On the CFO estimation of the OFDM: A frequency domain approach

This paper presents a simple yet effective carrier-frequency-offset (CFO) estimation algorithm for orthogonal-frequency-division-multiplexing (OFDM) system using a general inter-carrier interference (ICI) self-cancellation scheme. The key feature of the proposed algorithm is that it has a significantly wider CFO estimation range than the maximum-likelihood (ML) algorithm. The proposed algorithm first constructs the snapshot vectors through stacking the signals in each subcarrier group of the precoded OFDM symbol. Because the ICI self-cancellation scheme can suppress the inter-group ICIs, the snapshot vectors can be expressed in a form having a CFO-directed response structure. This enables the proposed approach to estimate the CFO by using the multiple signal classification (MUSIC) algorithm in the frequency domain.     

Diversity incorporated energy adaptation for A-CDMA systems over slow fading channels

In this paper, a theoretical analysis of diversity incorporated Variable Energy Adaptation (VEA) in an Asynchronous Code Division Multiple Access (A-CDMA) system is discussed for Rayleigh, Rician and Nakagami slow fading channels. The adaptation is accomplished by providing the receiver with the capability of measuring the signal energy-to-noise ratio, and controlling the transmitted signal energy by means of a noise-free feedback loop. System parameters such as fading margin, maximum signal-to-noise ratio, and mean transmitter energy gain are derived and plotted for fading channels as a function of the probability of error specification and the probability of unsatisfactory operation. The mean and median probabilities of error are plotted as a function of energy-to-noise ratios for different fading channels. Error probability distribution and density functions are derived and plotted for various signal-fading distributions.     

Fusion estimation for stochastic uncertain systems with time-correlated rician fading channels

In this article, a fusion estimation scheme is proposed for stochastic uncertain systems with time-correlated fading channels (TFCs). A batch of random variables obeying Gaussian distributions is employed to describe the parameter uncertainties. The sensor communicates with the local filter through a TFC where the evolution of the channel coefficient is characterized by a certain dynamic process with one-step correlated noises. For further analyzing the effects of TFCs, a class of additional variables is first introduced by augmenting the dynamics of channel coefficients and the concerned system. Then, a new group of modified local filters is developed and the unbiasedness of local filters is examined by means of inductive method. Furthermore, the filter gains which minimize the local filtering error covariances are designed for the modified local filters in the simultaneous presence of stochastic uncertainties and TFCs. Subsequently, the cross-covariances among local estimates are computed iteratively and, based on the obtained cross-covariances as well as the unbiased local estimates and their corresponding filtering error covariances, a fusion estimate is obtained by using weighted least square fusion method. Finally, the effectiveness of the proposed fusion estimation scheme is verified by two examples.     

无线局域网中OFDM系统的频偏估计技术研究

正交频分复用（OFDM）是一种正交多载波技术，目前在很多领域得到广泛的应用。其主要缺点之一就是对于发送接收之间的载波频偏（CFO）很敏感。如果在接受机中CFO没有得到补偿，子载波间就会失去正交性，这会导致严重的信道间干扰（ICI）。本文分析了目前无线局域网中OFDM频偏估计常用的两种算法，提出一种针对IEEE802．11aOFDM系统频偏的解决方案，该方案将目前无线局域网中的解决OFDM系统的频偏纠正算法的优点和802．11a的帧结构充分结合起来，最后通过计算机的仿真证明了我们方案的正确性。     

无线局域网中OFDM系统的频偏估计技术研究

正交频分复用(OFDM)是一种正交多载波技术,目前在很多领域得到广泛的应用.其主要缺点之一就是对于发送接收之间的载波频偏(CFO)很敏感.如果在接受机中CFO没有得到补偿,子载波间就会失去正交性,这会导致严重的信道间干扰(ICI).本文分析了目前无线局域网中OFDM频偏估计常用的两种算法,提出一种针对IEEE802.11aOFDM系统频偏的解决方案,该方案将目前无线局域网中的解决OFDM系统的频偏纠正算法的优点和802.11a的帧结构充分结合起来,最后通过计算机的仿真证明了我们方案的正确性.     

A filtering based recursive least squares estimation algorithm for pseudo-linear auto-regressive systems

This paper uses the filtering technique, transforms a pseudo-linear auto-regressive system into an identification model and presents a new recursive least squares parameter estimation algorithm pseudo-linear auto-regressive systems. The proposed algorithm has a high computational efficiency because the dimensions of its covariance matrices become small compared with the recursive generalized least squares algorithm.     

Blind estimation of carrier frequency offset for OFDM systems with time-varying DC offset

Orthogonal frequency division multiplexing (OFDM) has been widely adopted in radar and communication systems. High sensitivity to carrier frequency offset (CFO) is one of the major drawbacks of OFDM. CFO estimation for OFDM systems had been extensively studied and various algorithms had been proposed. However, the established algorithms may be compromised by the adoption of direct-conversion architecture and multi-mode low noise amplifier in the OFDM receiver, which introduces time-varying direct current offset (TV-DCO) into the system. In our previous study, we developed an eigen-decomposition based estimation algorithm, which is robust to TV-DCO but suffers from performance degradation under low to medium signal-to-noise ratio and requires high computation efforts. To address those issues, we in this paper propose a novel blind CFO estimation algorithm. By making use of the second order differential filtering and subspace method, the proposed algorithm achieves great performance improvement with reduced complexity. The performance of the proposed algorithm is demonstrated by simulations.     

Recursive parameter estimation algorithm for multivariate output-error systems

In this paper, we consider the parameter estimation issues of a class of multivariate output-error systems. A decomposition based recursive least squares identification method is proposed using the hierarchical identification principle and the auxiliary model idea, and its convergence is analyzed through the stochastic process theory. Compared with the existing results on parameter estimation of multivariate output-error systems, a distinct feature for the proposed algorithm is that such a system is decomposed into several sub-systems with smaller dimensions so that parameters to be identified can be estimated interactively. The analysis shows that the estimation errors converge to zero in mean square under certain conditions. Finally, in order to show the effectiveness of the proposed approach, some numerical simulations are provided.     

一种CMMB系统信道估计改进算法的研究

针对CMMB系统中接收信号因受传输环境的大、小尺度衰落、多普勒衰落影响,通过最小二乘信道估计和低密度奇偶校验码LDPC（Low Density Parity Check Code）译码结合的算法在接收端对信号进行接收处理,实验仿真表明,该算法可以达到与经典算法的性能相接近效果的同时大量减少了系统的复杂度。     

OFDM系统时变信道下基于导频的信道估计

本文就OFDM系统在时变信道下基于导频的信道估计技术进行了研究.分析了一种利用改进的分组导频结构估计时变信道冲激响应的方法.通过Matlab仿真,比较了不同导频结构下系统的误码率性能.仿真结果表明,在时变信道中,这种改进的导频结构的性能在一定程度上优于传统的等间隔导频结构的性能.     

基于抗差算法的马斯京根参数估计

用于估计马斯京根模型参数的方法很多,但这些方法在数据存在异常值时缺乏抵御异常值影响的抗差性能. 推导出一种有限制条件的参数抗差估计算法,通过含有随机误差和异常误差的人工数据和真实数据比较抗差算法与传统最小二乘算法的抗差性. 研究表明抗差估计算法能减小异常值对参数估值的影响.     

A novel LMI-based optimization algorithm for the guaranteed estimation of the domain of attraction using rational Lyapunov functions

In this article we deal with the classical problem of estimating the domain of attraction (DOA) of autonomous dynamical systems. We propose a new LMI estimation method based on recent results from the mathematical theory of moments. In contrast to previous works we exploit the advantages of rational Lyapunov functions to enhance the estimates. Several examples illustrate the estimation method.     

Decomposition based least squares iterative estimation algorithm for two-input single-output output error systems

This paper develops a decomposition based least squares iterative identification algorithm for two-input single-output (TISO) systems. The basic idea is to decompose a TISO system into two subsystems and then to identify each subsystem, respectively. Compared with the least squares based iterative algorithm, the proposed algorithm has less computational load. The simulation results indicate that the proposed algorithm is effective.     

OFDM系统降低PAPR的PTS优化算法分析与比较

针对OFDM系统峰均比PAPR过大而限制其应用的缺点,对比分析了目前优化PAPR的传统PTS(部分传输序列法)算法以及优化的PTS算法的性能与计算复杂度,在此基础上提出分组优化PTS算法,在性能与计算复杂度上有良好平衡。最后对各种算法列表对比优劣,对今后的算法研究提供一定的参考价值。     

OFDM系统中一种信道算法仿真

在无线通信系统中,存在着严重的频率选择性衰落、快衰落和慢衰落,以及各种噪声的干扰和多径传播下的码间串扰等问题,这些问题都会严重地影响着通信系统的性能和质量。为了解决这些问题,本文对基于FFT算法的OFDM系统信道进行了系统仿真及性能分析。仿真结果表明,本算法具有性能好、复杂度低的优点。     

A test strip for the estimation of urea in serum

We have developed a biostrip for determination of urea in serum. The test strip is based on enzymatic assay where urease has been immobilized on the chromatographic paper along with chromogen, phenol red. The chromogen is easily soluble in water and does not require other components for the color change. Serum urea reacts with urease and water to liberate ammonia and carbon dioxide. The liberated ammonia changes the pH of the reaction medium, which is monitored by the chromogen phenol red. A single step working reagent strip has been developed and the reaction is completed within 50 seconds at room temperature. With this test strip urea concentration is measured in serum as low as 0.15 g/L. The speed and convenience of determining urea in serum by this strip instantly makes it well suited for individuals, physicians and emergency centres.     

A Rawlsian algorithm for autonomous vehicles

Autonomous vehicles must be programmed with procedures for dealing with trolley-style dilemmas where actions result in harm to either pedestrians or passengers. This paper outlines a Rawlsian algorithm as an alternative to the Utilitarian solution. The algorithm will gather the vehicle’s estimation of probability of survival for each person in each action, then calculate which action a self-interested person would agree to if he or she were in an original bargaining position of fairness. I will employ Rawls’ assumption that the Maximin procedure is what self-interested agents would use from an original position, and then show how the Maximin procedure can be operationalized to produce unique outputs over probabilities of survival.     

网格市场中服务质量驱动下的任务调度算法

针对资源提供方不能完成用户所有任务的情况,提出一种服务质量驱动下的任务调度算法,即预算和截止时间限制下的最大任务完成数调度算法(DBCN).这种批调度算法结合了Min-min算法吞吐量较高和线性规划全局优化的优点,不仅考虑了用户的所有任务,同时还考虑了优先级较高的任务.实验结果表明,该算法在任务完成总数方面比经典算法Min-min和DBCT分别提高了约10.6%和22.0%,在优先级高的任务完成总数方面也有大幅度提高,分别约为20%和40%.