Hybrid pilots assisted channel estimation algorithm for MIMO-OFDM systems

Abstract: A hybrid pilots assisted channel estimation algorithm for multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) systems under low signal-to-noise ratio (SNR) and arbitrary Doppler spread scenarios is proposed. Motivated by the dissatisfactory performance of the optimal pilots (OPs) designed under static channels over multiple OFDM symbols imposed by fast fading channels, the proposed scheme first assumes that the virtual pilot tones superimposed at data locations over specific subcarriers are transmitted from all antennas, then the virtual received pilot signals at the corresponding locations can be obtained by making full use of the time and frequency domain correlations of the frequency responses of the time varying dispersive fading channels and the received signals at pilot subcarriers, finally the channel parameters are derived from the combination of the real and virtual received pilot signals over one OFDM symbol based on least square (LS) criterion. Simulation results illustrate that the proposed method is insensitive to Doppler spread and can effectively ameliorate the mean square error (MSE) floor inherent to the previous method, meanwhile its performance outmatches that of OPs at low SNR region under static channels.     

降低MIMO-OFDM系统峰均比的分解并行选择映射算法

高峰均功率比(peak-to-average power ratio, PAPR)问题是多输入多输出正交频分复用(multiple-input multiple-output orthogonal frequency division multiplexing, MIMO-OFDM)系统实用化的主要障碍之一,针对这一问题提出了一种分解并行选择映射(decomposed concurrent selected mapping, D-CSLM)算法,进一步提高了算法的峰均比性能。所提算法将每根天线上OFDM 符号分解为实部和虚部,分别采用相同的相位因子,在进行逆离散傅里叶变换(inverse discrete Fourier transform, IDFT)之后进行组合,选择使所有天线具有最小平均峰均比的信号进行传输。与原有的并行选择映射算法相比,所提算法具有更大的待选信号范围,峰均比降低性能更好。同时,利用实序列固有的共轭对称特性,使算法的计算复杂度保持不变。仿真结果证明,该算法在保持计算复杂度不变的前提下,显著改善了系统的峰均比性能。     

信道参数对多天线OFDM系统的性能影响

讨论了在波束成形的多天线OFDM系统中信道反馈时延和多普勒频移所带来的信道估计误差对通信性能的影响。将信道估计误差等价为与信道参数相关的随机变量并通过Q函数的等效定义和OFDM系统中各子信道的同分步特性,推导出了多天线的OFDM系统误码率受信道反馈时延和多普勒频移影响的闭合表达式,同时仿真给出了三个发射天线、三个接收天线下的不同反馈时延和多普勒频移对通信误码率的影响,可为时变信道下的多天线OFDM系统设计提供参考。     

基于波达方向矩阵的MIMO-OFDM系统载频偏移估计

MIMO-OFDM系统中设置虚拟子载波后,时域接收符号向量与经频域信道系数加权的频域发射符号向量之间通过一个范德蒙矩阵相互联系,且该矩阵的列向量的结构决定于载频偏移量。基于此,提出了一种采用波达矩阵方法、利用范德蒙矩阵的移不变结构完成载频偏移估计的闭式频偏估计方法。该方法综合地利用了多收发天线的空域分集效应,降低了信道零点对频偏估计性能的影响,有效地提高了估计的均方误差性能。仿真结果验证了不同天线配置情况下所提出算法的性能。     

基于PTS级联抵消的峰均比抑制性能仿真

提出了PTS级联抵消算法,实现对地面数字多媒体广播系统中时域同步正交频分复用信号的峰均功率比的抑制.通过研究地面数字多媒体广播系统传输协议,分析了采用时域同步正交频分复用多载波调制方式对系统射频前端信号时域性能的影响.针对信号峰均功率比高的缺陷,提出一种新颖的峰值功率比抑制算法.该算法对峰均功率比的抑制能力强于传统PTS算法,引起的带外辐射和互调失真小于传统限幅技术.当子载波数较大时,仍可实现对系统峰均功率比的有效控制.通过仿真,与传统限幅技术相比,算法可以使地面数字多媒体广播系统的峰均功率比控制在4-5dB,比传统PTS算法峰均功率比减小约3-4dB,且仅有少量的误码率性能损失.     

基于神经网络的高并行大规模MIMO信号检测算法

随着5G和未来移动无线网络的不断发展,大规模多输入多输出(multiple input multiple output, MIMO)是其中的关键技术之一。随着天线数目的不断增加,给接收机的设计带来更高的挑战,复杂度过高的检测算法在实际中难以应用。本文将一种高并行(high-parallelism, HP)检测算法展开到神经网络中,单层神经网络基于该算法的每次迭代,并将其与可训练的权重参数和非线性神经单元相结合,提出基于网络结构HP-Net的方法。通过训练HP-Net得到最优可训练参数,进而提高检测性能。实验结果表明,所提方法相对传统最小均方误差(minimum mean square error, MMSE)算法复杂度更低,并能够得到更低的误码率;同时相对HP并行检测算法误码率性能更优。     

基于EM的MIMO-OFDM系统MAP信道估计算法

最大后验概率（maximum a posteriori, MAP）信道估计算法应用于MIMO-OFDM系统时将带来大规模矩阵求逆和乘积运算,且OFDM符号的数据传输效率随着发送天线的增多逐渐下降。针对这些弊端,提出一种基于期望最大化（expectation maximum, EM）的MAP信道估计算法,并分析了算法的性能。该算法利用EM算法把多输入输出信道估计问题化简为一系列独立的单输入输出问题,避免了大规模矩阵运算,降低了MAP算法的计算复杂度;为进一步改善MAP算法的数据传输效率及其估计性能,可通过对多个连续的OFDM符号进行联合信道估计。通过仿真实验证明了该算法的有效性。     

Efficient spread space-time block coding scheme in multiple antenna systems

1 .INTRODUCTIONRecently ,an intense interest has focused on wire-less systems that can provide good quality and highdata rate .Space-ti me coding is an i mportant tech-nique that can i mprove system performance at fa-ding environments by obtaining diversity gains andcoding gains in multiple antenna systems .To make multiple antenna system practical ,methods that can obtain diversity gains with mod-erate complexity and provide acceptable bit errorrate ( BER) performance are investigated i…     

一种基于导频的OFDM系统信道估计方法

提出一种使用矩形导频图案的OFDM信道估计方法。接收端首先在频率方向估计信道,然后在时间方向插值。该方法仅需累加和少量乘法运算就能估计出信道冲激响应,复杂度低,实时性高。在未编码16QAM-OFDM系统中,通过仿真将提出的方法与线性、cubic和MMSE插值法进行均方误差和误比特率的比较。结果表明该方法性能优于前两者,接近后者。     

MIMO-OFDM系统中基于CS-ESPRIT算法的多频偏盲估计

提出了一种基于接收信号循环平稳特性(CS)和基于旋转不变技术的参数估计方法(ESPRIT)的多输入多输出正交频分复用(MIMO-OFDM)系统多频偏盲估计算法。理论分析表明,算法无需训练序列或导频符号,可估计每对收发天线间频偏,适用于任意分布加性平稳噪声下的频偏估计。计算机仿真验证了算法在低信噪比下仍可取得稳定性能,并在传统单入单出(SISO)OFDM系统中也可获得较好的性能。     

大规模MIMO系统中分布式压缩感知LMMSE信道估计

大规模多输入多输出(multiple input multiple output,MIMO)系统中,信道估计算法复杂度随着基站侧天线数量的增加而急剧增加,针对需要在信道估计算法复杂度与算法性能之间进行折中的问题,提出分布式压缩感知线性最小均方误差(distributed compressed sensing linea...     

Compressive sensing based multiuser detector for massive MBM MIMO uplink

Media based modulation(MBM)is expected to be a prominent modulation scheme,which has access to the high data rate by using radio frequency(RF)mirrors and fewer transmit antennas.Associated with multiuser multiple input multiple output(MIMO),the MBM scheme achieves better performance than other conventional multiuser MIMO schemes.In this paper,the massive MIMO uplink is considered and a conjunctive MBM transmission scheme for each user is employed.This conjunctive MBM transmission scheme gathers aggregate MBM signals in multiple continuous time slots,which exploits the structured sparsity of these aggregate MBM signals.Under this kind of scenario,a multiuser detector with low complexity based on the compressive sensing(CS)theory to gain better detection performance is proposed.This detector is developed from the greedy sparse recovery technique compressive sampling matching pursuit(CoSaMP)and exploits not only the inherently distributed sparsity of MBM signals but also the structured sparsity of multiple aggregate MBM signals.By exploiting these sparsity,the proposed CoSaMP based multiuser detector achieves reliable detection with low complexity.Simulation results demonstrate that the proposed CoSaMP based multiuser detector achieves better detection performance compared with the conventional methods.     

Joint frequency offset tracking and PAPR reduction algorithm in OFDM systems

This paper presents an algorithm that aims to reduce the peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) communication systems while maintaining frequency tracking. The algorithm achieves PAPR reduction by applying the complex conjugates of the data symbol obtained from the frequency domain to cancel the phase of the data symbol. A likelihood estimator is used to obtain the sub-carrier phase error due to the residual carrier frequency offset (RCFO) using the same complex conjugates as a pilot signal. Furthermore, a joint time and frequency domain multicarrier phase locked loop (MPLL) is developed to compensate additional frequency offset. Simulation results show that this algorithm is capable of reducing PAPR without impacting the frequency tracking performance.     

Lattice-reduction-aided MMSE precoding for correlated MIMO channels and performance analysis

The lattice-reduction (LR) has been developed to improve the performance of the zero-forcing (ZF) precoder in multiple input multiple output (MIMO) systems. Under the assumptions of uncorrelated flat fading channel model and perfect channel state information at the transmitter (CSIT), an LR-aided ZF precoder is able to collect the full transmit diversity. With the complex LenstraLenstra-Lova′sz (LLL) algorithm and limited feedforward structure, an LR-aided linear minimum-mean-square-error (LMMSE) precoder for spatial correlated MIMO channels and imperfect CSIT is proposed to achieve lower bit error rate (BER). Assuming a time division duplexing (TDD) MIMO system, correlated block flat fading channel and LMMSE uplink channel estimator, it is proved that the proposed LR-aided LMMSE precoder can also obtain the full transmit diversity through an analytical approach. Furthermore, the simulation results show that with the quadrature phase shift keying (QPSK) modulation at the transmitter, the uncoded and coded BERs of the LR-aided LMMSE precoder are lower than that of the traditional LMMSE precoder respectively when E b / N0 is greater than 10 dB and 12 dB at all correlation coefficients.     

低轨卫星通信中SCMA系统载波同步算法设计

为了提高低轨卫星通信频谱利用率及对抗存在的大多普勒频移, 考虑将稀疏码多址接入(sparse code multiple access, SCMA)技术应用于低轨卫星通信,提出一种针对SCMA系统的数据辅助载波同步方案。该同步方案的频偏、相偏估计算法分别采用分步相关法和最大似然法。同时, 根据所提分步相关算法的特点, 优化了导频和数据组成的分布图样。仿真结果表明, 以6个用户共享4个资源块的系统为例, 基于优化帧结构的载波同步方案可以利用较少的导频开销获得比使用经典帧结构的更高估计精度和更好误码性能。     

突出重点目标跟踪的分布式MIMO雷达阵元选取

在分布式多输入多输出(multiple input multiple output, MIMO)雷达执行目标检测和跟踪多任务时, 为了在多个目标中突出对重点目标的跟踪, 提出了基于改进公平起点搜索的阵元选取模型与求解算法。在限定目标检测性能、跟踪性能和系统资源的前提下, 以最小的阵元集合为代价函数, 建立优化模型。为在同一框架下讨论系统的不同性能指标, 对参数进行预处理, 将表征跟踪性能的位置估计误差界进行去量纲化、归一化处理。分别引入表征目标重要程度和任务重要程度的权重因子, 得到表征系统综合性能的参数。遍历每一个初始阵元对, 逐次增加对系统贡献最大的阵元, 最终完成阵元集的选择。仿真结果表明, 所提算法能够提供接近穷举算法的性能并有效降低系统计算量。     

OFDM/OQAM系统限幅补偿IAM信道估计方法

基于偏移正交幅度调制的正交频分复用(offset quadrature amplitude modulation/orthogonal frequency division multiplexing,OFDM/OQAM)系统信道估计方法中,干扰近似法(interference approximation method,IAM)具有估计精度高的特点,是该系统常用的信道估计方法。然而,在OFDM/OQAM信号发送和接收过程中,高功率放大器(high power amplifier,HPA)对信号的限幅作用导致IAM信道估计精度下降。为了研究不同IAM导频结构下的系统性能受限幅影响的程度,针对导频峰均比问题,提出了局部互补累积分布函数,并研究了不同限幅门限作用下,系统比特误码率性能和信道估计归一化均方误差性能。为了补偿HPA的限幅作用对系统的影响,提出了一种导频限幅补偿方法,该方法不需要发送额外的补偿信息,仅仅需要根据导频结构计算并在接收端补偿。仿真结果验证了补偿方法的有效性,并且导频信号受限幅影响越严重,补偿效果越好。     

Resource allocation with minimum transmit power in multicast OFDM systems

To minimize the total transmit power for multicast service in an orthogonal frequency division multiplexing (OFDM) downlink system, resource allocation algorithms that adaptively allocate subcarriers and bits are proposed. The proposed algorithms select users with good channel conditions for each subcarrier to reduce the transmit power, while guaranteeing each user’s instantaneous minimum rate requirement. The resource allocation problem is first formulated as an integer programming (IP) problem, and then, a full search algorithm that achieves an optimal solution is presented. To reduce the computation load, a suboptimal algorithm is proposed. This suboptimal algorithm decouples the joint resource allocation problem by separating subcarrier and bit allocation. Greedy-like algorithms are employed in both procedures. Simulation results illustrate that the proposed algorithms can significantly reduce the transmit power compared with the conventional multicast approach and the performance of the suboptimal algorithm is close to the optimum.     

基于预编码矩阵的迭代均衡算法

针对长期演进(long time evolution,LTE)下行多输入多输出正交频分多址链路(multiple input multiple output orthogonal frequency division multiplexing, MIMO OFDM)异步通信系统中的天线间干扰和多径干扰的问题,提出一种低复杂度的基于预编码矩阵的迭代均衡算法。在发射端,该算法通过预编码矩阵将信号扩展到所有子载波上,从而降低部分子载波深衰落对扩展前原始信号的影响。在接收端,利用最小均方差误差排序QR分解(minimum mean square error sorted QR decomposition, MMSE SQRD)软输入软输出干扰消除均衡算法,一方面避免传统基于最小均方误差(minimum mean square error,MMSE)并行软干扰消除均衡算法中复杂的矩阵求逆运算,进而降低了算法复杂度,另一方面利用信道排列优先检测信噪比最大的传输符号提高检测准确性。同时通过预编码对重构信号中误差进行扩展,进而缓解在迭代干扰消除过程中的误差传播。仿真结果证明,在2发2收场景下,误码率在10^-3时,算法经过5次迭代后系统性能相比于现有的迭代均衡算法改善约4 dB。     

基于BSBL-BO算法的DME脉冲干扰抑制方法

针对测距仪(distance measure equipment, DME)信号干扰L频段数字航空通信系统1(L-band digital aeronautical communication system 1, L-DACS1)正交频分复用(orthogonal frequency-division multiplexing, OFDM)接收机的问题, 提出基于块稀疏贝叶斯学习-边界优化(block sparse bayesian learning-the bound optimization, BSBL-BO)算法的DME脉冲干扰抑制方法。首先, 利用OFDM接收机空子载波不传输有用信号的特点构造针对DME脉冲干扰信号的压缩感知模型; 然后基于BSBL-BO算法重构DME脉冲干扰信号; 最后在时域进行干扰消除。仿真结果表明, 该方法比已有的脉冲干扰抑制方法具有更高的重构精度和更快的运算速度, 进一步降低了OFDM接收机的误比特率, 提高了L-DACS1系统前向链路传输性能。