Table Of ContentSpringer Theses
Recognizing Outstanding Ph.D. Research
Sicong Liu
Research on the Key
Technologies in
Narrowband Interference
and Impulsive Noise
Mitigation and
Cancellation
Springer Theses
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Sicong Liu
Research on the Key
Technologies in Narrowband
Interference and Impulsive
Noise Mitigation
and Cancellation
Doctoral Thesis accepted by
Tsinghua University, Beijing, China
123
Author Supervisor
Dr. SicongLiu Prof. JianSong
Department Information Electronic Engineering, DTVTechnology
andCommunication Engineering R&D Center
Schoolof Informatics TsinghuaUniversity
Xiamen University Beijing,China
Xiamen, Fujian, China
ISSN 2190-5053 ISSN 2190-5061 (electronic)
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Supervisor s Foreword
Withthecommenceoferaofinternet-of-thingsandthehelpfrombigdata,theneed
for human-human, human-thing and thing-thing communications and intercon-
nections is explosively increasing. To meet the requirements of “massive and
intelligent interconnections” for those important scenarios such as intelligent
lighting, smart grid, vehicular networks and the internet-of-lights, etc., the new
communication technologies to support high rate, ultra-reliability, low latency,
wide coverage and massive connections are emerging. However, the noise and
interference in the communication systems have always been the bottleneck that
limits the system performance. Especially the Narrowband Interference (NBI) and
Impulsive Noise (IN) are special noise and interference that prevailingly exist in
broadband transmission systems. They are quite different from the commonly
perceived additive white Gaussian noise due to the characteristics of difficult to
model, randomness, sparsity and high-intensity. Because of the passive nature,
conventionalmethodscouldn’teffectivelymitigateoraccuratelyeliminatethenoise
andinterference,leadingtoinevitablesystemperformanceloss.Inordertosupport
the effective transmission of broadband communication systems and improve both
thethroughputandQoSofthenext-generationcommunicationnetwork,thiscritical
issue needs to be well addressed.
Based on the classical digital communication theory and the emerging sparse
recovery theory, Dr. Sicong Liu, the author of this book summarized his research
results from his Ph.D. thesis, which investigates this issue from three strategies
including anti-NBI synchronization, time-frequency interleaving against NBI and
IN, and accurate NBI and IN recovery. The main contribution of this thesis is as
follows. First, an efficient anti-NBI frame structure which can be applied for
broadband power line communications was proposed, and an effective synchro-
nization algorithm against NBI was therefore designed. Second, a time-frequency
combinedinterleaverthatisabletomaximizethetime-frequencydiversitygainwas
devised, which can be applied in many broadband transmission scenarios such as
digital terrestrial multimedia broadcasting. It provides a novel and effective inter-
leavingschemeforthereliabletransmissioninthetime-frequencydoublyselective
channel with both NBI and IN. Furthermore, a more important contribution in this
v
vi Supervisor’sForeword
work is that, a sparse recovery and multi-dimensional compressed sensing-based
frameworkofNBIandINestimationwasformulated,inwhichhedesignedseveral
practical algorithms with superior performance for NBI and IN estimation and
cancelation. The proposed schemes have provided novel research regimes and
solutions with both theoretical and practical value for the area of NBI and IN
mitigation.
I do hope that this book can be a good reference to researchers, undergraduate
and graduate students in the area of communications and signal processing, and
provide theoretical and technical support for the design and application of the
next-generation communication systems.
Beijing, China Prof. Jian Song
February 2020
Preface
Withtherapiddevelopmentofbroadbanddigitalcommunications,therequirements
for transmission reliability, effectiveness and stability keep increasing. However,
the ubiquitously existing Barrowband Interference (NBI) and Impulsive Noise
(IN) have become a vital bottleneck constraining the system performance of
broadband communications systems. Due to the complicated characteristics of the
NBI and IN that are different from additive white Gaussian noise, such as ran-
domness,sparsenessandhighintensity,theconventionalmethodscannoteliminate
their impacts effectively. Aimed at this technological difficulty, this thesis is con-
centrated on the main topic of “key technologies in NBI and IN mitigation and
cancelation” based on the theories of digital communications systems and sparse
recovery. The research is taken on the four aspects including frame structure,
interleaving, sparse recovery and noise elimination:
First, concerning about the severe impacts of NBI on the synchronization of
orthogonal frequency division multiplexing systems, the optimized frame structure
design that can effectively mitigate theNBI impactson synchronization is studied.
Optimized synchronization algorithm is proposed to mitigate NBI, which signifi-
cantly improves the accuracy offrame and carrier synchronization in the presence
ofNBI.Thus,anewsignalframestructureforbroadbandtransmission,whichtakes
both spectral efficiency and transmission robustness into consideration, is formed.
Second, considering about the drawback that conventional interleaving tech-
niques cannot simultaneously mitigate NBI and IN effectively, the optimal
time-frequencycombinedinterleavingtechnologyisstudied.Thetechniquesofthe
interleaving parameters optimization and the sub-matrix cyclic shifting for symbol
interleavingareproposedtomaximizebothtimeandfrequencydiversitygains.The
performance of both anti-NBI and anti-IN capability is significantly improved.
Moreover, to solve the crucial problem that conventional anti-NBI methods
cannot exactly reconstruct the NBI, the technology of accurate NBI reconstruction
based on the sparse recovery theory is researched on by exploiting the sparse
property of NBI in the frequency domain. The Compressed Sensing (CS) and
Structured CS (SCS)-based recovery algorithms are proposed. The spatially
multi-dimensional SCS-based recovery algorithm for MIMO systems is proposed.
vii
viii Preface
The research in sparse recovery theory-based NBI estimation is insufficient at
present, so this thesis proffers cutting-edge and novel technology in this field to
improve the performance of NBI estimation significantly, which can be widely
applied to many different broadband transmission systems such as power line and
wireless communications.
Finally,aimedatsolvingthedrawbacksoftheexistinganti-INmethodssuchas
high complexity, low spectral efficiency and inaccuracy, the technology of
multi-dimensional CS-based IN cancelation is studied by exploiting the sparse
property of IN in the time domain. The prior information aided CS-based method,
alongwiththespatiallymulti-dimensionalSCS-basedmethodforINcancelation,is
proposed to effectively guarantee the reliable and efficient broadband transmission
in the channel with severe noise and interference.
Throughtheseresearches,thisthesisprovidestheoreticalbasisandtechnological
essentials for the NBI and IN mitigation and cancelation in the next-generation
broadband digital communications, and facilitates the application and standard-
ization of the proposed technologies.
Xiamen, China Dr. Sicong Liu
January 2020 Assistant Professor
Acknowledgements
I would like to sincerely thank my supervisor, Prof. Jian Song, for his dedicated
guidance on my Ph.D. research. His talent and spirit have inspired me and pushed
meforwardonthewaytoscience.IalsowouldliketothankProf.FangYang,my
co-supervisor,whodevotedhimselftoteachingmehowtodoresearchfromscratch
day by day. Without their help, this book cannot be finished.
I would like to thank other teachers and my colleagues in Digital Television
(DTV)R&Dlaboratory,TsinghuaUniversity,fortheirgreatsupportandhelptomy
researchanddailylifeduringmystudyinthewarmandunforgettableenvironment.
I would like to appreciate the nice colleagues and my current affiliation, the
Department ofInformation &Communication Engineering, School ofInformatics,
Xiamen University, for providing kind support to my career as a researcher.
I would like to acknowledge the National Natural Science Foundation of China
undergrant61901403,andNaturalScienceFoundationofFujianProvinceofChina
under grant 2019J05001, for funding my research.
Finally, I would like to thank all my family for supporting my research career
continuously and greatly.
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