Mobile unit velocity estimation based on the instantaneous frequency of the received signal

This paper presents a new mobile station velocity estimator based on the first moment of the instantaneous frequency (IF) of the received signal. The effects of shadowing, additive noise, and scattering distribution on the proposed velocity estimator are analyzed. We show that, unlike velocity estimators based on the envelope and quadrature components of the received signal, the proposed estimator is robust to shadowing. We also prove that the performance of the IF-based estimator is only mildly affected by the presence of additive noise. Finally, by using simulations we show that the performance of the proposed IF-based estimator is superior to that of existing velocity estimators.     

Predictive mobility support for QoS provisioning in mobile wirelessenvironments

With the proliferation of wireless network technologies, mobile users are expected to demand the same quality of service (QoS) available to fixed users. This paper presents a predictive and adaptive scheme to support timed-QoS guarantees in pico- and micro-cellular environments. The proposed scheme integrates the mobility model into the service model to achieve efficient network resource utilization and avoid severe network congestion. The mobility model uses a probabilistic approach to determine the most likely cluster to be visited by the mobile unit. The admission control is invoked when a new call arrives or an existing call performs a handoff to verify the feasibility of supporting the call. The performance of the proposed schemes is compared to the shadow cluster scheme. The performance of the proposed scheme under different traffic patterns is also presented     

Physical characteristics of urban micro-cellular propagation

The characteristics of the propagation in micro-cellular environments at a carrier frequency of 1.98 GHz are investigated by wide band measurements, complemented by theoretical model calculations. The spatial variations of the complex impulse response were measured with a high time resolution allowing via the scattering function the extraction of detailed information about the wave propagation process. The analysis of a large number of different real propagation configurations leads to a characterization of the most relevant urban micro-cellular propagation mechanisms: propagation in lined streets under line-of-sight conditions, coupling into side streets and propagation effects near street intersections. The wide band channel behavior during the transition of a mobile antenna from directly illuminated into shadowed areas has been considered in particular detail, since this is a crucial situation for a mobile communications system     

Simplified Estimation of 2D DOA for Coherently Distributed Sources

In mobile communications, local scattering in the vicinity of the mobile results in angular spreading as seen from a base station antenna array. In this paper, we consider the problem of estimating the two-dimensional (azimuth and elevation) direction-of-arrival (DOA) parameters of spatially distributed sources. Based on double parallel uniform linear arrays (ULAs), a simplified method without spectrum-peak searching is proposed for the 2D DOA estimation of multiple coherently distributed (CD) sources. The proposed method firstly obtains two approximate rotational invariance relations with respect to the nominal DOAs of CD sources by using one-order Taylor approximation to the generalized steering vectors (GSVs) of two pairs of shifted subarrays. And then a new ESPRIT-based method is utilized to estimate the nominal azimuth DOA and nominal elevation DOA. In addition, a simple parameter matching approach is also given. Compared with the conventional methods, our method has significantly reduced the computational cost and can sustain the estimation performance within a tolerable level. Moreover, our method is a blind estimator without any prior knowledge about angular distribution shape. Numerical examples illustrate the performance of the method.     

Least squares frequency estimation in frequency-selective channelsand its application to transmissions with antenna diversity

A new data-aided frequency estimator for frequency-selective fading channels is introduced. The proposed estimator is developed based on a least squares (LS) error criterion and can estimate frequency offsets without the need for channel information. Statistical analysis indicates that the resulting estimate is unbiased and tends to approach the Cramer-Rao lower bound (CRLB). Simulation shows that the proposed LS method is preferable to existing techniques in mobile communications. The application of the LS estimator to systems with transmitter antenna diversity is also considered. In particular, it is demonstrated that the LS method can be successfully applied to third-generation wireless communication systems     

Nonparametric mobile speed estimation in fading channels: Performance analysis and experimental results

In this paper we propose a new speed estimation technique, applicable to both mobile and base stations, based on the characteristics in the power spectrum of mobile fading channels. Our analytic performance analysis, verified by Monte Carlo simulations, shows that our low-complexity estimator is not only robust to both Gaussian and non-Gaussian noises, but also insensitive to nonisotropic scattering observed at the mobile. The estimator performs very well in both two- and three-dimensional propagation environments. The robustness against both nonisotropic scattering and line of sight can be further increased, by taking advantage of resolvable paths in wideband fading channels, due to the differences among the Doppler spectra observed at different paths. We also extend this technique to base stations with antenna arrays. By exploiting the spatial information, the proposed space-time estimator exhibits excellent performance over a wide range of noise power, nonisotropic scattering, and line-of-sight component, verified by simulation. The utility of the new method is further demonstrated by applying it to the measured data.     

A scale‐independent way for differential estimation in dynamic radio frequency identification systems

Cardinality estimation in radio frequency identification systems has been applied to estimate the population of tags in many applications. However, it is more meaningful to estimate the number of tags moved in and out in a dynamic radio frequency identification system, which is called differential estimation problem. Zero differential estimator is a newly proposed algorithm to solve this problem. However, the time slots consumed by zero differential estimator are relevant to the system scale under the accuracy constraint. This will result in low time efficiency when the system scale is very large. In this paper, we thus propose a scale‐independent algorithm for differential estimation called zero‐one differential estimator. The numbers of tags moved in and out are estimated from the idle slots in two consecutive frames. We can prove that the time slots consumed in our proposed algorithm are not relevant to the system scale under the accuracy constraint. Moreover, we conduct abundant simulations to evaluate the performance of the proposed approach. The simulation results show that the estimation error grows little as the system scale grows. It indicates that our proposed algorithm is indeed scale‐independent. Copyright © 2015 John Wiley & Sons, Ltd.     

基于多天线的微蜂窝微波移动通信信道建模研究

城市微蜂窝移动通信电波传播环境相当复杂,因此建立这种无线传播信道的有效模型无论对理论分析、系统优化设计以及网络工程规划来说都是非常重要的.特别是针对未来陆地蜂窝移动通信系统基于智能天线应用的规范标准要求尤其如此.为此从多径色散信道的特性分析出发,采用电磁散射理论建立了基于多天线的微蜂窝多输入多输出物理信道模型,对刻画信道特性的一些重要性能参数,如空间相关性、容量和时间演化等进行了研究和仿真分析.与有关文献结果的比较表明了所建立的微蜂窝移动通信信道模型的有效性.     

Estimation of the number of operating sensors in large-scale sensor networks with mobile access

This paper investigates the estimation of the number of operating sensors in a sensor network in which the data collection is made by a mobile access point. In this paper, an estimator based on the Good-Turing estimator of the missing mass is proposed and it is generalized to other related problems such as the estimation of the distribution of energy available at sensors. The estimator is analyzed using the theory of large deviations. Closed-form bounds on the large deviation exponent are presented and confidence intervals for the estimator are characterized.     

A Hybrid SS–ToA Wireless NLoS Geolocation Based on Path Attenuation: ToA Estimation and CRB for Mobile Position Estimation

We propose a new hybrid wireless geolocation scheme that requires only one observation quantity, namely, the received signal. The attenuation model is explored herein to capture the propagation features from the received signal. Thus, it provides a more accurate approach for wireless geolocation. To investigate geolocation accuracy, we consider the time-of-arrival (ToA) estimation in the presence of path attenuation. The maximum-correlation (MC) estimator is revisited, and the exact maximum-likelihood (ML) estimator is derived to estimate the ToA. The error performance of the ToA estimates is derived using a Taylor expansion. It is shown that the ML estimate is unbiased and has a smaller error variance than the MC estimate. Numerical results illustrate that, for a low effective bandwidth, the ML estimator well outperforms the MC estimator. Afterward, we derive the CramÉr–Rao bound (CRB) for the mobile position estimation. The obtained result, which is applicable to any value of path loss exponents, gives a generalized form of the CRB for the ordinary geolocation approach. In seven hexagonal cells, numerical examples show that the accuracy of the mobile position estimation exploring the path loss is improved compared with that obtained by the usual geolocation.      

The interior-point method for an optimal treatment of bias in trilateration location

This paper presents a new position-determination estimator for trilateration location. The proposed estimator takes the measurement bias into consideration and improves the location accuracy of a mobile location system. In case that a mobile station (MS) utilizes signals from a set of base stations for its location, the computed location is largely affected by nonline-of-sight (NLOS) error in signal propagation. A constrained optimization method in a three-stage estimation structure is proposed to estimate and eliminate the measurement bias contained in each pseudorange and mainly caused by the NLOS error. A linear observation model of the bias is formulated, and the interior-point optimization technique optimally estimates the bias by introducing a feasible range of the measurement bias. It is demonstrated that the new three-stage estimator successfully computes an accurate location of an MS in a realistic environment setting. The location accuracy of the proposed estimator is analyzed and compared with the existing methods through mathematical formulations and simulations. The proposed estimator efficiently mitigates the effect of a measurement bias and shows that the iterated least square (ILS) accuracy of 118 m [67% distance root-mean-square (DRMS)] can be improved to about 17 m in a typical urban environment.     

On the blind estimation of the parameters of continuous phase modulated signals

In this paper, a blind estimator of the technical parameters of continuous phase modulated (CPM) signals is proposed. It consists in estimating jointly the modulation index, the symbol period and the frequency offset. It is based on the following observations. First, the inverse of the index is the smallest positive real number a CPM signal should be raised to in order to generate a deterministic harmonic signal; second, the frequencies of the harmonic signal are simply related to the symbol period and the carrier frequency. The practical implementation of this joint estimator is described and the asymptotic behavior of the estimation error is studied. If N is the number of signaling intervals, the estimate of the modulation index is shown to converge to a non-Gaussian distribution at rate 1/N, while the estimate of the frequency offset and the estimate of the symbol period converge at rate 1/N/sup 3/2/. We also investigate the case where the modulation index and the symbol period are available at the receiver side. An estimator of the frequency offset is proposed by adapting the above joint estimator to the latter case. The asymptotic behavior of this estimator is studied and compared with the case where all of the parameters are unknown, so as to evaluate the possible degradation of the performance due to the ignorance of certain technical parameters. Simulations results sustain our theoretical claims.     

Data-adaptive evolutionary spectral estimation

We present a novel data-adaptive estimator for the evolutionary spectrum of nonstationary signals. We model the signal at a frequency of interest as a sinusoid with a time-varying amplitude, which is accurately represented by an orthonormal basis expansion. We then compute a minimum mean-squared error estimate of this amplitude and use it to estimate the time-varying spectrum at that frequency, all while minimizing the interference from the signal components at other frequencies. Repeating the process over all frequencies, we obtain a power distribution that is consistent with the Wold-Cramer evolutionary spectrum and reduces to Capon's (1969) method for the stationary case. Our estimator possesses desirable properties in terms of time-frequency resolution and positivity and is robust in the spectral estimation of noisy nonstationary data. We also propose a new estimator for the autocorrelation of nonstationary signals. This autocorrelation estimate is needed in the data-adaptive spectral estimation. We illustrate the performance of our estimator using simulation examples and compare it with the recently presented evolutionary periodogram and the bilinear time-frequency distribution with exponential kernels     

Rapid estimation of the range-Doppler scattering function

Under wide sense stationary uncorrelated scattering (WSSUS) conditions, the signal spreading due to a random channel may be described by the scattering function (SF). In an active acoustic system, the received signal is modeled as the superposition of delayed and Doppler spread replicas of the transmitted waveform. The SF completely describes the second-order statistics of a WSSUS channel and can be considered a density function that characterizes the average spread in delay and Doppler experienced by an input signal as it passes through the channel. The SF and its measurement will be reviewed. An estimator is proposed based on a two-dimensional (2-D) autoregressive (AR) model for the scattering function. In order to implement this estimator, we derive the conditional minimum variance unbiased estimator of the time-varying frequency response of a linear channel. Unlike conventional Fourier methods, the AR approach does not suffer from the usual convolutional smoothing due to the signal ambiguity function. Simulation results are given.     

Parabolic distribution of scatterers for street-dominated mobile environments

We propose a parabolic scattering model (PSM) to complement the widely used circular scattering model for street-dominated environments, where street canyons favor propagation in narrow angular ranges centered on the street direction. The proposed model is based on the recently introduced semi-geometrically based statistical (SGBS) model and the geometric classification (GEC). The SGBS model defines the distribution of scatterers contributing to the final reradiation of multipath components to the receiver and the GEC defines spatio-temporal clusters using a geometric approach, which simulates different propagation classes based on their suitability to specific radio environments. Expressions are then provided for the power azimuthal spectrum (PAS), angular constriction, variance of received power, and Doppler spectrum (DS) using the PSM, all of which are obtained as seen from the mobile unit. Results for the PSM are also compared with the experimental data provided for dense urban macrocells, for which it has been shown that the proposed model produces PAS and DS that closely agree with the measurement.     

Quorum-Based Asynchronous Power-Saving Protocols for IEEE 802.11 Ad Hoc Networks

This paper investigates the power mode management problem for an IEEE 802.11-based mobile ad hoc network (MANET) that allows mobile hosts to tune to the power-saving (PS) mode. There are two major issues that need to be addressed in this problem: (a) wakeup prediction and (b) neighbor discovery. The former is to deliver buffered packets to a PS host at the right time when its radio is turned on. The latter is to monitor the environment change under a mobile environment. One costly, and not scalable, solution is to time-synchronize all hosts. Another possibility is to design asynchronous protocols as proposed by Tseng et al. in [25]. In this paper, we adopt the latter approach and correlate this problem to the quorum system concept. We identify a rotation closure property for quorum systems. It is shown that any quorum system that satisfies this property can be translated to an asynchronous power-saving protocol for MANETs. Thus, the result bridges the classical quorum system design problem in the area of distributed systems to the power mode management problem in the area of mobile ad hoc networks. We derive a lower bound for quorum sizes for any quorum system that satisfies the rotation closure property. We identify a group of quorum systems that are optimal or near optimal in terms of quorum sizes, which can be translated to efficient asynchronous power-saving protocols. We also propose a new e-torus quorum system, which can be translated to an adaptive protocol that allows designers to trade hosts' neighbor sensibility for power efficiency. Simulation experiments are conducted to evaluate and compare the proposed protocols.     

Bayes estimation of reliability in stress-strength model of Weibull distribution with equal scale parameters

The paper provides a Bayesian approach to inference about the reliability in a multicomponent stress-strength system. We consider Bayes' estimator of the system reliability from data consisting of a random sample from the stress distribution and one from the strength distribution when the two distributions are Weibull with equal and known scale parameters. The estimator of λ, ratio of two shape parameters, is also considered. The proposed estimators can be compared with the maximum likelihood estimators (mles). However, the comparison is carried out for single component stress-strength system and the Monte Carlo efficiencies are obtained. It is found that the proposed estimators are better than the corresponding mles.     

Estimation of P[Y

Kundu  D. Gupta  R.D. 《Reliability, IEEE Transactions on》2006,55(2):270-280