit antennas. Previously, we have proposed a parallel detection algorithm using multiple QR decompositions (Q is an orthogonal square matrix, R is upper triangular matrix) with permuted channel matrix (MQRD-PCM) to reduce the system complexity of MIMO-OFDM. This method achieves a good BER performance with a low system complexity. However, since MQRD-PCM is a kind of parallel detection method, the wrong detection probability is increased due to the bad channel signal-to-interference plus noise power ratio (SINR) of the transmitted signals. As a result, the average BER performance is influenced by the wrong detection probability of the bad channel SINR. To overcome the above-mentioned problems, in this paper, we propose the high time resolution carrier interferometry and channel ranking based joint signal detection for MQRD-PCM/MIMO-OFDM.     

Broadband MIMO-OFDM wireless communications

Orthogonal frequency division multiplexing (OFDM) is a popular method for high data rate wireless transmission. OFDM may be combined with antenna arrays at the transmitter and receiver to increase the diversity gain and/or to enhance the system capacity on time-varying and frequency-selective channels, resulting in a multiple-input multiple-output (MIMO) configuration. The paper explores various physical layer research challenges in MIMO-OFDM system design, including physical channel measurements and modeling, analog beam forming techniques using adaptive antenna arrays, space-time techniques for MIMO-OFDM, error control coding techniques, OFDM preamble and packet design, and signal processing algorithms used to perform time and frequency synchronization, channel estimation, and channel tracking in MIMO-OFDM systems. Finally, the paper considers a software radio implementation of MIMO-OFDM.     

New List Sphere Decoding (LSD) and Iterative Synchronization Algorithms for MIMO-OFDM Detection With LDPC FEC

New sphere decoding and synchronization algorithms for multiple-input–multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems are proposed in this paper. In particular, an iterative list branch-and-bound (BB) algorithm based on the basic BB algorithm is described to obtain a candidate list to compute soft information that is used in the iterative detector. Furthermore, an improved algorithm that uses prior information from the preceding iteration to calculate the lower bound is proposed, and the candidate list is updated every iteration. To obtain a complete modem architecture, we propose an efficient expectation–maximization (EM)-based iterative algorithm for synchronization and channel estimation to interface with the proposed list-sphere-decoding detector, and we investigate the performance of the designed MIMO-OFDM modem on a realistic fading channel. The obtained performance results show that it is possible to practically design a performing MIMO-OFDM modem with high spectral efficiency, i.e., 8 bit/s/Hz with a 4 $times$ 4 16-QAM MIMO-OFDM system.      

Superposition-based adaptive modulated space time block coding for MIMO-OFDM systems

We propose a superposition-based adaptive modulated STBC (SPAM-STBC) for MIMO-OFDM systems to improve adaptive modulation optimization of space time block coding (STBC). When transmit antennas have the different channel conditions, the previous adaptive modulated STBC selects the same modulation based on averaging of the multiple channel gains. If the different modulation is selected to each transmit antenna, the STBC decoding problem occurs. In this letter, we select the optimal modulation corresponding to each channel condition by the superpositioned space time encoding and decoding. Simulation shows the proposed SPAM-STBC scheme outperforms both the fixed and adaptive modulated STBC schemes by the maximum 0.407 bits/sec/Hz in terms of spectral efficiency.     

MIMO-OFDM快衰落信道的稀疏自适应感知估计

在多输入多输出（MIMO）-正交频分复用（OFDM） 系统中,怎样在较高频谱利用率的情况下对快时变信道进行较为准确的估计是一个具有挑战性的课题。该文在利用压缩感知理论可提高系统频谱利用率的基础上,提出了一种适合于快时变环境下MIMO-OFDM 系统的稀疏自适应信道估计方法。该方法不再受到奈奎斯特采样频率条件约束,避免了传统导频辅助信道估计方法频谱利用率低的缺点。该文方法通过构建多天线群时频结构特征稀疏基,利用多天线间和群时变OFDM符号内信道冲激响应具有更强稀疏性的特点,对MIMO-OFDM快衰落信道进行稀疏变换。由于实际MIMO-OFDM快衰落信道往往处于频率选择性、时变性和多种干扰并存的复杂环境,受到干扰的信道参数对系统而言是未知,采用该方法克服了现有基于压缩感知理论的信道估计方法需要预先知道信道冲激响应稀疏度才能重构信道参数的不足,在信道稀疏度未知道的情况下,运用稀疏自适应的方法来对不同时频结构特征的信道参数进行估计。仿真结果表明所提估计方法具有对快时变信道参数估计的鲁棒性和较高频谱利用率,且均方误差小。      

Binomial distribution based grey wolf optimization algorithm for channel estimation in wireless communication system

Several input high-data-rate transmissions over broadband wireless channels are possible using multiple input multiple output (MIMO) systems paired with orthogonal frequency division multiplexing (OFDM) technology. Channel estimation is an essential technique and a necessary component of MIMO-OFDM systems. However, the noise will be there in MIMO-OFDM due to the environment. As a result, the wireless system performs degrades in terms of bit error rate (BER). The suggested method offers a better pilot pattern strategy for MIMO-OFDM and an efficient power allocation to address this issue. The binomial distribution-based grey wolf optimization (BDGWO) algorithm is proposed to identify the optimal pilot patterns. The power is then adaptively distributed to each transmit antenna to increase the spectral efficiency and maximum channel capacity through an adaptive neuro-fuzzy inference system with a sigmoid membership function (SMFANFIS). The best pilot patterns in PDGSIP (pilot design with generalized shift invariant property) were determined using the BDGWO algorithm based on the binomial distribution. According to the simulation results, the proposed BDGWO established pilot design with generalized shift invariant property (BDGWO-DGSIP) achieves higher performance compared other existing approaches such as PDGSIP, TPDGSIP, and LS in terms of NMSE, BER, and SER. Compared to the PDGSIP technique, the proposed PDGSIP-BDGWO system minimizes NMSE at 10%, BER at about 12%, and SER at 15%.     

A phase noise mitigation scheme for MIMO WLANs with spatially correlated and imperfectly estimated channels

Applying multiple input multiple output (MIMO) technique to OFDM-based wireless local area networks (WLANs) promises impressive high capacity and spectral efficiency compared with conventional systems. However, similar to SISO-OFDM, MIMO-OFDM suffers significant performance degradation due to the presence of phase noise. Many methods have been developed to mitigate phase noise for a single antenna system with perfect channel estimation, whereas none has been proposed for correlated MIMO-OFDM scenarios. Therefore, in this letter, by using the phase noise correlation function, a new phase noise mitigation scheme is proposed for the general M/sub T//spl times/M/sub R/ MIMO WLANs system with channel estimation errors. Numerical results show that, compared with conventional approaches, the proposed scheme achieves significant performance gain with high spectral efficiency, requiring few pilots, and is robust to spatial correlation and channel estimation errors, which makes it very attractive for practical applications.     

Unsupervised Optimization for Universal Spatial Image Steganalysis

This paper presents adaptive per-spatial stream power allocation algorithms for Single User Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (SU MIMO-OFDM) systems. Three efficient and low-complexity Greedy Power Allocation (GPA) algorithms are proposed to maximize the throughput and spectral efficiency of the SU MIMO-OFDM systems. Firstly, the low-complexity pre-coded GPA algorithms are developed for the MIMO systems. The spatial sub-channels are created by applying the so-called Singular Value Decomposition (SVD) technique on the MIMO channel matrix, and then the Pre-GPA algorithms are applied to exploit the multi-path and spatial diversities. Secondly, the spatial and frequency diversities are exploited by adaptively allocating the system sub-carriers to the spatial sub-channels followed by Per-Spatial GPA (PSGPA). Finally, spatial multiplexing-based GPA algorithms are proposed to optimize the spectral efficiency of the SU MIMO-OFDM system. An optimal two-dimensional Spatial-Frequency GPA (SFGPA) algorithm is proposed to efficiently improve the average system spectral efficiency. The high computational complexity of the optimal SFGPA solution is simplified by proposing a low-complexity Per-Spatial GPA with Excess Power Moving down (PSGPA-EPMd) algorithm, which moves the per-spatial excess power downwards to enhance the spectral efficiency of the spatial multiplexing-based SU MIMO-OFDM systems. The proposed algorithms achieve better spectral efficiency and maximize the throughput in comparison with conventional algorithms.     

Adaptive Blocker Rejection Continuous-Time $Sigma Delta $ ADC for Mobile WiMAX Applications

An adaptive blocker-rejection wideband continuous-time (CT) sigma-delta (SigmaDelta) analog-to-digital converter (ADC) is presented. An integrated blocker detector reconfigures the ADC loop architecture to avoid overloading in the presence of strong interferers, improving receiver channel selectivity and sensitivity without increasing its dynamic range (DR) requirements. The adaptive operation relaxes receiver baseband channel filtering requirements for a worldwide inter-operability for microwave access (WiMAX, IEEE 802.16e) receiver. The ADC achieves 71 dB of dynamic range (DR), 65 dB of peak SNDR and 68 dB of peak SNR over a 10 MHz signal bandwidth, consuming 18 mW from a 1.2 V supply. The ADC system reconfigures the loop filter topology within 51 mus, improving receiver selectivity without any transient impact on BER. In the blocker suppression mode, the ADC can withstand 30 dBc blocker at the adjacent channel, achieving - 22 dB error vector magnitude (EVM) with a 24 Mb/s 16-QAM signal. The IC is fabricated on a 130 nm 8-level metal, metal-insulator-metal (MIM) capacitor, CMOS technology, occupying 1.5 times 0.9 mm² silicon area.     

MIMO-OFDM系统中基于迭代MAP算法的RLS信道估计

该文提出了一种适用于MIMO-OFDM系统的迭代最大后验概率(Iterative-MAP)信道估计算法。接收机利用MAP译码算法中的信息位和校验位软信息,经过非线性映射将信息反馈至信道估计模块,采用递归最小二乘(RLS)自适应滤波算法对信道时变状态参数进行跟踪,提高了信道估计的精度。仿真结果表明,该方法与最小二乘(LS)算法相比,估计的均方误差(MSE)和误帧率(FER)性能都有较大改善。     

Approaching the Zero-Outage Capacity of MIMO-OFDM Without Instantaneous Water-Filling

Orthogonal-frequency-division multiplexing (OFDM) transforms a frequency-selective multiple-input multiple-output (MIMO) fading channel into a MIMO-OFDM channel that has a well-defined outage capacity. A transmitter with channel knowledge can achieve this capacity by a combination of eigenbeamforming and water-filling; the eigenbeamforming transforms the MIMO-OFDM channel into a parallel bank of scalar channels, and the water-filling procedure optimally allocates rate and energy to the scalar channels - a form of adaptive modulation. This paper shows that the water-filling procedure is not necessary to approach the zero-outage capacity of the MIMO-OFDM channel; it is sufficient instead to use a combination of eigenbeamforming and a fixed (nonadaptive) rate allocation. The fixed allocation depends only on the statistics of the channel and is independent of the particular channel realization. This paper proves that the capacity penalty incurred by the fixed allocation approaches zero as the number of antennas grows large. Numerical results indicate that the convergence is fast; for example, the fixed allocation suffers an SNR penalty of less than 0.2 dB for a 6-input 6-output Rayleigh-fading MIMO-OFDM channel at 8 bits per signaling interval, when the channel is assumed to be uncorrelated between antennas and between channel taps. A main conclusion is that eigenbeamforming is the most valuable way to exploit knowledge of the channel at the transmitter, and that any subsequent adaptive modulation has minimal relative value.     

MIMO-OFDM系统中LDPC编码和自适应比特功率分配算法研究

该文提出了将LDPC码与自适应比特功率分配相结合应用于MIMO-OFDM系统中的算法。文中分别对两种不同码率的LDPC码与自适应OFDM,自适应MIMO-OFDM相结合的算法进行了仿真,同时还对未编码的自适应OFDM以及MIMO-OFDM进行了仿真。仿真结果显示,在相同的传输带宽以及相同的传输信息量（即数据净码率）情况下,采用低码率LDPC编码的自适应OFDM系统的性能要比未编码的自适应OFDM以及自适应 MIMO-OFDM系统的性能好;采用高码率LDPC编码的自适应OFDM系统的性能比未编码的自适应OFDM系统性能好,但比未编码的自适应MIMO-OFDM系统性能差。     

Inter-Frame, Fine Frequency/Phase Synchronization forSimple Space-Time-Coded OFDM Receivers

This paper proposes an enhanced receiver (Rx) configuration for multiple-input, multiple-output (MIMO) OFDM systems, operating under the composite effect of phase noise (PHN), residual frequency offset (RFO) and the transmission channel, herein modeled as quasi-static but unknown. The proposed Rx identifies the different impairments by exploiting their different time constants and compensates for each one accordingly. It includes a novel inter-frame fine frequency synchronization (FFS) scheme, which is closely coupled to an intra-frame adaptive phase synchronizer/channel estimator. The proposed scheme is evaluated for a 2 times 2, Alamouti space-time code (STC), and is shown to provide significant performance gain. The theory can be employed with any other STC scheme.     

Comments on "channel estimation and signal detection for MIMO-OFDM with time varying channels"

It is shown in (W.G. Song and J.T. Lim, 2006) that the proposed least squares channel estimator for multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) systems will acquire improved performance as the polynomial order increases, which we find is not generally the case. Analyses and simulation results are given to support our claim.     

RF power and I/Q imbalance calibration in B3G/4G MIMO-OFDM systems

Radio frequency (RF) front-end nonidealities in multi-input and multi-output (MIMO) systems are more serious than in single-input and single-output systems and must be calibrated. According to the effects of RF power and in-phase/quadrature-phase (I/Q) imbalance, calibration methods for multi-input and multi-output-orthogonal frequency division multiplexing (MIMC-OFDM) systems in transmitter and interference in receiver are improved, respectively, in this article. Furthermore, a calibration scheme including I/Q imbalance errors and amplitude variations is proposed and implemented in the B3G/4G time division duplex communication system. Simulation results show that the calibration algorithms are feasible, and the bit error rate (BER) performances for MIMO-OFDM systems are improved after calibrations.     

MIMO-OFDM系统信道估计算法综述

MIMO-OFDM技术是近年来通信信号处理领域的研究热点,无线信道不仅是频率选择性的,而且是时变的,为了获得较高的系统性能,信道估计就显得尤为重要.对MIMO-OFDM系统中现有的信道估计算法进行了综述,重点介绍了基于训练序列的、导频符号的以及盲和半盲信道估计算法.比较了各种算法的优缺点,提出了未来信道估计的发展方向.     

基于MIMO—OFDM系统的信道估计算法分析

MIMO-OFDM技术是未来无线通信系统的研究热点。信道估计是估计出信道的时域或频域响应,对接收到的数据进行校正与恢复,是实现MIMO-OFDM系统优良的传输性能的重要环节。对MIMO-OFDM系统的多种信道估计算法进行了全面深入地探讨,重点分析和比较了基于LS和MMSE的非盲信道估计算法、盲信道估计算法和半盲信道估计算法,并提出了未来信道估计算法的研究方向。     

一种基于改进ROMP的MIMO-OFDM信道估计方法

本文根据信道响应的时域稀疏性,引入压缩感知理论,针对正则化正交匹配追踪（ROMP）需已知稀疏度和原子一旦选入无法删除两大缺点,提出一种基于改进ROMP的信道估计方法.该方法结合压缩采样匹配追踪（CoSaMP）、稀疏度自适应匹配追踪（SAMP）和变步长的优点,实现稀疏信号快速准确的重建.仿真结果表明,与基于OMP、ROMP、CoSaMP、SAMP的信道估计方法相比,所提方法有效提高了MIMO-OFDM系统的归一化均方误差（NMSE）和误码率（BER）性能.     

MIMO—OFDM系统基于子空间的盲信道估计技术

MIMO-OFDM系统能在宽带无线信道中达到很高的速率。文章建立了MIMO-OFDM信道识别的条件并实现了基于子空间方法的盲信道估计技术。该方法将现存的在SISO-OFDM系统中的基于子空间的盲信道估计进行统一，并且推广到MIMO-OFDM系统中。特别是该方法可以获得信道的精确估计，且能快速收敛。仿真实验的结果显示了该方法的均方误差性能。     

Application of 32 and 16 kb/s speech encoding techniques to digital satellite communications

This paper describes the performance of various voice encoding techniques at 32 and 16 kb/s for applying to digital satellite communication systems. The subjective performances of adaptive differential PCM (ADPCM), adaptive predictive coding (APC), subband coding (SBC) and adaptive delta modulation (ADM) are compared under various satellite channel environments, that is, random and burst channel errors in satellite link and an ambient noise in the ship-to-shore direction in a maritime satellite channel. The performance of the voiceband data at 4·8 and 2·4 kb/s is also evaluated for these coders. ADPCM encoding at 32 kb/s is very attractive for conventional fixed satellite systems, keeping the equivalent quality to 64 kb/s PCM. On the other hand, APC encoding at 16 kb/s is also most suitable for maritime satellite communication systems at the sacrifice of a small degradation of speech quality.