DESIGN OF INTERPOLATION FILTER FOR ALL DIGITAL RECEIVER-ON THE INTERPOLATION PROBLEM OF FULL RESPONSE MODULATION SIGNALS

All digital implementation of receiver is a main topic on digital communication recently. The design of interpolation filter is one of the important problems for all digital implementation of receiver. In this paper, for full response linear modulation signal, a interpolation criterion is proposed. An interpolation formula is presented on bandwidth-limited transmission signal. For example, using the raised cosine roll off function as the system pulse response, the feasibility and effectiveness on the interpolation formula are certified by theoretical and numerical analysis. The computer simulation result on 16-QAM signal is given.

Acquisition of Weak Signals in Multi-Constellation Frequency Domain Receivers

New positioning applications’ availability requirements demand receivers with higher sensitivities and ability to process multiple GNSS signals. Possible applications include acquiring one signal per GNSS constellation in the same frequency band and combining them for increased sensitivity or predicting acquisition of other signals. Frequency domain processing can be used for this purpose, since it benefits from parallel processing capabilities of Fast Fourier Transform (FFT), which can be efficiently implemented in software receivers. On the other hand, long coherent integration times are mainly limited due to large FFT size in receivers using frequency domain techniques. A new method is proposed to address the problems in frequency domain receivers without compromising the resources and execution time. A pre-correlation accumulation (PCA) is proposed to partition the received samples into one-code-period blocks, and to sum them together. As a result, the noise is averaged out and the correlation results will gain more power, provided that the relative phase between the data segments is compensated for. In addition to simplicity, the proposed PCA method enables the use of one-size FFT for all integration times. A post-correlation peak combination is also proposed to remove the need for double buffering. The proposed methods are implemented in a configurable Simulink model, developed for acquiring recorded GNSS signals. For weak signal scenarios, a Spirent GPS simulator is used as a source. Acquisition results for GPS L1 C/A and GLONASS L1OF are shown and the performance of the proposed technique is discussed. The proposed techniques target GNSS receivers using frequency domain processing aiming at accommodating all the GNSS signals, while minimizing resource usage. They also apply to weak signal acquisition in frequency domain to answer the availability demand of today’s GNSS positioning applications.

Constrained Weighted Least Squares Location Algorithm Using Received Signal Strength Measurements

Determine the location of a target has gained considerable interest over the past few years. The Received Signal Strength(RSS) measurements and Differential RSS(DRSS) measurements can be converted to distance or distance ratio estimates for constructing a set of linear equations. Based on these linear equations, a constrained weighted least Squares(CWLS) algorithm for target localization is derived. In addition, an iterative technique based on Newton's method is utilized to give a solution. The covariance and bias of the CWLS algorithm is derived using perturbation analysis. Simulation shows that the proposed estimator achieves better performance than existing algorithms with reasonable complexity.

Multi-Variable Flocking Control for Multi-Agent Systems via a Received Signal Strength Indicator

A novel flocking control approach is proposed for multi-agent systems by integrating the variables of velocities, motion directions, and positions of agents. A received signal strength indicator （RSSI） is applied as a variable to estimate the inter-distance between agents. A key parameter that contains the local information of agents is defined, and a multi-variable controller is proposed based on the parameter. For the position control of agents, the RSSI is introduced to substitute the distance as a control variable in the systems. The advantages of RSSI include that the relative distance between every two agents can be adjusted through the communication quality under different environments, and it can shun the shortage of the limit of sensors. Simulation studies demonstrate the effectiveness of the proposed control approach.

Robust digital receiver for EPC sensor network

A robust digital receiver based on a matched filter （MF） is proposed for the radio frequency identification （RFID） reader system to enhance the reliability of signal processing in the electronic product code （EPC） sensor network （ESN）. The performance of the proposed receiver is investigated by examining the anti-collision algorithm in the EPC global Class1 Generation2 protocol. The validity and usefulness are demonstrated by both computer simulations and experiments. Based on the verification results, comparing with the conventional zero crossing detector （ZCD） based receiver, the proposed receiver is very robust against strong amplitude distortions and considerable frequency deviations happening on the backscattered signal from a passive tag.

A HIGH SENSITIVITY AND WIDE DYNAMIC RANGE ZERO-IF RF RECEIVER FOR COGNITIVE RADIO APPLICATION

This paper presents an RF receiver of zero-Intermediate Frequency(IF) architecture for Cognitive Radio(CR) communication systems.Zero-IF architecture reduce the image reject filter and IF filter,so it is excellent in low cost,compact volume,and low power dissipation.The receiver employs three digital attenuator and a high gain,high linearity low noise amplifier to achieve wide dynamic range of 70 dB and high receiving sensitivity of-81 dBm.A fully balanced I/Q demodulator and a differential Local Oscillator(LO) chips are used to minimize the negative effects caused by second-order distortion and LO leakage.In order to select an 8 MHz-channel from 14 continuous ones located in UHF band(694-806 MHz) accurately,approach of channel selectivity circuits is proposed.The RF receiver has been designed,fabricated,and test.The measured result shows that the noise figure is 3.4 dB,and the error vector magnitude is 7.5% when the input power is-81 dBm.

S^3 LQA: A Link Quality Assessment Metric for WSNs Based on Symbol Error and Received Signal Strength

With the rapid evolution of WSNs technology, it is very important to evaluate link quality quickly and accurately, so that the routing protocols can take relevant strategies in time to keep the entire network working steadily and efficiently. However, the issue of layer is still open to research. To tackle this issue, a improving link quality assessment methods on physical novel link quality assessment metric called S3LQA is proposed, which estimates the link quality of wireless sensor networks by CC2420 wireless radio frequency transceiver principles and free space propagation theory. The metric adopts both complete and incomplete packages to improve the evaluation performance effectively based on IEEE802. 15.4 frame format and DSSS-O- QPSK mechanism. The experimental results show that the proposed method can improve energy cost and achieves hatter real-timin nerformance than traditional counting-based （PRR） link aualitv assessment metric.

Broad-Band All-Optical Wavelength Conversion of Differential Phase-Shift Keyed Signal Using an SOA-Based Nonlinear Polarization Switch

Broad-band all-optical wavelength conversion of differential phase-shift keyed （DPSK） signal is experimentally demonstrated. This scheme is composed of a one-bit delay interferometer demodulation stage followed by a semiconductor optical amplifier （SOA） based nonlinear polarization switch. A wavelength converter for the 10 G b/s DPSK signal is presented, which has a wide wavelength range of more than 30 nm. The converted signals experience small power penalties less than 1.4 dB compared with the original signal, at a bit error rate of 10-9. Additionally, the optical spectra, the measured waveforms and the open eye diagrams of the converted signals show a high quality wavelength conversion performance.

A sign-function receiving scheme for sine signals enhanced by stochastic resonance

To address the problem that it is difficult to detect an intermediate frequency(IF)signal at the receiving end of a communication system under extremely low signal-to-noise ratio(SNR)conditions,we propose a stochastic resonance(SR)-enhanced sine-signal detection method based on the sign function.By analyzing the SR mechanism of the sine signal and combining it with the characteristics of a dual-sequence frequency-hopping(DSFH)receiver,a periodic stationary solution of the Fokker-Planck equation(FPE)with a time parameter is obtained.The extreme point of the sine signal is selected as the decision time,and the force law of the electromagnetic particles is analyzed.A receiving structure based on the sign function is proposed to maximize the output difference of the system,and the value condition of the sign function is determined.In order to further improve the detection performance,in combination with the central-limit theorem,the sampling points are averaged N times,and the signal-detection problem is transformed into a hypothesis-testing problem under a Gaussian distribution.The theoretical analysis and simulation experiment results confirm that when N is 100 and the SNR is greater than 20 dB,the bit-error ratio(BER)is less than 1.5×10^(-2) under conditions in which the signal conforms to the optimal SR parameters.

Accuracy Analysis of Position Estimation Based on Measurements of Received Signal Strength Difference

The performance of a cellular location system based on received signal strength difference （RSSD） is investigated. In the cellular location system, each mobile station needs to measure the signal strength transmitted by surrounding base stations, and sends its measurements to the service base station. Using the strength difference between the service base station and neighboring base stations, the position of a mobile station is estimated. The related Cramer-Rao lower bound （CRLB） on the location error of this method was derived, and numerical simulations are made to discuss the influences of the number of base stations, correlation coefficient of shadowing attenuation, and cell radius on CRLB. The results show that the CRLB is positively correlated with the standard deviation of shadowing attenuation and cell radius, but negatively correlated with the number of base stations and the correlation coefficient of shadowing attenuation. In addition, the CRLB results obtained in this paper were compared with those of the cellular location system based on received signal strength （RSS） measurements, which reveals that the former is more tight.

Improved Circular Correlation Methods for Acquisition in Software GPS Receiver

In this paper the authors explore the Global Positioning System （GPS） signal acquisition and tracking algorithms used in software GPS receiver. Acquisition time is the most important parameter in evaluating the performance of a software GPS receiver in terms of its speed. A trade-off study is done to seek a good balance between the acquisition accuracy and the processing time. The frequency-domain acquisition method by circular correlation, used in a software GPS receiver, has been improved by studying the power spectrum of the Coarse Acquisition （C/A） code alone. The analysis of C/A code reveals that its power spectrum is symmetrical; hence only half the points are required to perform circular correlation. Besides, either half of the spectrum is asymmetrical where a larger amount of power is concentrated in almost one-quarter of the spectrum on its either sides. This further reduces the number of points used to perform correlation. Comparative results of MATLAB simulation of full-size, half-size and quarter-size circular correlation done on actual data stored on hard disk are provided, and they agree with those obtained using GPS receiver. Further reduction in acquisition time has been achieved by investigating the effect of length of the noncoherent pre-integration period. The improved acquisition methods pave way for further development of new algorithms to enhance software GPS receiver performance.

Analysis of RFID Based Positioning Technique Using Received Signal Strength and Directional Antenna

Automatic robot navigation is being utilized in many industries for the purpose of high speed work delivery. Color follower, fix path follower robots are current solution to this activities but dynamic path configuration is not possible in these robots. Hence new system proposes effective and fully dynamic path follower robots using RFID and directional antenna. Radio Frequency Identification (RFID) system permits automatic identification of objects with RFID tags using radio waves which have been widely used in mobile robot navigation, localization and mapping both in indoor and outdoor environment. This article presents a navigation strategy for autonomous mobile robot using passive RFID system. Proposed robot system is provided with RFID tag functionality which will load tag number and direction instruction. At some turning point, user will put RF tag, this tag will be read by RF reader which is placed on robot. As per direction instruction robot will change the direction and reach to the destination. Also as per the movement, robot will send its GPS location to PC (Personal Computer) which will be displayed on PC. Hence main goal is to provide more reliable and low energy consumption based indoor positioning system which will be achieved using directional antenna.

面向城区的基于图去噪的小区级RSRP估计方法

移动通信系统网络的规划、部署和优化都不同程度依赖于参考信号接收功率(RSRP)估计的准确性。传统上,基站覆盖小区内某信号接收点的RSRP可由对应的无线传播模型估计。在城市环境中,不同小区的无线传播模型需要使用大量RSRP实测数据校正。由于不同小区环境存在差异,经过校正后的模型只适用于对应小区,且小区内的RSRP估计精度低。针对上述问题,将RSRP估计问题转化为图去噪问题,并通过图像处理与深度学习技术得到小区级无线传播模型,不仅能实现小区整体的RSRP估计,且能适用于相似环境小区。首先,通过随机森林回归器逐点预测每个接收点的RSRP,得到整个小区的RSRP估计图;然后,将RSRP估计图和实测RSRP分布图之间的损失视为RSRP噪声图,提出基于条件生成对抗网络(CGAN)的图去噪RSRP估计方法,通过电子环境地图反映小区的环境信息,有效地降低不同小区的RSRP。实验结果表明,在无实测数据的跨小区RSRP预测场景下,所提方法预测RSRP的均方根误差(RMSE)为6.77 dBm,相较于基于卷积神经网络的RSRP估计方法EFsNet下降2.55 dBm;在同小区RSRP预测场景下,相较于EFsNet,模型参数量减小80.3%。

基于特征值的动态数字信道化子带检测算法

动态数字信道化接收结构通过检测所有子带,判断信号是否存在,为综合滤波器组处理提供依据,因此子带检测在接收结构中起着关键作用。针对传统检测算法存在低信噪比(signal-to-noise ratio,SNR)下检测性能不高的问题,依据随机矩阵理论,提出了基于最大最小特征值之差与平均特征值之比的检测算法,利用平均特征值和最小特征值的极限分布规律来推导算法的检测门限。其次,根据所有子带数据获取的特征值信息对所提算法进行了优化。最后,在动态数字信道化接收结构中,分析不同因素下算法的性能,表明了所提算法能够克服低SNR的影响,子带检测的性能更好。

一种WiFi混合滤波的RSSI室内定位算法

针对接收信号强度指示(RSSI)在基于WiFi的室内定位应用中易受到环境影响出现波动、突变进而导致定位精度降低的问题,提出了一种WiFi混合滤波的RSSI室内定位算法。首先,根据WiFi信号距离衰减模型设计一种自适应阈值滤波器剔除观测信号异常值;然后,根据自适应阈值滤波、卡尔曼(Kalman)滤波、均值(Mean)滤波设计了一种混合滤波算法(ATKM)对RSSI数据进行滤波;最后,提出了一种基于斯皮尔曼-欧几里得距离的加权K近邻算法(SEWKNN)进行位置估计。在真实环境下的实测结果表明,本文提出的ATKM滤波算法能显著降低RSSI信号的波动,提出的SEWKNN算法在室内环境中平均定位误差为1.17 m,在走廊环境中平均定位误差为1.53m,相比传统的WKNN算法平均定位误差分别下降18.18%和16.84%。

多RIS辅助车载通信信号优化及部署规划

针对匀变速运动的汽车产生的多普勒扩展和时延扩展以及接收信噪比的问题,提出了一种多智能超表面(RIS)辅助匀变速移动物体通信的方案。与传统信道估计不同的是,使用了信道增益的方法和优化RIS相位以及多目标优化来让移动物体能达到最大接收瞬时信噪比的同时,获得小的多普勒扩展和时延扩展。通过优化后的RIS相位来研究RIS的位置对接收信号的影响,分别研究了RIS之间的距离以及RIS之间距离一定时,RIS摆放在什么位置使得接收信号的信噪比以及时延扩展保持较低的范围,对于这个问题提出了相对运动的理论,且各自提出一种算法解决这两个问题。仿真表明,多RIS辅助的通信系统对车载通信接收信号的功率提升了约10 dB。RIS的部署位置应该让第一个RIS靠近基站并且RIS之间的距离在现实允许的情况下尽可能靠近。由此多RIS的通信方案可以广泛应用于车载通信中。

欧美月球GNSS规划现状分析综述

月球是地球最重要的天然卫星,当前国际上正在迎来新一轮月球探索高潮,数十个机构和商业团队正在规划月球探索任务,并设想在未来实现航天员长期驻月,围绕月球的“太空竞赛”刚刚开始。月球GNSS(基于现有的地球GNSS以及新的环月卫星通信导航基础设施的月球卫星通信导航定位技术)是空间基准科研的基础,能够提供航天器着陆定位以及月面(及其覆盖空间)定位、导航与授时等服务,同时可以将月球作为试验场,将导航工具包扩展到更远的目的地(如火星)。对欧美近期发布的月球GNSS规划进行了整理归纳,其中包括美国月球GNSS接收机实验(LuGRE)计划和欧洲月光(MoonLight)计划,以及美国中远期月球通信中继和导航系统(LCRNS)计划,这些计划可以为我国开展月球GNSS规划提供参考。

基于RSSR融合RNGO-Elman神经网络的室内可见光定位

针对动态环境下基于接收信号强度的传统可见光定位方法定位精度低、稳定性差等问题,提出一种基于接收信号强度比的改进北方苍鹰算法(NGO)优化Elman神经网络(RNGOElman)的室内可见光定位系统。提出选择一个辅助参考点,将待测参考点与辅助参考点的接收信号强度比值和接收机的真实位置作为训练集数据,建立不受动态环境影响的指纹数据库。针对NGO算法收敛速度慢、容易陷入局部最优等问题,利用折射反向学习策略初始化种群,增加种群多样性,引入非线性权重因子来加快收敛速度,避免陷入局部最优。使用优化后的NGO算法来优化Elman神经网络的初始权值和阈值,构建RNGO-Elman动态定位预测模型。仿真结果表明,在4m×4m×3m的实验空间下,优化后的RNGO-Elman定位模型平均定位误差为1.34cm,定位精度相较于Elman定位算法、NGO-Elman定位算法分别提高了82%,21%。在LED发射功率波动时,基于RSSR的RNGO-Elman定位误差为1.29cm,1.38cm。所提可见光定位方法具有定位精度高、定位性能稳定等优点。

基于自适应距离ADWKNN室内定位算法

针对基于蓝牙接收信号强度(RSS)的加权K-近邻(WKNN)位置指纹室内定位算法中由于信号波动存在的单一距离估算标准导致定位精度偏低的问题,提出了一种基于自适应距离的ADWKNN定位算法。离线阶段利用K-means聚类算法对指纹数据库进行划分,减少数据查询量以保证定位的时效性。在线定位阶段首先对待定位点处采集到的RSS信号值进行卡尔曼滤波,减弱随机噪声的干扰;然后采用ADWKNN算法计算曼哈顿距离与欧氏距离的标准差,自适应的选择距离估算方法并实现K值的动态变化。实验结果表明,ADWKNN算法的平均定位精度为1.22 m,与使用余弦距离、曼哈顿距离、欧氏距离和Sorensen距离的单一距离的WKNN算法相比,ADWKNN算法的平均定位精度有明显提高。

扩展卡尔曼滤波的改进蛇定位算法在WSN中的应用

针对接收信号强度指示(Received Signal Strength Index,RSSI)定位易受到环境因素的影响,提出了一种基于RSSI扩展卡尔曼滤波的改进蛇定位算法(RSSI Extended Kalman Filter-based Improved Snake Optimization Localization Algorithm,RSSI-EISL)。该算法利用扩展卡尔曼滤波(Extended Kalman Filter,EKF)模型对RSSI信号值进行平滑处理,使其能够抑制噪声和异常值对估计结果的影响,从而提高测距的准确性和鲁棒性。通过引入Levy飞行和非线性收敛因子的改进蛇优化算法(Improved Snake Optimization Algorithm,ISO),提升了蛇优化算法(Snake Optimization Algorithm,SO)的寻优能力,使之能够更加准确地计算出待测节点的坐标。根据仿真结果显示,相较于基于RSSI最小二乘定位算法(RSSI Ordinary Least Squares Localization Algorithm,ROL)、基于RSSI EKF的灰狼定位算法(RSSI Extended Kalman Filter-based Grey Wolf Optimization Algorithm,REGL)和基于RSSI EKF的蛇定位算法(RSSI EKF-based Snake Optimization Localization Algorithm,RESL),RSSI-EISL的定位精度分别提高了26.4%、8.75%和5.6%,算法的收敛速度和全局搜索能力也有所提升。