82 research outputs found
Direction of arrival estimation using robust complex Lasso
The Lasso (Least Absolute Shrinkage and Selection Operator) has been a
popular technique for simultaneous linear regression estimation and variable
selection. In this paper, we propose a new novel approach for robust Lasso that
follows the spirit of M-estimation. We define -Lasso estimates of regression
and scale as solutions to generalized zero subgradient equations. Another
unique feature of this paper is that we consider complex-valued measurements
and regression parameters, which requires careful mathematical characterization
of the problem. An explicit and efficient algorithm for computing the -Lasso
solution is proposed that has comparable computational complexity as
state-of-the-art algorithm for computing the Lasso solution. Usefulness of the
-Lasso method is illustrated for direction-of-arrival (DoA) estimation with
sensor arrays in a single snapshot case.Comment: Paper has appeared in the Proceedings of the 10th European Conference
on Antennas and Propagation (EuCAP'2016), Davos, Switzerland, April 10-15,
201
Multichannel sparse recovery of complex-valued signals using Huber's criterion
In this paper, we generalize Huber's criterion to multichannel sparse
recovery problem of complex-valued measurements where the objective is to find
good recovery of jointly sparse unknown signal vectors from the given multiple
measurement vectors which are different linear combinations of the same known
elementary vectors. This requires careful characterization of robust
complex-valued loss functions as well as Huber's criterion function for the
multivariate sparse regression problem. We devise a greedy algorithm based on
simultaneous normalized iterative hard thresholding (SNIHT) algorithm. Unlike
the conventional SNIHT method, our algorithm, referred to as HUB-SNIHT, is
robust under heavy-tailed non-Gaussian noise conditions, yet has a negligible
performance loss compared to SNIHT under Gaussian noise. Usefulness of the
method is illustrated in source localization application with sensor arrays.Comment: To appear in CoSeRa'15 (Pisa, Italy, June 16-19, 2015). arXiv admin
note: text overlap with arXiv:1502.0244
ΠΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΠ°Π»ΡΠ½ΠΎΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ ΡΠΈΡΡΠ΅ΠΌΡ ΠΏΠ΅ΡΠ΅Π΄Π°ΡΠΈ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ FBMC/OQAM
Introduction. This paper investigates a transmission system based on FBMC/OQAM multiplexing. This system is characterized by a high spectral efficiency, thereby attracting interest as an alternative transmission method in future wireless mobile communication standards. However, a disadvantage of the system is the high complexity of signal processing. There are numerous publications that study the FBMC/OQAM system from a theoretical perspective. This paper presents an experimental study of a transmission system based on FBMC/OQAM.Aim. Verification of a transmission system based on FBMC/OQAM multiplexing in a wireless channel.Materials and methods. Computer simulation modeling in Matlab and experimental research using Keysight and Rohde & Schwarz certified measuring instruments.Results. A model of synthesis and signal processing was developed, and a frame structure was proposed. The processing included synchronization, since the study was carried out in a wireless double-dispersive channel. Time synchronization was provided by the method of time-domain correlation. A preamble consisting of two symbols was used for CFO compensation. Channel estimation in FBMC/OQAM was conducted by pilot symbols spread over the time-frequency domain, a method with an auxiliary pilot to compensate for intrinsic interference, as well as Zero Forcing and a linear interpolator. As a result, dependences of the bit error rate on the Eb/N0 in various channels were obtained. An error rate of 10β4 was achieved under the Eb/N0 equal to 13.4 dB, 15.3 dB and 20.9 dB in the first, second and third channel, respectively.Conclusion. A FBMC/OQAM-based transmission system with a linear equalizer can operate without a cyclic prefix in a multipath wireless channel, providing comparable noise immunity to OFDM-CP. Long frames should be used to obtain greater spectral efficiency, due to the presence of a transition zone at the beginning and end of the FBMC/OQAM frame.ΠΠ²Π΅Π΄Π΅Π½ΠΈΠ΅. ΠΠ°Π½Π½Π°Ρ ΡΠ°Π±ΠΎΡΠ° ΠΏΠΎΡΠ²ΡΡΠ΅Π½Π° ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΡΠΈΡΡΠ΅ΠΌΡ ΠΏΠ΅ΡΠ΅Π΄Π°ΡΠΈ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΠΌΡΠ»ΡΡΠΈΠΏΠ»Π΅ΠΊΡΠΈΡΠΎΠ²Π°Π½ΠΈΡ FBMC/OQAM. ΠΠΊΡΡΠ°Π»ΡΠ½ΠΎΡΡΡ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΡΠ²ΡΠ·Π°Π½Π° Ρ Π²ΡΡΠΎΠΊΠΎΠΉ ΡΠΏΠ΅ΠΊΡΡΠ°Π»ΡΠ½ΠΎΠΉ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΡΡ Π΄Π°Π½Π½ΠΎΠΉ ΡΠΈΡΡΠ΅ΠΌΡ, Π±Π»Π°Π³ΠΎΠ΄Π°ΡΡ ΠΊΠΎΡΠΎΡΠΎΠΉ ΠΎΠ½Π° ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅ΡΡΡ ΠΊΠ°ΠΊ Π°Π»ΡΡΠ΅ΡΠ½Π°ΡΠΈΠ²Π½ΡΠΉ ΠΌΠ΅ΡΠΎΠ΄ ΠΏΠ΅ΡΠ΅Π΄Π°ΡΠΈ Π² Π±ΡΠ΄ΡΡΠΈΡ
ΡΡΠ°Π½Π΄Π°ΡΡΠ°Ρ
Π±Π΅ΡΠΏΡΠΎΠ²ΠΎΠ΄Π½ΠΎΠΉ ΠΌΠΎΠ±ΠΈΠ»ΡΠ½ΠΎΠΉ ΡΠ²ΡΠ·ΠΈ. ΠΠ΄Π½Π°ΠΊΠΎ Π½Π΅Π΄ΠΎΡΡΠ°ΡΠΊΠΎΠΌ ΡΠΈΡΡΠ΅ΠΌΡ ΡΠ²Π»ΡΠ΅ΡΡΡ Π²ΡΡΠΎΠΊΠ°Ρ ΡΠ»ΠΎΠΆΠ½ΠΎΡΡΡ ΠΎΠ±ΡΠ°Π±ΠΎΡΠΊΠΈ ΡΠΈΠ³Π½Π°Π»ΠΎΠ². Π‘ΡΠ΅Π΄ΠΈ ΠΎΡΠ΅ΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΡ
ΠΈ Π·Π°ΡΡΠ±Π΅ΠΆΠ½ΡΡ
ΠΏΡΠ±Π»ΠΈΠΊΠ°ΡΠΈΠΉ Π²ΡΡΡΠ΅ΡΠ°Π΅ΡΡΡ ΠΌΠ½ΠΎΠΆΠ΅ΡΡΠ²ΠΎ ΡΠ°Π±ΠΎΡ Ρ ΡΠ΅ΠΎΡΠ΅ΡΠΈΡΠ΅ΡΠΊΠΈΠΌ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ ΡΠΈΡΡΠ΅ΠΌΡ FBMC/OQAM. Π Π΄Π°Π½Π½ΠΎΠΉ ΡΡΠ°ΡΡΠ΅ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Ρ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ ΡΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΠ°Π»ΡΠ½ΠΎΠ³ΠΎ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΡΠΈΡΡΠ΅ΠΌΡ ΠΏΠ΅ΡΠ΅Π΄Π°ΡΠΈ Π½Π° Π΅Π΅ ΠΎΡΠ½ΠΎΠ²Π΅.Π¦Π΅Π»Ρ ΡΠ°Π±ΠΎΡΡ. ΠΠ΅ΡΠΈΡΠΈΠΊΠ°ΡΠΈΡ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΡΠΈΡΡΠ΅ΠΌΡ ΠΏΠ΅ΡΠ΅Π΄Π°ΡΠΈ Π΄Π°Π½Π½ΡΡ
Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ FBMC/OQAM Π² Π±Π΅ΡΠΏΡΠΎΠ²ΠΎΠ΄Π½ΠΎΠΌ ΠΊΠ°Π½Π°Π»Π΅ ΡΠ²ΡΠ·ΠΈ.ΠΠ°ΡΠ΅ΡΠΈΠ°Π»Ρ ΠΈ ΠΌΠ΅ΡΠΎΠ΄Ρ. Π ΡΠ°Π±ΠΎΡΠ΅ ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΠ΅ΡΡΡ ΠΌΠ΅ΡΠΎΠ΄ ΠΈΠΌΠΈΡΠ°ΡΠΈΠΎΠ½Π½ΠΎΠ³ΠΎ ΠΊΠΎΠΌΠΏΡΡΡΠ΅ΡΠ½ΠΎΠ³ΠΎ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ Π² ΡΡΠ΅Π΄Π΅ Matlab ΠΈ ΡΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΠ°Π»ΡΠ½ΠΎΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ ΡΠ΅ΡΡΠΈΡΠΈΡΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠ³ΠΎ ΠΈΠ·ΠΌΠ΅ΡΠΈΡΠ΅Π»ΡΠ½ΠΎΠ³ΠΎ ΠΎΠ±ΠΎΡΡΠ΄ΠΎΠ²Π°Π½ΠΈΡ Keysight ΠΈ Rohde & Schwarz.Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ. ΠΡΠ»Π° ΡΠ°Π·ΡΠ°Π±ΠΎΡΠ°Π½Π° ΠΌΠΎΠ΄Π΅Π»Ρ ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΈ ΠΎΠ±ΡΠ°Π±ΠΎΡΠΊΠΈ ΡΠΈΠ³Π½Π°Π»Π°, Π° ΡΠ°ΠΊΠΆΠ΅ ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½Π° ΡΡΡΡΠΊΡΡΡΠ°Β ΠΊΠ°Π΄ΡΠ°.Β ΠΠΎΠΊΠ°Π΄ΡΠΎΠ²Π°ΡΒ ΠΎΠ±ΡΠ°Π±ΠΎΡΠΊΠ°Β Π²ΡΠΏΠΎΠ»Π½ΡΠ»Π°ΡΡΒ ΡΒ ΡΡΠ΅ΡΠΎΠΌΒ Π²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠΉΒ ΠΈΒ ΡΠ°ΡΡΠΎΡΠ½ΠΎΠΉΒ ΡΠΈΠ½Ρ
ΡΠΎΠ½ΠΈΠ·Π°ΡΠΈΠΈ,Β ΠΏΠΎΡΠΊΠΎΠ»ΡΠΊΡΒ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅Β ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΎΡΡΒ Π²Β Π±Π΅ΡΠΏΡΠΎΠ²ΠΎΠ΄Π½ΠΎΠΌΒ ΠΊΠ°Π½Π°Π»Π΅Β ΡΒ ΡΠ°ΡΡΠΎΡΠ½ΠΎ-Π²ΡΠ΅ΠΌΠ΅Π½Π½ΡΠΌΒ ΡΠ°ΡΡΠ΅ΡΠ½ΠΈΠ΅ΠΌ.Β ΠΡΠ΅ΠΌΠ΅Π½Π½Π°Ρ ΡΠΈΠ½Ρ
ΡΠΎΠ½ΠΈΠ·Π°ΡΠΈΡ ΠΎΠ±Π΅ΡΠΏΠ΅ΡΠΈΠ²Π°Π»Π°ΡΡ ΠΊΠΎΡΡΠ΅Π»ΡΡΠΈΠΎΠ½Π½ΡΠΌ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠΌ Π²ΠΎ Π²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠΉ ΠΎΠ±Π»Π°ΡΡΠΈ. ΠΠ»Ρ ΠΊΠΎΠΌΠΏΠ΅Π½ΡΠ°ΡΠΈΠΈΒ ΡΠ°ΡΡΠΎΠ³Π»Π°ΡΠΎΠ²Π°Π½ΠΈΡΒ ΠΎΠΏΠΎΡΠ½ΡΡ
Β Π³Π΅Π½Π΅ΡΠ°ΡΠΎΡΠΎΠ²Β ΠΏΡΠΈΠΌΠ΅Π½ΡΠ»Π°ΡΡΒ ΠΎΡΠ΅Π½ΠΊΠ°Β ΡΒ ΠΏΠΎΠΌΠΎΡΡΡΒ ΠΏΡΠ΅Π°ΠΌΠ±ΡΠ»Ρ,Β ΡΠΎΡΡΠΎΡΡΠ΅ΠΉ ΠΈΠ· Π΄Π²ΡΡ
ΡΠΈΠΌΠ²ΠΎΠ»ΠΎΠ². Π ΡΠ°Π±ΠΎΡΠ΅ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π»Π°ΡΡ ΠΎΡΠ΅Π½ΠΊΠ° ΠΊΠ°Π½Π°Π»Π° ΠΌΠ΅ΡΠΎΠ΄ΠΎΠΌ Zero Forcing, Π° ΡΠ°ΠΊΠΆΠ΅ ΡΠΊΠ²Π°Π»Π°ΠΉΠ·Π΅Ρ Ρ Π»ΠΈΠ½Π΅ΠΉΠ½ΡΠΌΒ ΠΈΠ½ΡΠ΅ΡΠΏΠΎΠ»ΡΡΠΎΡΠΎΠΌ.Β ΠΠ»ΡΒ ΠΊΠΎΡΡΠ΅ΠΊΡΠ½ΠΎΠΉΒ ΠΎΡΠ΅Π½ΠΊΠΈΒ ΠΊΠ°Π½Π°Π»Π°Β Π²Β FBMC/OQAMΒ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π»ΠΈΡΡΒ ΠΏΠΈΠ»ΠΎΡΠ½ΡΠ΅ ΡΠΈΠΌΠ²ΠΎΠ»Ρ, ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Π½ΡΠ΅ ΠΏΠΎ Π²ΡΠ΅ΠΉ ΡΠ°ΡΡΠΎΡΠ½ΠΎ-Π²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠΉ ΡΠ΅ΡΠΊΠ΅, Π° ΡΠ°ΠΊΠΆΠ΅ ΠΌΠ΅ΡΠΎΠ΄ Ρ Π΄ΠΎΠΏΠΎΠ»Π½ΠΈΡΠ΅Π»ΡΠ½ΡΠΌ ΠΏΠΈΠ»ΠΎΡΠΎΠΌ Π΄Π»Ρ ΠΊΠΎΠΌΠΏΠ΅Π½ΡΠ°ΡΠΈΠΈ ΠΌΠ΅ΠΆΠΊΠ°Π½Π°Π»ΡΠ½ΠΎΠΉ ΠΈΠ½ΡΠ΅ΡΡΠ΅ΡΠ΅Π½ΡΠΈΠΈ. Π ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠ΅ ΡΠ°Π±ΠΎΡΡ ΠΏΠΎΠ»ΡΡΠ΅Π½Ρ Π·Π°Π²ΠΈΡΠΈΠΌΠΎΡΡΠΈ ΠΊΠΎΡΡΡΠΈΡΠΈΠ΅Π½ΡΠ° Π±ΠΈΡΠΎΠ²ΡΡ
ΠΎΡΠΈΠ±ΠΎΠΊ ΠΎΡ ΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΡ ΡΠ½Π΅ΡΠ³ΠΈΠΈ, ΠΏΡΠΈΡ
ΠΎΠ΄ΡΡΠ΅ΠΉΡΡ Π½Π° Π±ΠΈΡ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ, ΠΊ ΡΠ½Π΅ΡΠ³ΠΈΠΈ ΡΡΠΌΠ° Π² ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ
Β ΠΊΠ°Π½Π°Π»Π°Ρ
.Β ΠΠΎΡΡΠΈΠ³Π½ΡΡΒ ΠΊΠΎΡΡΡΠΈΡΠΈΠ΅Π½ΡΒ ΠΎΡΠΈΠ±ΠΎΠΊΒ 10β4Β ΠΏΡΠΈΒ ΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΡΡ
Β ΡΠ½Π΅ΡΠ³ΠΈΠΈ,Β ΠΏΡΠΈΡ
ΠΎΠ΄ΡΡΠ΅ΠΉΡΡΒ Π½Π°Β Π±ΠΈΡ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ, ΠΊ ΠΌΠΎΡΠ½ΠΎΡΡΠΈ ΡΡΠΌΠ°, ΡΠ°Π²Π½ΡΡ
13.4 Π΄Π Π² ΠΏΠ΅ΡΠ²ΠΎΠΌ ΠΊΠ°Π½Π°Π»Π΅, 15.3 Π΄Π Π²ΠΎ Π²ΡΠΎΡΠΎΠΌ ΠΈ 20.9 Π΄Π Π² ΡΡΠ΅ΡΡΠ΅ΠΌ. ΠΠ°ΠΊΠ»ΡΡΠ΅Π½ΠΈΠ΅. Π‘ΠΈΡΡΠ΅ΠΌΠ° ΠΏΠ΅ΡΠ΅Π΄Π°ΡΠΈ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ FBMC/OQAM Ρ Π»ΠΈΠ½Π΅ΠΉΠ½ΡΠΌ ΡΠΊΠ²Π°Π»Π°ΠΉΠ·Π΅ΡΠΎΠΌ ΠΌΠΎΠΆΠ΅Ρ ΡΠ°Π±ΠΎΡΠ°ΡΡ Π±Π΅Π· ΡΠΈΠΊΠ»ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎΒ ΠΏΡΠ΅ΡΠΈΠΊΡΠ°Β Π²Β Π±Π΅ΡΠΏΡΠΎΠ²ΠΎΠ΄Π½ΠΎΠΌΒ ΠΊΠ°Π½Π°Π»Π΅Β ΡΠ²ΡΠ·ΠΈΒ ΡΒ ΠΌΠ½ΠΎΠ³ΠΎΠ»ΡΡΠ΅Π²ΠΎΡΡΡΡ,Β ΠΎΠ±Π΅ΡΠΏΠ΅ΡΠΈΠ²Π°ΡΒ ΡΡΠ°Π²Π½ΠΈΠΌΡΡΒ Ρ OFDM-CPΒ ΠΏΠΎΠΌΠ΅Ρ
ΠΎΡΡΡΠΎΠΉΡΠΈΠ²ΠΎΡΡΡ.Β ΠΠ»ΡΒ ΠΏΠΎΠ»ΡΡΠ΅Π½ΠΈΡΒ Π±ΠΎΠ»ΡΡΠ΅ΠΉΒ ΡΠΏΠ΅ΠΊΡΡΠ°Π»ΡΠ½ΠΎΠΉΒ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈΒ Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎΒ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°ΡΡ Π΄Π»ΠΈΠ½Π½ΡΠ΅ ΠΊΠ°Π΄ΡΡ, ΠΏΠΎΡΠΊΠΎΠ»ΡΠΊΡ Π² Π½Π°ΡΠ°Π»Π΅ ΠΈ ΠΊΠΎΠ½ΡΠ΅ ΠΊΠ°Π΄ΡΠ° FBMC/OQAM ΠΈΠΌΠ΅Π΅ΡΡΡ ΠΏΠ΅ΡΠ΅Ρ
ΠΎΠ΄Π½Π°Ρ Π·ΠΎΠ½Π°
The Graph Curvature Calculator and the curvatures of cubic graphs
We classify all cubic graphs with either non-negative Ollivier-Ricci
curvature or non-negative Bakry-\'Emery curvature everywhere. We show in both
curvature notions that the non-negatively curved graphs are the prism graphs
and the M\"obius ladders. We also highlight an online tool for calculating the
curvature of graphs under several variants of these curvature notions that we
use in the classification. As a consequence of the classification result we
show, that non-negatively curved cubic expanders do not exist
Recommended from our members
System Properties of Implicit Passive Electrical Networks Descriptions
Redesigning systems by changing elements, topology, organization, augmenting the system by the addition of subsystems, or removing parts, is a major challenge for systems and control theory. A special case is the redesign of passive electric networks which aims to change the natural dynamics of the network (natural frequencies) by the above operations leading to a modification of the network. This requires changing the system to achieve the desirable natural frequencies and involves the selection of alternative values for dynamic elements and non-dynamic elements within a fixed interconnection topology and/or alteration of the interconnection topology and possible evolution of the network (increase of elements, branches). The use of state-space or transfer function models does not provide a suitable framework for the study of this problem, since every time such changes are introduced, a new state space or transfer function model has to be recalculated. The use of impedance and admittance modeling, provides a suitable framework for the study of network properties under the process of re-engineering transformations. This paper deals with the fundamental system properties of the impedance-admittance network description which provide the appropriate framework for network re-engineering. We identify the natural topologies expressing the structured transformations linked to the impedance-graph, admittance graph-topology of the network and examine issues such as network regularity, number of finite frequencies and provide characterization of them in terms of the basic network matrices. The implicit network representation introduced provides a natural framework for expressing the different types of re-engineering transformations which can be used for the study of the natural frequencies assignment
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