OFDM系统中子信道的自适应比特、功率分配

研究了一种改进的OFDM系统中子信道的自适应比特、功率分配算法。该算法可适用于多径频率选择性衰落信道,它根据信道的瞬时特性,动态地为OFDM系统的各子信道分配传输比特数和发送功率。依据不同的分配准则,采用了MA和RA两种优化算法。仿真结果表明,采用自适应技术可以大大提高OFDM系统的性能。     

一种基于三阶累积量的准则及自适应滤波算法

该文提出了一个基于三阶累积量的优度准则。基于此准则,利用最速下降法,得到一种新的基于三阶累积的梯度型自适应滤波算法,该算法用于平稳和非平稳的MA(Moving Average)模型系统辨识的计算机模拟仿真结果表明:该算法有良好的收敛性能及对时变系统的跟踪能力。     

自适应OFDMA系统无线资源管理的CPN建模与仿真

基于自适应OFDMA系统,对多业务系统中基于总发射功率最小化的无线资源管理问题进行研究,并使用着色Petri网(CPN,coloured Petri nets)以及CPN分析工具CPN Tools对其进行建模。采用Monitor监控器对模型进行仿真分析,并将仿真结果与随机Petri网(SPN,stochastic Petri nets)模型以及基于吞吐量最大化的CPN模型进行比较,验证了该系统模型的正确性和优越性。     

Higher order cumulants-based least squares for nonminimum-phasesystems identification

A third-order cumulants based adaptive recursive least-squares (CRLS) algorithm for the identification of time-invariant nonminimum phase systems, as well as time-variant nonminimum phase systems, has been successfully developed. As higher order cumulants preserve both the magnitude and the phase information of received signals, they have been considered as powerful signal processing tools for nonminimum phase systems. In this paper, the development of the CRLS algorithm is described and examined. A cost function based on the third-order cumulant and the third-order cross cumulant is defined for the development of the CRLS system identification algorithm. The CRLS algorithm is then applied to different moving average (MA) and autoregressive moving average (ARMA) models. In the case of identifying the parameters of an MA model, a direct application of the CRLS algorithm is adequate. When dealing with an ARMA model, the poles and the zeros are estimated separately. In estimating the zeros of the ARMA model, the construction of a residual time-series sequence for the MA part is required. Simulation results indicate that the CRLS algorithm is capable of identifying nonminimum phase and time-varying systems. In addition, because of the third-order cumulant properties, the CRLS algorithm can suppress Gaussian noise and is capable of providing an unbiased estimate in a noisy environment     

基于加载算法的室内无线信道OFDM接收机的性能

本文研究了无线局域网中使信号频谱得到优化的一种简单OFDM子载波加载算法。此算法基于边缘自适应（Margin Adaptive）加载准则及其在室内无线信道上的性能。     

下行多用户CoMP系统资源分配算法

针对下行多用户多点协作传输系统(MU-CoMP)边值自适应(MA)的问题,提出了一种快速资源分配算法。该算法首先根据用户的速率要求及平均信道增益估计出每个用户需要的子载波数目,在此基础上设计合理的子载波分配算法进行子载波分配,通过预判并且剔除不适合传输数据的较差空间子信道实现快速比特加载。仿真结果表明,所提算法在满足用户最低速率和误码率要求的前提下有效地降低了总发射功率,以较低的复杂度获得了接近最优算法的性能。     

自适应功率估计算法的计算机仿真

本文提出并建立了一种称之为功率估计算法的ＭＴＩ滤波算法,与现有的自适应算法相比,它具有结构简单,易于工程实现之优点。基于这个算法已构成了一个最优低阶自适应ＭＴＩ系统的模型,计算机仿真结果表明,这个系统的性能十分逼近于理想系统,从而证明了新算法的正确性和可行性。     

Adaptive identification of nonminimum phase ARMA models usinghigher order cumulants alone

An adaptive identification algorithm for causal nonminimum phase ARMA models in additive colored Gaussian noise is proposed. The algorithm utilizes higher order cumulants of the observed signal alone. It estimates the AR and MA parameters successively in each iteration without computing the residual time series. The steepest descent method is used for parameter updating     

OFDM系统中动态子信道和功率的分配

在分析一种多用户OFDM系统中自适应子信道和比特功率分配算法的基础上,根据多径频率选择性衰落信道的瞬时特性,动态地为多用户分配子信道和传输比特数,并服从MA优化准则.并且进一步考虑了系统中有固定速率用户和可变速率用户同时存在的情况:在子信道分配时,先给固定速率的用户分配子信道,再给可变速率用户按照子信道链路增益最大化分配剩余的子信道;在信号发射功率分配上,按照"注水"法则分配,链路增益大的子信道分配的功率大,链路增益小的子信道分配的功率小,则系统的目标函数,总传输速率可以达到最大.仿真证明了此方案优于一般的方案.     

非最小相位ARMA模型的一种自适应辨识算法

本文提出了一种加性有色高斯噪声中因果非最小相位ARMA模型的自适应辨识算法。模型输入假定为非高斯独立同分布随机过程。算法只利用了观测信号的高阶统计量。在每次迭代中,先估计AR参数,再估计MA参数,但不用计算残差序列。在参数递推中采用了随机梯度法。仿真实验证实了本文算法的有效性。     

基于粒子群优化算法思想的组合自适应滤波算法

根据粒子群优化(PSO)算法的社会心理学指导思想并结合自适应FIR滤波器的特点,设计了合适的惯性项、认知项与社会项表达式,并将之应用于组合自适应滤波器的子自适应滤波器更新中,提出了基于PSO算法思想的组合自适应滤波算法,分析了新算法的计算复杂度。理论分析与不同条件下的自适应系统辨识仿真结果表明,新算法可以在不明显提高计算量的条件下较好地平衡自适应滤波器的稳态失调与跟踪能力,其收敛性能优于其它几种较新的LMS算法。     

Robust adaptive beamforming for large-scale arrays

For a large-scale adaptive array, heavy computational load and high-rate data transmission are two challenges in the implementation of an adaptive digital beamforming system. Moreover, the large-scale array becomes extremely sensitive to array imperfections. First, based on a restructured recursive linearly constrained minimum variance algorithm and a gradient-based optimization method, a new robust recursive linearly constrained minimum variance (RRLCMV) algorithm is proposed in this paper. The computational load of the RRLCMV algorithm is on the order of o(N), which is less than that of the conventional gradient-based robust adaptive algorithm. Then, a new efficient parallel robust recursive linearly constrained minimum variance (PRRLCMV) adaptive algorithm is proposed by appropriately partitioning the RRLCMV algorithm into a number of operational modules. It can be easily executed in a distributed-parallel-processing fashion, sequentially and in parallel. As a result, the PRRLCMV algorithm provides an effective solution that can alleviate the bottleneck of high-rate data transmission and reduce the computational cost. Finally, an implementation scheme of the PRRLCMV algorithm based on a distributed-parallel-processing system is also proposed. The simulation results demonstrate that the new PRRLCMV algorithm can significantly reduce the degradation due to various array errors.     

子阵级和差及辅助波束联合自适应单脉冲方法

数字阵列雷达在每一个阵元后有一个接收通道,若采用全自适应处理,则计算复杂度高,难以满足实时性需求。因此,对于实际的系统往往要采用降维自适应阵列处理去解决以上问题。鉴于此,提出一种子阵级和差及辅助波束联合自适应单脉冲算法。该方法基于子阵降维情况下,利用子阵合成的高增益差波束以及若干子阵合成的指向若干副瓣干扰(SLJ)方向的辅助波束来对消主副瓣干扰。理论分析和仿真结果均表明,该方法不仅在有效抑制主副瓣干扰的同时保证了高精度的单脉冲测角能力,并且进行子阵降维处理解决了相控阵体制雷达阵元数繁多所带来的问题,便于工程实现。     

变步长LMS算法及其在自适应消噪中的应用

介绍了一种新的变步长LMS自适应滤波算法。该算法具有较快的收敛速度和较小的失调，并且他不受已经存在的不相关噪声的干扰．将该算法应用于自适应噪声对消系统的仿真中，给出了计算机仿真结果，仿真结果与理论分析是一致的．     

Adaptive subcarrier and bit allocation in OFDMA systems supporting heterogeneous services

Orthogonal Frequency Division Multiple Access (OFDMA) is an efficient multiple access method for the future wireless systems. This paper studies the adaptive subcarrier and bit allocation problem in OFDMA systems to support heterogeneous services. The goal of the considered resource optimization technique is to maximize the total system throughput under the overall transmit power constraint while guaranteeing the QoS requirement of realtime users and supporting proportional fairness among non-realtime users. First, we introduce a Rate Adaptive (RA) resource allocation algorithm for non-realtime users and a Margin Adaptive (MA) algorithm for realtime users. Then, based on the previous algorithms, a novel algorithm is proposed to allocate the resource to both classes of users, which makes an efficient tradeoff between the resource usage of realtime users and non-realtime users. The algorithm is locally optimal solution provided that the MA and RA algorithms are utilized. Also, to reduce the computational complexity, a suboptimal method based on the balancing of the average power per subcarrier is also introduced. Monte Carlo simulation results show that all the proposed algorithms outperform the existing counterparts. The results also show that the suboptimal method for heterogeneous services can efficiently reduce the computational complexity at the cost of very little performance degradation. This work was supported by the National Natural Science Foundation of China (Nos. 60472079, 60572115), and by the Natural Science Foundation of Zhejiang Province (No. Z104252), China.     

自适应数字波束形成在MIMO雷达中的应用

MIMO雷达是近几年来发展起来的一种新体制雷达,由于采用空间分集与信号分集技术,相对于传统相控阵雷达在目标检测及参数估计性能都有很大提高。文中主要研究MIMO雷达的系统的自适应数字波束形成算法,介绍了基于MIMO雷达的SMI自适应DBF算法,该算法有较好的性能,易于实现。针对于空间中的有源干扰,从自由度的角度讨论分析了MIMO雷达处理系统中自适应模块的位置问题。     

一种基于核的GPS空时自适应抗干扰方法

针对GPS接收系统的空时自适应抗干扰技术,分析目前基于FROST阵列处理的最小均方算法LMS(FLMS)算法,提出一种基于核方法的FLMS算法(Kernel FLMS,KFLMS).通过对空时自适应STAP和算法的建模,研究了KFLMS算法的性能.系统仿真表明,KFLMS算法不仅能抑制大于阵元个数的多个宽、窄带干扰,而且使接收机整体抗干扰能力达到70dB左右,比FLMS算法效果更优.     

变步长频域快速自适应收发隔离算法研究

针对频域LMS算法收敛速度较慢的缺点,将LMS频域快速算法和变步长技术相结合,提出了一种基于新的Sigmoid函数的变步长频域快速自适应收发隔离算法。理论分析和计算机仿真表明,新算法除具有原频域快速算法的优点外,还具有较快的收敛速度和良好的收敛精度,可以有效地应用于干扰机自适应收发隔离系统中。     

自适应预失真射频功率放大器的多方向搜索优化算法

通常功率放大器的特性会随环境温度、供电电压等多种因素发生变化,为了保证预失真功率放大器的稳定工作,预失真系统的自适应性能就显得非常重要.本文提出了一种新的高效射频预失真功率放大器自适应优化算法,其核心思想是提取放大器输出信号的带外分量作为系统自适应的优化目标,结合具有稳定收敛性的多方向搜索优化算法对预失真系统进行优化调整,使系统始终处于最优工作状态.仿真结果表明运用该算法的预失真系统自适应收敛速度比传统自适应优化算法有明显提高,带外分量可以获得大约15dB的改善.     

ARMA-cepstrum Recursion Algorithm for the Estimation of the MA Parameters of 2-D ARMA Models

This paper considers the problem of estimating the moving average (MA) parameters of a two-dimensional autoregressive moving average (2-D ARMA) model. To solve this problem, a new algorithm that is based on a recursion relating the ARMA parameters and cepstral coefficients of a 2-D ARMA process is proposed. On the basis of this recursion, a recursive equation is derived to estimate the MA parameters from the cepstral coefficients and the autoregressive (AR) parameters of a 2-D ARMA process. The cepstral coefficients are computed benefiting from the 2-D FFT technique. Estimation of the AR parameters is performed by the 2-D modified Yule–Walker (MYW) equation approach. The development presented here includes the formulation for real-valued homogeneous quarter-plane (QP) 2-D ARMA random fields, where data are propagated using only the past values. The proposed algorithm is computationally efficient especially for the higher-order 2-D ARMA models, and has the advantage that it does not require any matrix inversion for the calculation of the MA parameters. The performance of the new algorithm is illustrated by some numerical examples, and is compared with another existing 2-D MA parameter estimation procedure, according to three performance criteria. As a result of these comparisons, it is observed that the MA parameters and the 2-D ARMA power spectra estimated by using the proposed algorithm are converged to the original ones