310 research outputs found
Distributed Adaptive Networks: A Graphical Evolutionary Game-Theoretic View
Distributed adaptive filtering has been considered as an effective approach
for data processing and estimation over distributed networks. Most existing
distributed adaptive filtering algorithms focus on designing different
information diffusion rules, regardless of the nature evolutionary
characteristic of a distributed network. In this paper, we study the adaptive
network from the game theoretic perspective and formulate the distributed
adaptive filtering problem as a graphical evolutionary game. With the proposed
formulation, the nodes in the network are regarded as players and the local
combiner of estimation information from different neighbors is regarded as
different strategies selection. We show that this graphical evolutionary game
framework is very general and can unify the existing adaptive network
algorithms. Based on this framework, as examples, we further propose two
error-aware adaptive filtering algorithms. Moreover, we use graphical
evolutionary game theory to analyze the information diffusion process over the
adaptive networks and evolutionarily stable strategy of the system. Finally,
simulation results are shown to verify the effectiveness of our analysis and
proposed methods.Comment: Accepted by IEEE Transactions on Signal Processin
Index Modulation Techniques for Energy-efficient Transmission in Large-scale MIMO Systems
This thesis exploits index modulation techniques to design energy- and spectrum-efficient system models to operate in future wireless networks. In this respect, index modulation techniques are studied considering two different media: mapping the information onto the frequency indices of multicarrier systems, and onto the antenna array indices of a platform that comprises multiple antennas.
The index modulation techniques in wideband communication scenarios considering orthogonal and generalized frequency division multiplexing systems are studied first. Single cell multiuser networks are considered while developing the system models that exploit the index modulation on the subcarriers of the multicarrier systems. Instead of actively modulating all the subcarriers, a subset is selected according to the index modulation bits. As a result, there are subcarriers that remain idle during the data transmission phase and the activation pattern of the subcarriers convey additional information.
The transceivers for the orthogonal and generalized frequency division multiplexing systems with index modulation are both designed considering the uplink and downlink transmission phases with a linear combiner and precoder in order to reduce the system complexity. In the developed system models, channel state information is required only at the base station. The linear combiner is designed adopting minimum mean square error method to mitigate the inter-user-interference. The proposed system models offer a flexible design as the parameters are independent of each other. The parameters can be adjusted to design the system in favor of the energy efficiency, spectrum efficiency, peak-to-average power ratio, or error performance.
Then, the index modulation techniques are studied for large-scale multiple-input multiple-output systems that operate in millimeter wave bands. In order to overcome the drawbacks of transmission in millimeter wave frequencies, channel properties should be taken in to account while envisaging the wireless communication network. The large-scale multiple-input multiple-output systems increase the degrees of freedom in the spatial domain. This feature can be exploited to focus the transmit power directly onto the intended receiver terminal to cope with the severe path-loss. However, scaling up the number of hardware elements results in excessive power consumption. Hybrid architectures provide a remedy by shifting a part of the signal processing to the analog domain. In this way, the number of bulky and high power consuming hardware elements can be reduced. However, there will be a performance degradation as a consequence of renouncing the fully digital signal processing. Index modulation techniques can be combined with the hybrid system architecture to compensate the loss in spectrum efficiency to further increase the data rates.
A user terminal architecture is designed that employs analog beamforming together with spatial modulation where a part of the information bits is mapped onto the indices of the antenna arrays. The system is comprised a switching stage that allocates the user terminal antennas on the phase shifter groups to minimize the spatial correlation, and a phase shifting stage that maximizes the beamforming gain to combat the path-loss. A computationally efficient optimization algorithm is developed to configure the system. The flexibility of the architecture enables optimization of the hybrid transceiver at any signal-to-noise ratio values.
A base station is designed in which hybrid beamforming together with spatial modulation is employed. The analog beamformer is designed to point the transmit beam only in the direction of the intended user terminal to mitigate leakage of the transmit power to other directions. The analog beamformer to transmit the signal is chosen based on the spatial modulation bits. The digital precoder is designed to eliminate the inter-user-interference by exploiting the zero-forcing method. The base station computes the hybrid beamformers and the digital combiners, and only feeds back the digital combiners of each antenna array-user pair to the related user terminals. Thus, a low complexity user architecture is sufficient to achieve a higher performance. The developed optimization framework for the energy efficiency jointly optimizes the number of served users and the total transmit power by utilizing the derived upper bound of the achievable rate. The proposed transceiver architectures provide a more energy-efficient system model compared to the hybrid systems in which the spatial modulation technique is not exploited.
This thesis develops low-complexity system models that operate in narrowband and wideband channel environments to meet the energy and spectrum efficiency demands of future wireless networks. It is corroborated in the thesis that adopting index modulation techniques both in the systems improves the system performance in various aspects.:1 Introduction 1
1.1 Motivation 1
1.2 Overview and Contribution 2
1.3 Outline 9
2 Preliminaries and Fundamentals 13
2.1 Multicarrier Systems 13
2.2 Large-scale Multiple Input Multiple Output Systems 17
2.3 Index Modulation Techniques 19
2.4 Single Cell Multiuser Networks 22
3 Multicarrier Systems with Index Modulation 27
3.1 Orthogonal Frequency Division Multiplexing 28
3.2 Generalized Frequency Division Multiplexing 40
3.3 Summary 52
4 Hybrid Beamforming with Spatial Modulation 55
4.1 Uplink Transmission 56
4.2 Downlink Transmission 74
4.3 Summary 106
5 Conclusion and Outlook 109
5.1 Conclusion 109
5.2 Outlook 111
A Quantization Error Derivations 113
B On the Achievable Rate of Gaussian Mixtures 115
B.1 The Conditional Density Function 115
B.2 Tight Bounds on the Differential Entropy 116
B.3 A Bound on the Achievable Rate 118
C Multiuser MIMO Downlink without Spatial Modulation 121
Bibliograph
Vidutinių dažnių 5G belaidžių tinklų galios stiprintuvų tyrimas
This dissertation addresses the problems of ensuring efficient radio fre-quency transmission for 5G wireless networks. Taking into account, that the next
generation 5G wireless network structure will be heterogeneous, the device
density and their mobility will increase and massive MIMO connectivity
capability will be widespread, the main investigated problem is formulated –
increasing the efficiency of portable mid-band 5G wireless network CMOS power amplifier with impedance matching networks.
The dissertation consists of four parts including the introduction, 3 chapters, conclusions, references and 3 annexes.
The investigated problem, importance and purpose of the thesis, the ob-ject of the research methodology, as well as the scientific novelty are de-fined in the
introduction. Practical significance of the obtained results, defended state-ments and the structure of the dissertation are also included.
The first chapter presents an extensive literature analysis. Latest ad-vances in the structure of the modern wireless network and the importance of the power amplifier in the radio frequency transmission chain are de-scribed in detail. The latter is followed by different power amplifier archi-tectures, parameters and their improvement techniques. Reported imped-ance matching network design methods are also discussed. Chapter 1 is concluded distinguishing the possible research vectors and defining the problems raised in this dissertation.
The second chapter is focused around improving the accuracy of de-signing lumped impedance matching network. The proposed methodology of estimating lumped inductor and capacitor parasitic parameters is dis-cussed in detail provi-ding complete mathematical expressions, including a summary and conclusions.
The third chapter presents simulation results for the designed radio fre-quency power amplifiers. Two variations of Doherty power amplifier archi-tectures are presented in the second part, covering the full step-by-step de-sign and simulation process. The latter chapter is concluded by comparing simulation and
measurement results for all designed radio frequency power amplifiers.
General conclusions are followed by an extensive list of references and a list of 5 publications by the author on the topic of the dissertation.
5 papers, focusing on the subject of the discussed dissertation, have been
published: three papers are included in the Clarivate Analytics Web of Sci-ence database with a citation index, one paper is included in Clarivate Ana-lytics Web of Science database Conference Proceedings, and one paper has been published in unreferred international conference preceedings. The au-thor has also made
9 presentations at 9 scientific conferences at a national and international level.Dissertatio
State-of-the-art assessment of 5G mmWave communications
Deliverable D2.1 del proyecto 5GWirelessMain objective of the European 5Gwireless project, which is part of the H2020 Marie Slodowska-
Curie ITN (Innovative Training Networks) program resides in the training and involvement of young
researchers in the elaboration of future mobile communication networks, focusing on innovative
wireless technologies, heterogeneous network architectures, new topologies (including ultra-dense
deployments), and appropriate tools. The present Document D2.1 is the first deliverable of Work-
Package 2 (WP2) that is specifically devoted to the modeling of the millimeter-wave (mmWave)
propagation channels, and development of appropriate mmWave beamforming and signal
processing techniques. Deliver D2.1 gives a state-of-the-art on the mmWave channel measurement,
characterization and modeling; existing antenna array technologies, channel estimation and
precoding algorithms; proposed deployment and networking techniques; some performance
studies; as well as a review on the evaluation and analysis toolsPostprint (published version
Aeronautical engineering: A continuing bibliography with indexes (supplement 272)
This bibliography lists 719 reports, articles, and other documents introduced into the NASA scientific and technical information system in November, 1991. Subject coverage includes: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment, and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics
WEC: weighted ensemble of text classifiers.
Text classification is one of the most important tasks in the field of Natural Language Processing. There are many approaches that focus on two main aspects: generating an effective representation; and selecting and refining algorithms to build the classification model. Traditional machine learning methods represent documents in vector space using features such as term frequencies, which have limitations in handling the order and semantics of words. Meanwhile, although achieving many successes, deep learning classifiers require substantial resources in terms of labelled data and computational complexity. In this work, a weighted ensemble of classifiers (WEC) is introduced to address the text classification problem. Instead of using majority vote as the combining method, we propose to associate each classifier’s prediction with a different weight when combining classifiers. The optimal weights are obtained by minimising a loss function on the training data with the Particle Swarm Optimisation algorithm. We conducted experiments on 5 popular datasets and report classification performance of algorithms with classification accuracy and macro F1 score. WEC was run with several different combinations of traditional machine learning and deep learning classifiers to show its flexibility and robustness. Experimental results confirm the advantage of WEC, especially on smaller datasets
Analysis of low-density parity-check codes on impulsive noise channels
PhD ThesisCommunication channels can severely degrade a signal, not only due to
fading effects but also interference in the form of impulsive noise. In
conventional communication systems, the additive noise at the receiver
is usually assumed to be Gaussian distributed. However, this assumption
is not always valid and examples of non-Gaussian distributed noise
include power line channels, underwater acoustic channels and manmade
interference. When designing a communication system it is useful
to know the theoretical performance in terms of bit-error probability
(BEP) on these types of channels. However, the effect of impulses on
the BEP performance has not been well studied, particularly when error correcting
codes are employed. Today, advanced error-correcting codes
with very long block lengths and iterative decoding algorithms, such as
Low-Density Parity-Check (LDPC) codes and turbo codes, are popular
due to their capacity-approaching performance. However, very long
codes are not always desirable, particularly in communications systems
where latency is a serious issue, such as in voice and video communication
between multiple users. This thesis focuses on the analysis of short
LDPC codes. Finite length analyses of LDPC codes have already been
presented for the additive white Gaussian noise channel in the literature,
but the analysis of short LDPC codes for channels that exhibit impulsive
noise has not been investigated.
The novel contributions in this thesis are presented in three sections.
First, uncoded and LDPC-coded BEP performance on channels exhibiting
impulsive noise modelled by symmetric -stable (S S) distributions
are examined. Different sub-optimal receivers are compared and a new
low-complexity receiver is proposed that achieves near-optimal performance.
Density evolution is then used to derive the threshold signal-tonoise
ratio (SNR) of LDPC codes that employ these receivers. In order
to accurately predict the waterfall performance of short LDPC codes, a
nite length analysis is proposed with the aid of the threshold SNRs of
LDPC codes and the derived uncoded BEPs for impulsive noise channels.
Second, to investigate the e ect of impulsive noise on wireless channels,
the analytic BEP on generalized fading channels with S S noise is derived.
However, it requires the evaluation of a double integral to obtain
the analytic BEP, so to reduce the computational cost, the Cauchy-
Gaussian mixture model and the asymptotic property of S S process
are used to derive upper bounds of the exact BEP. Two closed-form expressions
are derived to approximate the exact BEP on a Rayleigh fading
channel with S S noise. Then density evolution of different receivers is
derived for these channels to nd the asymptotic performance of LDPC
codes. Finally, the waterfall performance of LDPC codes is again estimated
for generalized fading channels with S S noise by utilizing the
derived uncoded BEP and threshold SNRs.
Finally, the addition of spatial diversity at the receiver is investigated.
Spatial diversity is an effective method to mitigate the effects of fading
and when used in conjunction with LDPC codes and can achieve
excellent error-correcting performance. Hence, the performance of conventional
linear diversity combining techniques are derived. Then the
SNRs of these linear combiners are compared and the relationship of
the noise power between different linear combiners is obtained. Nonlinear
detectors have been shown to achieve better performance than
linear combiners hence, optimal and sub-optimal detectors are also presented
and compared. A non-linear detector based on the bi-parameter
Cauchy-Gaussian mixture model is used and shows near-optimal performance
with a significant reduction in complexity when compared with
the optimal detector. Furthermore, we show how to apply density evolution
of LDPC codes for different combining techniques on these channels
and an estimation of the waterfall performance of LDPC codes is derived
that reduces the gap between simulated and asymptotic performance.
In conclusion, the work presented in this thesis provides a framework
to evaluate the performance of communication systems in the presence
of additive impulsive noise, with and without spatial diversity at the
receiver. For the first time, bounds on the BEP performance of LDPC
codes on channels with impulsive noise have been derived for optimal
and sub-optimal receivers, allowing other researchers to predict the performance
of LDPC codes in these type of environments without needing
to run lengthy computer simulations
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