104 research outputs found
Bridging the complexity gap in Tbps-achieving THz-band baseband processing
Recent advances in electronic and photonic technologies have allowed
efficient signal generation and transmission at terahertz (THz) frequencies.
However, as the gap in THz-operating devices narrows, the demand for
terabit-per-second (Tbps)-achieving circuits is increasing. Translating the
available hundreds of gigahertz (GHz) of bandwidth into a Tbps data rate
requires processing thousands of information bits per clock cycle at
state-of-the-art clock frequencies of digital baseband processing circuitry of
a few GHz. This paper addresses these constraints and emphasizes the importance
of parallelization in signal processing, particularly for channel code
decoding. By leveraging structured sub-spaces of THz channels, we propose
mapping bits to transmission resources using shorter code words, extending
parallelizability across all baseband processing blocks. THz channels exhibit
quasi-deterministic frequency, time, and space structures that enable efficient
parallel bit mapping at the source and provide pseudo-soft bit reliability
information for efficient detection and decoding at the receiver
A Tutorial on Coding Methods for DNA-based Molecular Communications and Storage
Exponential increase of data has motivated advances of data storage
technologies. As a promising storage media, DeoxyriboNucleic Acid (DNA) storage
provides a much higher data density and superior durability, compared with
state-of-the-art media. In this paper, we provide a tutorial on DNA storage and
its role in molecular communications. Firstly, we introduce fundamentals of
DNA-based molecular communications and storage (MCS), discussing the basic
process of performing DNA storage in MCS. Furthermore, we provide tutorials on
how conventional coding schemes that are used in wireless communications can be
applied to DNA-based MCS, along with numerical results. Finally, promising
research directions on DNA-based data storage in molecular communications are
introduced and discussed in this paper
Polar codes combined with physical layer security on impulsive noise channels
Ph. D. ThesisThe need for secure communications is becoming more and more impor-
tant in modern society as wired and wireless connectivity becomes more
ubiquitous. Currently, security is achieved by using well established
encryption techniques in the upper layers that rely on computational
complexity to ensure security. However, processing power is continu-
ally increasing and well-known encryption schemes are more likely to be
cracked. An alternative approach to achieving secure communication is
to exploit the properties of the communication channel. This is known as
physical layer security and is mathematically proven to be secure. Phys-
ical layer security is an active research area, with a significant amount
of literature covering many different aspects. However, one issue that
does not appear to have been investigated in the literature is the effect
on physical layer security when the noise in the communication channel
is impulsive. Impulsive noise adds large spikes to the transmitted signal
for very short durations that can significantly degrade the signal. The
main source of impulsive noise in wireless communications is electromag-
netic interference generated by machinery. Therefore, this project will
investigate the effect of impulsive noise on physical layer security.
To ensure a high level of performance, advanced error-correcting codes
are needed to correct the multiple errors due to this harsh channel. Turbo
and Low-Density Parity-Check (LDPC) codes are capacity-approaching
codes commonly used in current wireless communication standards, but
their complexity and latency can be quite high and can be a limiting fac-
tor when required very high data rates. An alternative error-correcting
code is the polar code, which can actually achieve the Shannon capacity
on any symmetric binary input discrete memoryless channel (B-DMC).
Furthermore, the complexity of polar codes is low and this makes them
an attractive error-correcting code for high data rate wireless commu-
nications. In this project, polar codes are combined with physical layer
security and the performance and security of the system is evaluated on
impulsive noise channels for the first time.
This project has three contributions:
Polar codes designed for impulsive noise channels using density evo-
lution are combined with physical layer security on a wire-tap chan-
nel experiencing impulsive noise.
The secrecy rate of polar codes is maximised. In the decoding of
polar codes, the frozen bits play an important part. The posi-
tions of the frozen bits has a significant impact on performance and
therefore, the selection of optimal frozen bits is presented to opti-
mise the performance while maintaining secure communications on
impulsive noise wire-tap channels.
Optimal puncturing patterns are investigated to obtain polar codes
with arbitrary block lengths and can be applied to different modu-
lation schemes, such as binary phase shift keying (BPSK) and M-
ary Quadrature Amplitude Modulation (QAM), that can be rate
compatible with practical communication systems. The punctured
polar codes are combined with physical layer security, allowing the
construction of a variety of different code rates while maintaining
good performance and security on impulsive noise wire-tap chan-
nels.
The results from this work have demonstrated that polar codes are ro-
bust to the effects of impulsive noise channel and can achieve secure
communications. The work also addresses the issue of security on im-
pulsive noise channels and has provided important insight into scenarios
where the main channel between authorised users has varying levels of
impulsiveness compared with the eavesdropper's channel. One of the
most interesting results from this thesis is the observation that polar
codes combined with physical layer security can achieve good perfor-
mance and security even when the main channel is more impulsive than
the eavesdropper's channel, which was unexpected. Therefore, this thesis
concludes that the low-complexity polar codes are an excellent candidate
for the error-correcting codes when combined with physical layer security
in more harsh impulsive wireless communication channels
Polarization and Spatial Coupling:Two Techniques to Boost Performance
During the last two decades we have witnessed considerable activity in building bridges between the fields of information theory/communications, computer science, and statistical physics. This is due to the realization that many fundamental concepts and notions in these fields are in fact related and that each field can benefit from the insight and techniques developed in the others. For instance, the notion of channel capacity in information theory, threshold phenomena in computer science, and phase transitions in statistical physics are all expressions of the same concept. Therefore, it would be beneficial to develop a common framework that unifies these notions and that could help to leverage knowledge in one field to make progress in the others. A particularly striking example is the celebrated belief propagation algorithm. It was independently invented in each of these fields but for very different purposes. The realization of the commonality has benefited each of the areas. We investigate polarization and spatial coupling: two techniques that were originally invented in the context of channel coding (communications) thus resulting for the first time in efficient capacity-achieving codes for a wide range of channels. As we will discuss, both techniques play a fundamental role also in computer science and statistical physics and so these two techniques can be seen as further fundamental building blocks that unite all three areas. We demonstrate applications of these techniques, as well as the fundamental phenomena they provide. In more detail, this thesis consists of two parts. In the first part, we consider the technique of polarization and its resultant class of channel codes, called polar codes. Our main focus is the analysis and improvement of the behavior of polarization towards the most significant aspects of modern channel-coding theory: scaling laws, universality, and complexity (quantization). For each of these aspects, we derive fundamental laws that govern the behavior of polarization and polar codes. Even though we concentrate on applications in communications, the analysis that we provide is general and can be carried over to applications of polarization in computer science and statistical physics. As we will show, our investigations confirm some of the inherent strengths of polar codes such as their robustness with respect to quantization. But they also make clear in which aspects further improvement of polar codes is needed. For example, we will explain that the scaling behavior of polar codes is quite slow compared to the optimal one. Hence, further research is required in order to enhance the scaling behavior of polar codes towards optimality. In the second part of this thesis, we investigate spatial coupling. By now, there exists already a considerable literature on spatial coupling in the realm of information theory and communications. We therefore investigate mainly the impact of spatial coupling on the fields of statistical physics and computer science. We consider two well-known models. The first is the Curie-Weiss model that provides us with the simplest model for understanding the mechanism of spatial coupling in the perspective of statistical physics. Many fundamental features of spatial coupling can be simply explained here. In particular, we will show how the well-known Maxwell construction in statistical physics manifests itself through spatial coupling. We then focus on a much richer class of graphical models called constraint satisfaction problems (CSP) (e.g., K-SAT and Q-COL). These models are central to computer science. We follow a general framework: First, we introduce interpolation procedures for proving that the coupled and standard (un-coupled) models are fundamentally related, in that their static properties (such as their SAT/UNSAT threshold) are the same. We then use tools from spin glass theory (cavity method) to demonstrate the so-called phenomenon of threshold saturation in these coupled models. Finally, we present the algorithmic implications and argue that all these features provide a new avenue for obtaining better, provable, algorithmic lower bounds on static thresholds of the individual standard CSP models. We consider simple decimation algorithms (e.g., the unit clause propagation algorithm) for the coupled CSP models and provide a machinery to analyze these algorithms. These analyses enable us to observe that the algorithmic thresholds on the coupled model are significantly improved over the standard model. For some models (e.g., 3-SAT, 3-COL), these coupled algorithmic thresholds surpass the best lower bounds on the SAT/UNSAT threshold in the literature and provide us with a new lower bound. We conclude by pointing out that although we only considered some specific graphical models, our results are of general nature hence applicable to a broad set of models. In particular, a main contribution of this thesis is to firmly establish both polarization, as well as spatial coupling, in the common toolbox of information theory/communication, statistical physics, and computer science
A Very Brief Introduction to Machine Learning With Applications to Communication Systems
Given the unprecedented availability of data and computing resources, there
is widespread renewed interest in applying data-driven machine learning methods
to problems for which the development of conventional engineering solutions is
challenged by modelling or algorithmic deficiencies. This tutorial-style paper
starts by addressing the questions of why and when such techniques can be
useful. It then provides a high-level introduction to the basics of supervised
and unsupervised learning. For both supervised and unsupervised learning,
exemplifying applications to communication networks are discussed by
distinguishing tasks carried out at the edge and at the cloud segments of the
network at different layers of the protocol stack
Artificial Intelligence Aided Receiver Design for Wireless Communication Systems
Physical layer (PHY) design in the wireless communication field realizes gratifying achievements in the past few decades, especially in the emerging cellular communication systems starting from the first generation to the fifth generation (5G). With the gradual increase in technical requirements of large data processing and end-to-end system optimization, introducing artificial intelligence (AI) in PHY design has cautiously become a trend. A deep neural network (DNN), one of the population techniques of AI, enables the utilization of its ‘learnable’ feature to handle big data and establish a global system model. In this thesis, we exploited this characteristic of DNN as powerful assistance to implement two receiver designs in two different use-cases. We considered a DNN-based joint baseband demodulator and channel decoder (DeModCoder), and a DNN-based joint equalizer, baseband demodulator, and channel decoder (DeTecModCoder) in two single operational blocks, respectively. The multi-label classification (MLC) scheme was equipped to the output of conducted DNN model and hence yielded lower computational complexity than the multiple output classification (MOC) manner. The functional DNN model can be trained offline over a wide range of SNR values under different types of noises, channel fading, etc., and deployed in the real-time application; therefore, the demands of estimation of noise variance and statistical information of underlying noise can be avoided. The simulation performances indicated that compared to the corresponding conventional receiver signal processing schemes, the proposed AI-aided receiver designs have achieved the same bit error rate (BER) with around 3 dB lower SNR
On the Road to 6G: Visions, Requirements, Key Technologies and Testbeds
Fifth generation (5G) mobile communication systems have entered the stage of commercial development, providing users with new services and improved user experiences as well as offering a host of novel opportunities to various industries. However, 5G still faces many challenges. To address these challenges, international industrial, academic, and standards organizations have commenced research on sixth generation (6G) wireless communication systems. A series of white papers and survey papers have been published, which aim to define 6G in terms of requirements, application scenarios, key technologies, etc. Although ITU-R has been working on the 6G vision and it is expected to reach a consensus on what 6G will be by mid-2023, the related global discussions are still wide open and the existing literature has identified numerous open issues. This paper first provides a comprehensive portrayal of the 6G vision, technical requirements, and application scenarios, covering the current common understanding of 6G. Then, a critical appraisal of the 6G network architecture and key technologies is presented. Furthermore, existing testbeds and advanced 6G verification platforms are detailed for the first time. In addition, future research directions and open challenges are identified for stimulating the on-going global debate. Finally, lessons learned to date concerning 6G networks are discussed
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