A High Spectral Efficient Frequency-Domain Channel-Estimation Method for the Polarization-Division-Multiplexed CO-OFDM-OQAM System

Contrary to the other multi-carrier modulation systems, the coherent optical orthogonal frequency division multiplexing communication system with an offset quadrature amplitude modulation (CO-OFDM-OQAM) possesses inherent imaginary interference (IMI). This has an important impact on the channel estimation process. Currently, a variety of frequency-domain channel estimation methods have been proposed. However, there are various problems that still exist. For instance, in order to reduce the influence of IMI, it is necessary to insert more guard intervals between the training sequence and the payload, leading to the occupation of excessive spectrum resources. In order to address this problem, this work designs a high spectral efficient frequency-domain channel estimation method for the polarization-division-multiplexing CO-OFDM-OQAM systems. First, the working principle of the proposed method is described in detail. Then, its spectral efficiency, power peak-to-average ratio, and channel estimation performance are studied based on simulations. The simulation results show that the proposed method improves the spectral efficiency without worsening the power peak-to-average ratio. The channel estimation capability of this method is verified in three scenarios of long-distance transmissions, including back-to-back, 100 km, and 200 km transmissions. .

Impact of WCDMA channel multiplexing on smart antenna systems

Smart antenna has been regarded as one promising technology to enhance the performance of CDMA mobile communication systems. However, when applied to 3G systems, the performance of traditional adaptive arrays may degrade due to code and time multiplexing in dedicated physical channels. A novel semiblind adaptive array approach is proposed to solve this problem. It overcomes the selfinterfering problem by introducing a quasidespreading technique for the control channel, and contains a timemultipexed structure to utilize both pilot symbols and unknown control symbols within the control channel. The blind part of the proposed approach is based on the competition of two parallel branches with different reference sequences. Simulation results show significant improvement can be achieved by the proposed approach in a fastfading WCDMA environment.

Diversity-multiplexing tradeoff of half-duplex multi-input multi-output two-way relay channel with decode-and-forward protocol

A multi-input multi-output(MIMO) separated two-way relay channel(STWRC) is considered,where two users exchange their messages via a relay node.When each link is quasi-static Rayleigh fading,the achievable diversity-multiplexing tradeoff(DMT) of the half-duplex STWRC is analyzed.Firstly,the achievable DMT of the STWRC with static decode-and-forward(DF) protocol is obtained.Then,a dynamic decode-and-forward(DDF) protocol for the STWRC is proposed,where the relay listening time varies dynamically with the channel qualities of the links between two users and the relay.Finally,the achievable DMT of the proposed DDF protocol is derived in a case-bycase manner.Numerical examples are also provided to verify the theoretical analysis of both protocols.

智能反射面辅助的OFDM系统稀疏信道估计研究

针对智能反射面(IRS)辅助的宽带正交频分复用(OFDM)系统的信道估计,当前大多数研究都是基于单符号全导频设置,且级联信道系数过多会导致导频开销较大。为此,提出了一种基于时域-角域块稀疏的两阶段信道估计方案。首先,通过分析信道在时域和角域上存在的共同稀疏特性,将级联信道矩阵转换为时域-角域上的块稀疏表示,并将信道估计问题转换为块稀疏矩阵恢复问题。其次,考虑传输导频限制和时域-角域块稀疏特性,提出了一种两阶段稀疏信道估计方案对级联信道进行稀疏恢复。仿真结果表明,相比另外三种基准方案,该方案可以使用较少的导频获得更优的信道估计性能,有效减少了导频开销,且估计准确度更高。

LDPC编码辅助的判决反馈信道估计与均衡方法

信道频率选择性衰落较强的环境下,传统正交频分复用非盲信道估计与均衡方法的系统误码性能较差,且需要在信号中增加导频符号的插入,降低系统吞吐量。针对上述问题,提出一种低密度奇偶校验(Low-Density Parity-Check,LDPC)编码辅助的判决反馈信道估计与均衡方法。将LDPC编码增益引入判决反馈回路中,以提升收敛性,在插入极少导频符号的条件下达到渐进非盲信道估计与均衡方法的性能。另外提出一种基于条件最大似然原则的信道估计改进算法,以恒虚警原则检测有效抽头信号以提高信道估计精度,并且能够与判决反馈信道估计与均衡方法相结合,进一步提升算法性能。仿真结果表明,在仿真所选用的信道环境下,LDPC编码辅助的判决反馈信道估计与均衡方法相比传统判决反馈方法具有11~13 dB的误码性能提升,具有优秀的系统误码性能和鲁棒性。

基于状态反馈的无人机通信接入拥塞动态控制研究

为解决复用信道内的通信接入拥塞问题,需要控制无人机通信链路中数据信息样本的实时累积量,故基于状态反馈研究无人机通信接入拥塞动态控制方法;建立信道复用模型,并借助MAC连接协议,定义通信数据包,实现对无人机集群通信节点接入行为的处理;按照状态反馈模型完善状态观测器结构,求解通信数据的离散化反馈表达式,在划分通信优先级条件的同时,确定无人机队列的实时调度关系,完成无人机通信行为控制;根据动态阈值窗口定义条件,确定通信链路长度,再联合相关通信数据样本,计算链路时延量的具体数值,完成动态控制方法的设计;实验结果表明,应用设计方法可将通信链路中数据信息样本实时累积量控制在5.7×10^(13)MB之下,能够较好解决复用信道内的通信接入拥塞问题,符合实际应用需求。

面向软件定义互连系统的多协议交换电路

为满足软件定义互连系统中异构协议融合互连的需求,提出一种两级多协议交换电路,该电路通过融合共享缓存与Crossbar这2种交换架构,实现对多种异构协议的报文转发需求的兼顾。同时,提出一种基于时隙的多级仲裁调度方法,实现调度过程中时间与空间的解耦。仿真结果表明,所设计的交换电路能够弹性适应绑定模式变化引起的交换规模及端口缓存、端口带宽需求变化,缓存资源利用率相较传统组合输入输出排队(CIOQ)架构最高提高87.5%,转发时延低至数十纳秒,不仅适用于RapidIO、光纤通道(FC)、Ethernet、外设部件互连快速总线(PCIe)单一协议交换,而且适用于多种协议组合的混合协议交换。

基于深度学习的OFDM半相干水声通信方法

针对正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)水声通信中常用的相干和非相干通信分别面临的对多普勒敏感和频谱效率低的问题,提出一种高阶幅度键控调制的半相干通信技术,将OFDM符号时频帧结构中全部频点采用高阶幅度键控调制方式,并利用信号幅度信息完成半相干信道估计。通过两种基于深度学习的算法优化半相干信道估计这一非线性过程,较非相干通信有效提高了频谱效率,较一定信噪比下的相干通信提高了鲁棒性,降低了误比特率和系统复杂度,并利用元学习算法降低深度学习算法对训练数据的依赖。最后,提取海试信道数据,完成OFDM半相干水声通信系统仿真,验证了所提方法在频谱效率和系统误比特率性能方面较非相干和相干通信的优势,当信道长度改变时,基于元学习的算法依然可以获得较好的性能。

OFDM叠加导频联合信道估计和检测方法

针对现有正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)系统信道估计和迭代检测算法中频谱效率低和鲁棒性差等问题,提出了一种基于酉近似消息传递和叠加导频的信道估计与联合检测方法。首先,在软调制/解调中叠加导频对正交幅度调制的星座点进行预处理,检测时将叠加的导频作为频域符号的先验分布,利用置信传播算法进行调制和解调,实现检测模型的简化。然后,应用因子图-消息传递算法对OFDM传输系统和信道进行建模和全局优化,引入酉变换加强信道估计算法的鲁棒性。最后,建立OFDM仿真环境对现有方法进行仿真分析。仿真结果表明,相对于现有的独立导频类算法,所提算法能够以相同复杂度显著提升OFDM系统的频谱效率和鲁棒性。

基于排序码本的水声自适应OFDM通信中信道状态信息反馈研究

水声(UWA)信道时延扩展大等特点导致信道频响(CFR)快衰落,水声通信(UWAC)技术发展受到挑战。发射端获取有效可靠的信道状态信息(CSI)是自适应通信的前提,针对水声自适应正交频分复用(OFDM)通信的需求,该文提出基于排序码本的信道状态信息分组排序拟合反馈算法(CSI-GSFF),包括分组、排序、数据拟合3个步骤。该算法首先将相邻导频子载波分组,以组为反馈单元;然后对各组内的导频子载波按照信道增益值进行排序,以减轻水声信道频响快衰落造成的反馈开销大等不利影响;最后进行多项式拟合,排序操作有效地降低了拟合阶数。通过实测海试时变信道数据仿真,结果表明,该文提出的信道状态信息反馈算法能够基本达到完美信道状态信息情形下的水声自适应OFDM通信系统误码率性能,同时可以有效地减少反馈开销。

深度学习辅助的5G OFDM系统的信道估计

传统的信道估计算法难以满足5G系统中的高速率低时延的需求。针对该问题,将通信信道的时频响应视为二维图像,提出了一种基于图像恢复技术的信道估计方法。首先,设定参数产生基于5G新空口(New Radio,NR)标准的物理下行链路共享信道(Physical Downlink Shared Channel,PDSCH)的信道数据信息数据集,将所产生的信道矩阵看作二维图像;然后,构建基于卷积神经网络的图像恢复网络,并融入残差连接来提高网络的性能;最后,利用训练好的网络模型进行信道估计。仿真结果表明,与最小二乘算法(Least Square,LS)、实际信道估计(Practical Channel Estimation,PCE)和基于图像超分辨率ChannelNet网络相比,所提出的信道估计算法性能提升明显。

基于贝叶斯框架的OFDM稀疏信道估计算法

为了提高正交频分复用OFDM(Orthogonal Frequency Division Multiplexing,OFDM)稀疏信道估计的性能,实现了一种基于3-L分层先验模型的变分贝叶斯VMP(Variational Message Passing)消息传递算法。该算法对待估计向量的辅助函数分组并且加入贝塞尔函数,通过消息传递原则更新估计值参数,最后估计出频率响应采样值。仿真显示相较于传统的CosaMP、EM算法,提出的变分贝叶斯VMP算法可以获取更好的重构性能。在中高信噪比下,所提出的算法比传统CosaMP、EM算法的误比特率提高了2-3db,均方误差提高了3-4db。

无线通信工程中的 MIMO 系统应用与性能分析

文章深入分析多输入多输出(Multiple InputMultiple Output,MIMO)系统在无线通信工程中的应用及其性能,重点探讨其关键技术和应用场景。MIMO系统通过空间复用和阵列增益提升通信系统的容量和可靠性,尤其在空间复用方面,通过向量偏转传输技术实现在同一时频资源上传输多个独立数据流,从而大幅提高频谱效率。此外,文章讨论了信道编码与交织技术在提高MIMO系统可靠性和抗衰落能力上的重要作用,分析了基于最小均方误差(Minimum Mean Square Error,MMSE)算法的信道估计与均衡技术在保证系统性能上的关键应用。仿真结果显示,MIMO系统在信噪比较高时实现了显著的吞吐量提升,验证了其在无线通信领域的优越性。

基于改进遗传算法优化的RBF网络的信道估计

为了提高通信系统信道估计的准确率,同时适应更大的数据量,进行更加复杂的数据计算,引入神经网络的方法进行信道估计,采用了BP和RBF神经网络进行实验对比,与传统信道估计方式相比有明显提升;在此基础上,进一步提出基于改进遗传算法优化的RBF神经信道估计方法,目的是帮助确定RBF网络的隐藏层参数,使得网络的参数趋于全局最优解,信道估计器的性能从而得到提升。经过Matlab仿真,改进后的RBF神经网络可以更好地解决信道估计问题,验证了此方法的可行性。

基于LoRa的多传感器低功耗数据采集方法

针对LoRa多传感器低功耗采集中同信道传感节点无效唤醒的问题,提出一种基于空中唤醒策略与信道切换机制相结合的低功耗采集方法。通过将LoRa通信链路划分为多个通信信道,不同信道分时切换复用,实现多传感节点的分组通信,避免从传感节点的无效唤醒,在有限信道容量下最大限度地降低从节点的通信功耗;并制定了LoRa局域网传感器通信指令协议,实现了多传感器的低功耗主动轮询采集、定点调试与预警上报。实验结果证明了所提方法的有效性。

A Reduced Complexity Time-Delay Tracking and Channel Estimation for OFDM Systems

This paper presented an improved channel estimator for orthogonal frequency division multiplexing (OFDM) systems using joint time delay detection and channel gain estimation. The algorithm well designs an adjustment scheme using the time correlation of time delays to increase the accuracy of the time delay detection. The most attractive advantage is that the complicated matrix calculation is replaced by the search steps to estimate the channel parameters without significantly increasing the complexity of the system. The computer simulation demonstrates that the proposed algorithm can track the time delays adaptively and improve the channel estimation performance. Consequently, the better system performance will be achieved.

Sparse channel recovery with inter-carrier interference self-cancellation in OFDM

A new sparse channel estimation method of orthogonal frequency division multiplexing（OFDM） system based on intercarrier interference（ICI） self-cancellation is investigated. Firstly,based on the characteristic that the ICI generated by a subcarrier to the two adjacent subcarriers is approximately equal, a data pair with opposite sign and equal magnitude is modulated onto two adjacent subcarriers as pilot pair to eliminate the effect of ICI on pilots. Secondly, a new OFDM channel estimation model based on linear time-varying（LTV） model and compressed sensing（CS） is constructed, which obtains the mean of the gains of the multipath.Finally, a pilot pair optimization algorithm based on two layers loop is used to realize the minimization of the mutual coherence of the measurement matrix. For time-varying channel scenes with different numbers or delay of multipath and maximum Doppler frequency shift, the performances of several channel estimation methods are verified by simulation. The result shows that the new method has obvious advantage in both the performance of the channel estimation and the spectral efficiency.

Improved H-infinity channel estimator based on EM for MIMO-OFDM systems

H-infinity estimator is generally implemented in timevariant state-space models, but it leads to high complexity when the model is used for multiple input multiple output with orthogo- hal frequency division multiplexing （MIMO-OFDM） systems. Thus, an H-infinity estimator over time-invariant system models is pro- posed, which modifies the Krein space accordingly. In order to avoid the large matrix inversion and multiplication required in each OFDM symbol from different transmit antennas, expectation maximization （EM） is developed to reduce the high computational load. Joint estimation over multiple OFDM symbols is used to resist the high pilot overhead generated by the increasing number of transmit antennas. Finally, the performance of the proposed estimator is enhanced via an angle-domain process. Through performance analysis and simulation experiments, it is indicated that the pro- posed algorithm has a better mean square error （MSE） and bit error rate （BER） performance than the optimal least square （LS） estimator. Joint estimation over multiple OFDM symbols can not only reduce the pilot overhead but also promote the channel performance. What is more, an obvious improvement can be obtained by using the angle-domain filter.

Low-complexity fractional phase estimation for totally blind channel estimation

To remove the scalar ambiguity in conventional blind channel estimation algorithms, totally blind channel estimation （TBCE） is proposed by using multiple constellations. To estimate the unknown scalar, its phase is decomposed into a fractional phase and an integer phase. However, the maximum-likelihood （ML） algorithm for the fractional phase does not have closed-form solutions and suffers from high computational complexity. By ex- ploring the structures of widely used constellations, this paper proposes a low-complexity fractional phase estimation algorithm which requires no exhaustive search. Analytical expressions of the asymptotic mean squared error （MSE） are also derived. The theo- retical analysis and simulation results indicate that the proposed fractional phase estimation algorithm exhibits almost the same performance as the ML algorithm but with significantly reduced computational burden.

Novel Channel Estimation Method in Broadband MIMO-OFDM Systems

A least square （IS） parametric channel estimation method in broadband mt/ltiple input multiple output （MIMO） orthogonal frequency division multiplexing （OFDM） systems is proposed. The mean square error （MSE） performance using optimal training pilots is also given, which proves the method can improve the estimation precision greatly in sparse channel.. Since such method needs the multi-path time delays information of the channel, the probabilistic data association （PDA） method is employed to estimate the time delay of each path. Simulation results show that both the bit error rate （BER） and the MSE performance of the proposed method are better than the traditional LS channel estimation method.