Author: Reza Barazideh Publisher: ISBN: Category : Languages : en Pages :
Book Description
Impulsive noise is a widespread and rapidly growing source of harmful interference in many applications such as vehicular communications, power line communication (PLC), underwater acoustic (UWA) communication, and Internet of Things (IoT). Noise of this type may originate from a variety of sources such as motors, high efficiency lighting, and even other wireless systems such as pulse-type or frequency-modulated continuous wave (FMCW) radars. Impulsive interference can reduce signal quality to the point of reception failure and increase bit errors resulting in degradation in system reliability. Multicarrier transmission techniques and, in particular, orthogonal frequency division multiplexing (OFDM), is proposed to cope with the frequency selectivity of the propagation channel. Although, OFDM provides some level of robustness against impulsivity by spreading the power of impulsive noise over multiple subcarriers, its performance degrades dramatically if the power of impulsive noise exceeds a certain threshold. Many mitigation techniques focus on reducing the interference before it reaches the receiver. In the context of this dissertation, the emphasis is on the reduction of interference that has already entered the signal path. Specifically, this dissertation aims to develop approaches to effectively detect and mitigate the severe impact of the impulsive noise. Here, we investigate two different categories of impulsive noise suppression techniques that can be used as a stand-alone solution or combined with other interference reduction techniques. First, we design and develop Blind Adaptive Intermittently Nonlinear Filters (BAINFs) for analog-domain mitigation of impulsive noise. The idea behind using analog domain mitigation is that insufficient processing bandwidth severely limits the effectiveness of digital nonlinear interference mitigation techniques. Therefore, the suppression of non-Gaussian noise in the analog domain before the analog to digital converter (ADC) where the outliers are more distinguishable can be helpful. The BAINFs can be implemented in many structures and we propose some sample realizations of BAINFs that can be used in different applications. In this dissertation, we consider PLC and UWA communication systems as case studies. The performance of the proposed BAINFs in these systems is quantified analytically and with experimental data. Secondly, in the classic threshold based outlier detection approaches, determining the optimum threshold is the main challenge as this threshold will vary in response to channel conditions and model mismatches. As always, there is a compromise between detection and false alarm probability in the traditional threshold based methods. To overcome this drawback, we propose a two stage impulsive noise mitigation approach. In the first stage, a machine learning approach such as a deep neural network (DNN) is used to detect the instances of impulsivity. Then, the detected impulsive noise can be mitigated in the suppression stage to alleviate the harmful effects of outliers. The robustness of the proposed DNN-based approach under (i) mismatch between impulsive noise models considered for training and testing, and (ii) bursty impulsive environment when the receiver is empowered with interleaving technique is evaluated.
Author: Jia Jia Publisher: ISBN: Category : Noise control Languages : en Pages : 0
Book Description
Compared to additive white Gaussian noise (AWGN), impulsive noise has unique characteristics which include random occurrence, short time duration, wide band spectrum, and high-energy content. Due to these distinctive features, impulsive noise with significant power can degrade the transmission quality of various communication systems. In this research, the impact of impulsive noise on Orthogonal Frequency-Division Multiplexing (OFDM)-based communication systems and ZigBee wireless sensor networks (WSNs) based on direct sequence spread spectrum (DSSS) modulation are addressed. For the purpose of improving system performance, several impulsive noise suppression approaches are proposed for both of the two communication systems mentioned above. First, this research proposes a novel time domain filtering approach for both OFDM and DSSS modulation with the aid of Reed-Solomon (RS) coding and noise estimation to mitigate the influence of impulsive noise on the transmitted signal. This filter utilizes a composite comparison value (CCV) algorithm to improve the accuracy of impulsive noise detection. Performance comparisons with previously proposed filtering and coding methods demonstrate the effectiveness of the CCV filter. In the second case, we describe a new Error-Balanced Wavelet (EB-Wavelet) filtering process for the impulsive noise suppression in ZigBee-based WSNs utilizing DSSS modulation. Theoretical analysis shows that the bit error rate (BER) of ZigBee systems is related to the received noise power and any filter generated distortion. The EB-Wavelet filter employs a multiresolution analysis and weighting matrix for bandwidth management to limit the presence of impulsive noise power while balancing the overall filter distortion. Computer simulations are performed to compare the performance of the proposed EB-Wavelet approach with conventional finite impulse response filters. Results show that the EB-Wavelet filter can further improve the BER performance of ZigBee systems in the presence of significant impulsive noise while maintaining a low complexity of ZigBee receiver design. Additionally, in this dissertation, the impulsive noise performances of 915 MHz and 2.4 GHz band ZigBee communication systems are compared. A novel impulsive noise model based on the statistical characteristics of the impulsive noise measured in electricity substations is proposed and utilized for the comparison procedure. Both theoretical and simulation results show the advantage of deploying the 2.4 GHz band ZigBee in impulsive noise environments in order to enhance transmission quality. However, it may be possible to deploy the 915 MHz band ZigBee for partial discharge fault monitoring in related environments.
Author: Sicong Liu Publisher: Springer Nature ISBN: 9811547246 Category : Technology & Engineering Languages : en Pages : 208
Book Description
This book summarizes the authors’ latest research on narrowband interference and impulsive noise mitigation and cancelation, including (i) mitigating the impacts of NBI on synchronization; (ii) improving time-frequency interleaving performance under NBI and IN; (iii) accurately recovering and eliminating NBI and IN. The complicated, random and intensive narrowband interference and impulsive noise are a serious bottleneck of the next-generation wireless communications and Internet of things. This book also proposes effective and novel frameworks and algorithms, which will significantly improve the capability of mitigating and eliminating NBI and IN in the next-generation broadband communications systems. This book not only presents thorough theoretical models and algorithm design guidelines, but also provides adequate simulation and experimental engineering methods and results. The book is a valuable reference for those engaged in theoretical study, algorithm design and engineering practice in related fields, such as wireless communications, smart lighting, IoT and smart grid communications.
Author: Deep Shrestha Publisher: ISBN: Category : Languages : en Pages : 183
Book Description
Power line communication (PLC) is considered as the most viable enabler of the smart grid. PLC exploits the power line infrastructure for data transmission and provides an economical communication backbone to support the requirements of smart grid applications. Though PLC brings a lot of benefits to the smart grid implementation, impairments such as frequency selective attenuation of the high-frequency communication signal, the presence of impulsive noise (IN) and the narrowband interference (NBI) from closely operating wireless communication systems, make the power line a hostile environament for reliable data transmission. Hence, the main objective of this dissertation is to design signal processing algorithms that are specifically tailored to overcome the inevitable impairments in the power line environment.First, we propose a novel IN mitigation scheme for PLC systems. The proposed scheme actively estimates the locations of IN samples and eliminates the effect of IN only from the contaminated samples of the received signal. By doing so, the typical problem encountered while mitigating the IN is avoided by using passive IN power suppression algorithms, where samples besides the ones containing the IN are also affected creating additional distortion in the received signal.Apart from the IN, the PLC transmission is also impaired by NBI. Exploiting the duality of the problem where the IN is impulsive in the time domain and the NBI is impulsive in the frequency domain, an extended IN mitigation algorithm is proposed in order to accurately estimate and effectively cancel both impairments from the received signal. The numerical validation of the proposed schemes shows improved BER performance of PLC systems in the presence of IN and NBI.Secondly, we pay attention to the problem of channel estimation in the power line environment. The presence of IN makes channel estimation challenging for PLC systems. To accurately estimate the channel, two maximumlikelihood (ML) channel estimators for PLC systems are proposed in this thesis.Both ML estimators exploit the estimated IN samples to determine the channel coefficients. Among the proposed channel estimators, one treats the estimated IN as a deterministic quantity, and the other assumes that the estimated IN is a random quantity. The performance of both estimators is analyzed and numerically evaluated to show the superiority of the proposed estimators in comparison to conventional channel estimation strategies in the presence of IN. Furthermore, between the two proposed estimators, the one that is based on the random approach outperforms the deterministic one in all typical PLC scenarios. However, the deterministic approach based estimator can perform consistent channel estimation regardless of the IN behavior with less computational effort and becomes an efficient channel estimation strategy in situations where high computational complexity cannot be afforded.Finally, we propose two ML algorithms to perform a precise IN support detection. The proposed algorithms perform a greedy search of the samples in the received signal that are contaminated by IN. To design such algorithms, statistics defined for deterministic and random ML channel estimators are exploited and two multiple hypothesis tests are built according to Bonferroni and Benjamini and Hochberg design criteria. Among the proposed estimators, the random ML-based approach outperforms the deterministic ML-based approach while detecting the IN support in typical power line environment.Hence, this thesis studies the power line environment for reliable data transmission to support smart grid. The proposed signal processing schemes arerobust and allow PLC systems to effectively overcome the major impairments in an active electrical network.The efficient mitigation of IN and NBI and accurate estimation of channel enhances the applicability of PLC to support critical applications that are envisioned for the future electrical power grid.
Author: Kyoungnam Seo Publisher: ISBN: Category : Languages : en Pages :
Book Description
(MMSE) multi-user detector and transmit power control, which results in an enhanced signal-to-noise ratio (SNR) and reduced transmit power consumption. In PLC systems, OFDM is combined with a bit-loading algorithm to increase throughput. Since the number of bits to carry at each sub-carrier is assigned by the SNR level, the throughput of the system is directly affected by impulsive noise. Our study focuses on the detection and mitigation of impulsive noise in PLC networks. We propose a time domain impulsive noise mitigation algorithm. This two-step iterative algorithm improves the data rate by up to 15 percent with a small addition of one OFDM block size memory. Finally, we consider SS-MC-MA systems that take advantage of DMT's adaptive bit-loading technique and CDMA's multi-user channel access. To further increase the throughput, we propose a dynamic sub-carrier allocation algorithm in SS-MC-MA-based PLC systems. Systems with the proposed algorithm show the average throughput increase up to 20 percent comparing to the conventional DMT systems and 10 percent comparing to the existing SS-MC-MA-based PLC systems.
Author: Manuel Graña Publisher: Springer ISBN: 3319473646 Category : Technology & Engineering Languages : en Pages : 813
Book Description
This volume of Advances in Intelligent and Soft Computing contains accepted papers presented at SOCO 2016, CISIS 2016 and ICEUTE 2016, all conferences held in the beautiful and historic city of San Sebastián (Spain), in October 2016. Soft computing represents a collection or set of computational techniques in machine learning, computer science and some engineering disciplines, which investigate, simulate, and analyze very complex issues and phenomena. After a through peer-review process, the 11th SOCO 2016 International Program Committee selected 45 papers. In this relevant edition a special emphasis was put on the organization of special sessions. Two special session was organized related to relevant topics as: Optimization, Modeling and Control Systems by Soft Computing and Soft Computing Methods in Manufacturing and Management Systems. The aim of the 9th CISIS 2016 conference is to offer a meeting opportunity for academic and industry-related researchers belonging to the various, vast communities of Computational Intelligence, Information Security, and Data Mining. The need for intelligent, flexible behaviour by large, complex systems, especially in mission-critical domains, is intended to be the catalyst and the aggregation stimulus for the overall event. After a through peer-review process, the CISIS 2016 International Program Committee selected 20 papers. In the case of 7th ICEUTE 2016, the International Program Committee selected 14 papers.
Author: Xiaodong Wang Publisher: Prentice Hall Professional ISBN: 9780130214355 Category : Computers Languages : en Pages : 716
Book Description
Wireless Communication Systems: Advanced Techniques for Signal Receptionoffers a unified frameworkfor understanding today's newest techniques for signal processing in communication systems - andusing them to design receivers for emerging wireless systems. Two leading researchers cover a fullrange of physical-layer issues, including multipath, dispersion, interference, dynamism, andmultiple-antenna systems. Topics include blind, group-blind, space-time, and turbo multiuserdetection; narrowband interference suppression; Monte Carlo Bayesian signal processing; fast fadingchannels; advanced signal processing in coded OFDM systems, and more.
Author: Xu Zhu Publisher: Artech House ISBN: 1630818100 Category : Technology & Engineering Languages : en Pages : 240
Book Description
This exciting resource covers the fundamentals of wireless and PLC technologies. Different types of wireless and PLC technologies used for indoor IoT applications are described. The channel models for both wireless and power line communications are introduced, highlighting the main challenges for these types of communications inside the indoor environment. The book explores the hybrid technologies with television white space (TVWS), very high frequency (VHF) wireless technology, and broadband PLC (BPLC) for indoor high speed IoT networks. A TVWS standardized BPLC system is proposed, which integrates the requirement of primary user sensing and the permissible transmission power spectral density (PSD) for TVWS users into BPLC standard, regarding VHF band access. The hybrid ultra-high frequency (UHF) wireless-powerline sensor networks with a focus on enlarging the network lifetime via cross-layer optimization is presented. Hybrid video sensor networks (HVSNs) with high data rate requirement are explored. Through the joint design of video encoding rate, aggregate power consumption, channel access control, along with link rate allocation, a distributed algorithm is developed, which divides the computational burden among all nodes with much lower communication overhead. The effectiveness of the cross-layer designs are evaluated through extensive simulation results.
Author: Reza Barazideh
Author: Jia Jia
Author: Anser Mehboob
Author: Sicong Liu
Author: Deep Shrestha
Author: Kyoungnam Seo
Author: Manuel Graña
Author: Xiaodong Wang
Author: Saeed V. Vaseghi
Author: Xu Zhu