45 research outputs found
Beamforming for powerline interference in large sensor arrays
This paper shows how to use beamforming to remove the power-line interference (PLI) in large surface electromyography (sEMG) sensor array or high-density sEMG. The method exploits the highly correlated nature of the different sources of interference, being part of the same electrical grid, and their narrow frequency bands. The idea is to use a very narrow pass-band filter around 50 or 60 Hz to get signals with high PLI content before applying a spatial filtering by principal component analysis (PCA). This way, beamforming are done on the frequency bands where PLI are presents. Also, it ensures that even if the PLI has a smaller overall power than the desired signal, it will be easily found as the most powerful component of the decomposition. The PLI can then be removed from the signal. With trivial modification, harmonics of the PLI can also be removed. The approach was used in the context of muscle behavior analyses of low back pain patients using a sEMG array of 64 sensors. The performances of the filter are studied by experimental and semi-empirical methods. Compared to the usual notch filter, an improvement of up 10 dB is found
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Space-time-frequency methods for interference-limited communication systems
textTraditionally, noise in communication systems has been modeled as an additive, white Gaussian noise process with independent, identically distributed samples. Although this model accurately reflects thermal noise present in communication system electronics, it fails to capture the statistics of interference and other sources of noise, e.g. in unlicensed communication bands. Modern communication system designers must take into account interference and non-Gaussian noise to maximize efficiencies and capacities of current and future communication networks. In this work, I develop new multi-dimensional signal processing methods to improve performance of communication systems in three applications areas: (i) underwater acoustic, (ii) powerline, and (iii) multi-antenna cellular. In underwater acoustic communications, I address impairments caused by strong, time-varying and Doppler-spread reverberations (self-interference) using adaptive space-time signal processing methods. I apply these methods to array receivers with a large number of elements. In powerline communications, I address impairments caused by non-Gaussian noise arising from devices sharing the powerline. I develop and apply a cyclic adaptive modulation and coding scheme and a factor-graph-based impulsive noise mitigation method to improve signal quality and boost link throughput and robustness. In cellular communications, I develop a low-latency, high-throughput space-time-frequency processing framework used for large scale (up to 128 antenna) MIMO. This framework is used in the world's first 100-antenna MIMO system and processes up to 492 Gbps raw baseband samples in the uplink and downlink directions. My methods prove that multi-dimensional processing methods can be applied to increase communication system performance without sacrificing real-time requirements.Electrical and Computer Engineerin
Internet of Things for Sustainable Community Development: Introduction and Overview
The two-third of the city-dwelling world population by 2050 poses numerous global challenges in the infrastructure and natural resource management domains (e.g., water and food scarcity, increasing global temperatures, and energy issues). The IoT with integrated sensing and communication capabilities has the strong potential for the robust, sustainable, and informed resource management in the urban and rural communities. In this chapter, the vital concepts of sustainable community development are discussed. The IoT and sustainability interactions are explained with emphasis on Sustainable Development Goals (SDGs) and communication technologies. Moreover, IoT opportunities and challenges are discussed in the context of sustainable community development
A Tutorial on Clique Problems in Communications and Signal Processing
Since its first use by Euler on the problem of the seven bridges of
K\"onigsberg, graph theory has shown excellent abilities in solving and
unveiling the properties of multiple discrete optimization problems. The study
of the structure of some integer programs reveals equivalence with graph theory
problems making a large body of the literature readily available for solving
and characterizing the complexity of these problems. This tutorial presents a
framework for utilizing a particular graph theory problem, known as the clique
problem, for solving communications and signal processing problems. In
particular, the paper aims to illustrate the structural properties of integer
programs that can be formulated as clique problems through multiple examples in
communications and signal processing. To that end, the first part of the
tutorial provides various optimal and heuristic solutions for the maximum
clique, maximum weight clique, and -clique problems. The tutorial, further,
illustrates the use of the clique formulation through numerous contemporary
examples in communications and signal processing, mainly in maximum access for
non-orthogonal multiple access networks, throughput maximization using index
and instantly decodable network coding, collision-free radio frequency
identification networks, and resource allocation in cloud-radio access
networks. Finally, the tutorial sheds light on the recent advances of such
applications, and provides technical insights on ways of dealing with mixed
discrete-continuous optimization problems
Symbol-level and Multicast Precoding for Multiuser Multiantenna Downlink: A State-of-the-art, Classification and Challenges
Precoding has been conventionally considered as an effective means of mitigating or exploiting the interference in the multiantenna downlink channel, where multiple users are simultaneously served with independent information over the same channel resources. The early works in this area were focused on transmitting an individual information stream to each user by constructing weighted linear combinations of symbol blocks (codewords). However, more recent works have moved beyond this traditional view by: i) transmitting distinct data streams to groups of users and ii) applying precoding on a symbol-per-symbol basis. In this context, the current survey presents a unified view and classification of precoding techniques with respect to two main axes: i) the switching rate of the precoding weights, leading to the classes of block-level and symbol-level precoding, ii) the number of users that each stream is addressed to, hence unicast, multicast, and broadcast precoding. Furthermore, the classified techniques are compared through representative numerical results to demonstrate their relative performance and uncover fundamental insights. Finally, a list of open theoretical problems and practical challenges are presented to inspire further research in this area
CMOS Hyperbolic Sine ELIN filters for low/audio frequency biomedical applications
Hyperbolic-Sine (Sinh) filters form a subclass of Externally-Linear-Internally-Non-
Linear (ELIN) systems. They can handle large-signals in a low power environment under half
the capacitor area required by the more popular ELIN Log-domain filters. Their inherent
class-AB nature stems from the odd property of the sinh function at the heart of their
companding operation. Despite this early realisation, the Sinh filtering paradigm has not
attracted the interest it deserves to date probably due to its mathematical and circuit-level
complexity.
This Thesis presents an overview of the CMOS weak inversion Sinh filtering
paradigm and explains how biomedical systems of low- to audio-frequency range could
benefit from it. Its dual scope is to: consolidate the theory behind the synthesis and design of
high order Sinh continuous–time filters and more importantly to confirm their micro-power
consumption and 100+ dB of DR through measured results presented for the first time.
Novel high order Sinh topologies are designed by means of a systematic
mathematical framework introduced. They employ a recently proposed CMOS Sinh
integrator comprising only p-type devices in its translinear loops. The performance of the
high order topologies is evaluated both solely and in comparison with their Log domain
counterparts. A 5th order Sinh Chebyshev low pass filter is compared head-to-head with a
corresponding and also novel Log domain class-AB topology, confirming that Sinh filters
constitute a solution of equally high DR (100+ dB) with half the capacitor area at the expense
of higher complexity and power consumption. The theoretical findings are validated by
means of measured results from an 8th order notch filter for 50/60Hz noise fabricated in a
0.35μm CMOS technology. Measured results confirm a DR of 102dB, a moderate SNR of
~60dB and 74μW power consumption from 2V power supply
Physical layer network coding based communication systems in frequency selective channels
PhD ThesisThe demand for wireless communications is growing every day which requiresmore
speed and bandwidth. In two way relay networks (TWRN), physical
layer network coding (PLNC) was proposed to double the bandwidth. A
TWRN is a system where two end users exchange data through a middle node
called the relay. The two signals are allowed to be physically added before being
broadcasted back to the end users. This system can work smoothly in flat
fading channels, but can not be applied straightforward in frequency selective
channels. In a multipath multi-tap FIR channel, the inter-symbol interference
(ISI) spreads through several symbols. In this case, the symbols at the relay
are not just an addition of the sent symbols but also some of the previous
symbols from both sides. This not only causes a traditional PLNC to fail but
also a simple one equalizer system will not solve the problem. Three main
methods have been proposed by other researchers. The OFDM based PLNC
is the simplest in terms of implementation and complexity but suffers from
the disadvantages of the OFDMlike cyclic prefix overhead and frequency offset.
The main disadvantage, however is the relatively low BER performance
because it is restricted to linear equalizers in the PLNC system. Another
approach is pre-filtering or pre-equalization. This method also has some disadvantages
like complexity, sensitivity to channel variation and the need of
a feedback channel for both end nodes. Finally, the maximum likelihood
sequence detector was also proposed but is restricted to BPSK modulation
and exponentially rising complexity are major drawbacks. The philosophy in
this work is to avoid these disadvantages by using a time domain based system.
The DFE is the equalizer of choice here because it provides a non-trivial
BER performance improvement with very little increase in complexity. In
this thesis, the problem of frequency selective channels in PLNC systems can
be solved by properly adjusting the design of the system including the DFE.
The other option is to redesign the equalizer to meet that goal. An AF DFE
system is proposed in this work that provides very low complexity especially
at the relay with little sensitivity to channel changes. A multi-antenna DNF
DFE system is also proposed here with an improved performance. Finally, a
new equalizer is designed for very low complexity and cost DNF approach
with little sacrifice of BER performance. Matlab was used for the simulations
with Monte Carlo method to verify the findings of this work through finding
the BER performance of each system. This thesis opens the door for future
improvement on the PLNC system. More research needs to be done like testing
the proposed systems in real practical implementation and also the effect
of adding channel coding to these systems.Iraqi Government, Ministry of
Higher Educatio