246 research outputs found
Turbo receivers for interleave-division multiple-access systems
In this paper several turbo receivers for Interleave-Division Multiple-Access (IDMA) systems will be discussed. The multiple access system model is presented first. The optimal, Maximum A Posteriori (MAP) algorithm, is then presented. It will be shown that the use of a precoding technique at the emitter side is applicable to IDMA systems. Several low complexity Multi-User Detector (MUD), based on the Gaussian approximation, will be next discussed. It will be shown that the MUD with Probabilistic Data Association (PDA) algorithm provides faster convergence of the turbo receiver. The discussed turbo receivers will be evaluated by means of Bit Error Rate (BER) simulations and EXtrinsic Information Transfer (EXIT) charts
Hitchin-Kobayashi correspondence, quivers, and vortices
A twisted quiver bundle is a set of holomorphic vector bundles over a complex
manifold, labelled by the vertices of a quiver, linked by a set of morphisms
twisted by a fixed collection of holomorphic vector bundles, labelled by the
arrows. When the manifold is Kaelher, quiver bundles admit natural
gauge-theoretic equations, which unify many known equations for bundles with
extra structure. In this paper we prove a Hitchin--Kobayashi correspondence for
twisted quiver bundles over a compact Kaehler manifold, relating the existence
of solutions to the gauge equations to a stability criterion, and consider its
application to a number of situations related to Higgs bundles and dimensional
reductions of the Hermitian--Einstein equations.Comment: 28 pages; larger introduction, added references for the introduction,
added a short comment in Section 1, typos corrected, accepted in Comm. Math.
Phy
Joint Communication and Positioning based on Channel Estimation
Mobile wireless communication systems have rapidly and globally become an integral part of everyday life and have brought forth the internet of things. With the evolution of mobile wireless communication systems, joint communication and positioning becomes increasingly important and enables a growing range of new applications. Humanity has already grown used to having access to multimedia data everywhere at every time and thereby employing all sorts of location-based services. Global navigation satellite systems can provide highly accurate positioning results whenever a line-of-sight path is available. Unfortunately, harsh physical environments are known to degrade the performance of existing systems. Therefore, ground-based systems can assist the existing position estimation gained by satellite systems. Determining positioning-relevant information from a unified signal structure designed for a ground-based joint communication and positioning system can either complement existing systems or substitute them. Such a system framework promises to enhance the existing systems by enabling a highly accurate and reliable positioning performance and increased coverage. Furthermore, the unified signal structure yields synergetic effects. In this thesis, I propose a channel estimation-based joint communication and positioning system that employs a virtual training matrix. This matrix consists of a relatively small training percentage, plus the detected communication data itself. Via a core semi- blind estimation approach, this iteratively includes the already detected data to accurately determine the positioning-relevant parameter, by mutually exchanging information between the communication part and the positioning part of the receiver. Synergy is created. I propose a generalized system framework, suitable to be used in conjunction with various communication system techniques. The most critical positioning-relevant parameter, the time-of-arrival, is part of a physical multipath parameter vector. Estimating the time-of-arrival, therefore, means solving a global, non-linear, multi-dimensional optimization problem. More precisely, it means solving the so-called inverse problem. I thoroughly assess various problem formulations and variations thereof, including several different measurements and estimation algorithms. A significant challenge, when it comes to solving the inverse problem to determine the positioning-relevant path parameters, is imposed by realistic multipath channels. Most parameter estimation algorithms have proven to perform well in moderate multipath environments. It is mathematically straightforward to optimize this performance in the sense that the number of observations has to exceed the number of parameters to be estimated. The typical parameter estimation problem, on the other hand, is based on channel estimates, and it assumes that so-called snapshot measurements are available. In the case of realistic channel models, however, the number of observations does not necessarily exceed the number of unknowns. In this thesis, I overcome this problem, proposing a method to reduce the problem dimensionality via joint model order selection and parameter estimation. Employing the approximated and estimated parameter covariance matrix inherently constrains the estimation problem’s model order selection to result in optimal parameter estimation performance and hence optimal positioning performance. To compare these results with the optimally achievable solution, I introduce a focused order-related lower bound in this thesis. Additionally, I use soft information as a weighting matrix to enhance the positioning algorithm positioning performance. For demonstrating the feasibility and the interplay of the proposed system components, I utilize a prototype system, based on multi-layer interleave division multiple access. This proposed system framework and the investigated techniques can be employed for multiple existing systems or build the basis for future joint communication and positioning systems. The assessed estimation algorithms are transferrable to all kinds of joint communication and positioning system designs. This thesis demonstrates their capability to, in principle, successfully cope with challenging estimation problems stemming from harsh physical environments
Multiple Access Techniques for Next Generation Wireless: Recent Advances and Future Perspectives
The advances in multiple access techniques has been one of the key drivers in moving from one cellular generation to another. Starting from the first generation, several multiple access techniques have been explored in different generations and various emerging multiplexing/multiple access techniques are being investigated for the next generation of cellular networks. In this context, this paper first provides a detailed review on the existing Space Division Multiple Access (SDMA) related works. Subsequently, it highlights the main features and the drawbacks of various existing and emerging multiplexing/multiple access techniques. Finally, we propose a novel concept of clustered orthogonal signature division multiple access for the next generation of cellular networks. The proposed concept envisions to employ joint antenna coding in order to enhance the orthogonality of SDMA beams with the objective of enhancing the spectral efficiency of future cellular networks
Capacity-Achieving MIMO-NOMA: Iterative LMMSE Detection
This paper considers a low-complexity iterative Linear Minimum Mean Square
Error (LMMSE) multi-user detector for the Multiple-Input and Multiple-Output
system with Non-Orthogonal Multiple Access (MIMO-NOMA), where multiple
single-antenna users simultaneously communicate with a multiple-antenna base
station (BS). While LMMSE being a linear detector has a low complexity, it has
suboptimal performance in multi-user detection scenario due to the mismatch
between LMMSE detection and multi-user decoding. Therefore, in this paper, we
provide the matching conditions between the detector and decoders for
MIMO-NOMA, which are then used to derive the achievable rate of the iterative
detection. We prove that a matched iterative LMMSE detector can achieve (i) the
optimal capacity of symmetric MIMO-NOMA with any number of users, (ii) the
optimal sum capacity of asymmetric MIMO-NOMA with any number of users, (iii)
all the maximal extreme points in the capacity region of asymmetric MIMO-NOMA
with any number of users, (iv) all points in the capacity region of two-user
and three-user asymmetric MIMO-NOMA systems. In addition, a kind of practical
low-complexity error-correcting multiuser code, called irregular
repeat-accumulate code, is designed to match the LMMSE detector. Numerical
results shows that the bit error rate performance of the proposed iterative
LMMSE detection outperforms the state-of-art methods and is within 0.8dB from
the associated capacity limit.Comment: Accepted by IEEE TSP, 16 pages, 9 figures. This is the first work
that proves the low-complexity iterative receiver (Parallel Interference
Cancellation) can achieve the capacity of multi-user MIMO systems. arXiv
admin note: text overlap with arXiv:1604.0831
A High-performance, Energy-efficient Modular DMA Engine Architecture
Data transfers are essential in today's computing systems as latency and
complex memory access patterns are increasingly challenging to manage. Direct
memory access engines (DMAEs) are critically needed to transfer data
independently of the processing elements, hiding latency and achieving high
throughput even for complex access patterns to high-latency memory. With the
prevalence of heterogeneous systems, DMAEs must operate efficiently in
increasingly diverse environments. This work proposes a modular and highly
configurable open-source DMAE architecture called intelligent DMA (iDMA), split
into three parts that can be composed and customized independently. The
front-end implements the control plane binding to the surrounding system. The
mid-end accelerates complex data transfer patterns such as multi-dimensional
transfers, scattering, or gathering. The back-end interfaces with the on-chip
communication fabric (data plane). We assess the efficiency of iDMA in various
instantiations: In high-performance systems, we achieve speedups of up to 15.8x
with only 1 % additional area compared to a base system without a DMAE. We
achieve an area reduction of 10 % while improving ML inference performance by
23 % in ultra-low-energy edge AI systems over an existing DMAE solution. We
provide area, timing, latency, and performance characterization to guide its
instantiation in various systems.Comment: 14 pages, 14 figures, accepted by an IEEE journal for publicatio
Rate compatible modulation for non-orthogonal multiple access
We propose a new Non-Orthogonal Multiple Access (NOMA) coding scheme based on the
use of a Rate Compatible Modulation (RCM) encoder for each user. By properly designing the encoders
and taking advantage of the additive nature of the Multiple Access Channel (MAC), the joint decoder from
the inputs of all the users can be represented by a bipartite graph corresponding to a standard point-topoint RCM structure with certain constraints. Decoding is performed over this bipartite graph utilizing the
sum-product algorithm. The proposed scheme allows the simultaneous transmission of a large number of
uncorrelated users at high rates, while the decoding complexity is the same as that of standard point-to-point
RCM schemes. When Rayleigh fast fading channels are considered, the BER vs SNR performance improves
as the number of simultaneous users increases, as a result of the averaging effect
Malware detection techniques for mobile devices
Mobile devices have become very popular nowadays, due to its portability and
high performance, a mobile device became a must device for persons using
information and communication technologies. In addition to hardware rapid
evolution, mobile applications are also increasing in their complexity and
performance to cover most needs of their users. Both software and hardware
design focused on increasing performance and the working hours of a mobile
device. Different mobile operating systems are being used today with different
platforms and different market shares. Like all information systems, mobile
systems are prone to malware attacks. Due to the personality feature of mobile
devices, malware detection is very important and is a must tool in each device
to protect private data and mitigate attacks. In this paper, analysis of
different malware detection techniques used for mobile operating systems is
provides. The focus of the analysis will be on the to two competing mobile
operating systems - Android and iOS. Finally, an assessment of each technique
and a summary of its advantages and disadvantages is provided. The aim of the
work is to establish a basis for developing a mobile malware detection tool
based on user profiling.Comment: 11 pages, 6 figure
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