Browsing by Subject "Gaussian noise (electronic)"

Now showing 1 - 9 of 9

Open Access
A complexity-reduced ML parametric signal reconstruction method
(2011) Deprem, Z.; Leblebicioglu, K.; Arkan O.; Çetin, A.E.
The problem of component estimation from a multicomponent signal in additive white Gaussian noise is considered. A parametric ML approach, where all components are represented as a multiplication of a polynomial amplitude and polynomial phase term, is used. The formulated optimization problem is solved via nonlinear iterative techniques and the amplitude and phase parameters for all components are reconstructed. The initial amplitude and the phase parameters are obtained via time-frequency techniques. An alternative method, which iterates amplitude and phase parameters separately, is proposed. The proposed method reduces the computational complexity and convergence time significantly. Furthermore, by using the proposed method together with Expectation Maximization (EM) approach, better reconstruction error level is obtained at low SNR. Though the proposed method reduces the computations significantly, it does not guarantee global optimum. As is known, these types of non-linear optimization algorithms converge to local minimum and do not guarantee global optimum. The global optimum is initialization dependent. © 2011 Z. Deprem et al.
Open Access
Convexity properties of detection probability under additive Gaussian noise: optimal signaling and jamming strategies
(IEEE, 2013) Dulek, B.; Gezici, Sinan; Arıkan, Orhan
In this correspondence, we study the convexity properties for the problem of detecting the presence of a signal emitted from a power constrained transmitter in the presence of additive Gaussian noise under the Neyman-Pearson (NP) framework. It is proved that the detection probability corresponding to the α-level likelihood ratio test (LRT) is either strictly concave or has two inflection points such that the function is strictly concave, strictly convex, and finally strictly concave with respect to increasing values of the signal power. In addition, the analysis is extended from scalar observations to multidimensional colored Gaussian noise corrupted signals. Based on the convexity results, optimal and near-optimal time sharing strategies are proposed for average/peak power constrained transmitters and jammers. Numerical methods with global convergence are also provided to obtain the parameters for the proposed strategies.
Open Access
Entropy minimization based robust algorithm for adaptive networks
(IEEE, 2012) Köse, Kıvanç; Çetin, A. Enis; Gunay O.
In this paper, the problem of estimating the impulse responses of individual nodes in a network of nodes is dealt. It was shown by the previous work in literature that when the nodes can interact with each other, fusion based adaptive filtering approaches are more effective than handling nodes independently. Here we are proposing the use of entropy functional based optimization in the adaptive filtering stage. We tested the new method on networks under Gaussian and ε-contaminated Gaussian noise. The results show that the proposed method achieves significant improvements in the error rates in case of ε-contaminated noise. © 2012 IEEE.
Open Access
The fractional fourier transform and its applications to image representation and beamforming
(ASME, 2003-09) Yetik, I. Ş; Kutay, M. A.; Özaktaş, Haldun. M.
The ath order fractional Fourier transform operator is the ath power of the ordinary Fourier transform operator. We provide a brief introduction to the fractional Fourier transform, discuss some of its more important properties, and concentrate on its applications to image representation and compression, and beamforming. We show that improved performance can be obtained by employing the fractional Fourier transform instead of the ordinary Fourier transform in these applications.
Open Access
Generalized approximate message-passing decoder for universal sparse superposition codes
(IEEE, 2017-06) Bıyık, Erdem; Barbier, J.; Dia, M.
Sparse superposition (SS) codes were originally proposed as a capacity-achieving communication scheme over the additive white Gaussian noise channel (AWGNC) [1]. Very recently, it was discovered that these codes are universal, in the sense that they achieve capacity over any memoryless channel under generalized approximate message-passing (GAMP) decoding [2], although this decoder has never been stated for SS codes. In this contribution we introduce the GAMP decoder for SS codes, we confirm empirically the universality of this communication scheme through its study on various channels and we provide the main analysis tools: state evolution and the potential. We also compare the performance of GAMP with the Bayes-optimal MMSE decoder. We empirically illustrate that despite the presence of a phase transition preventing GAMP to reach the optimal performance, spatial coupling allows to boost the performance that eventually tends to capacity in a proper limit. We also prove that, in contrast with the AWGNC case, SS codes for binary input channels have a vanishing error floor in the limit of large codewords. Moreover, the performance of Hadamard-based encoders is assessed for practical implementations. © 2017 IEEE.
Open Access
An image watermarking algorithm via Zero Assigned Filter Banks
(IEEE, 2005-12) Yücel, Zeyep; Özgüler, A. Bülent
In this paper a new method for digital image watermarking based on Zero Assigned Filter Banks and Embedded Zero Tree Wavelet (EZW) algorithm is presented. An image is partitioned into 128 × 128 subblocks and each block is processed in a three stage decomposition structure by a filter bank which is assigned a zero around the stop band. The coefficients to be marked are chosen according to the EZW algorithm. This method not only provides a robust watermarking scheme but may also be used as an effective compression strategy. The algorithm is tested under white Gaussian noise and against JPEG compression and it is observed to be robust even when exposed to high levels of corruption. © 2005 IEEE.
Open Access
Performance analysis of turbo codes over Nakagami-m fading channels with impulsive noise
(IEEE, 2007) Ali, Syed Amjad; İnce, E. A.
The statistical characteristics of impulsive noise differ greatly from those of Gaussian noise. Hence, the performance of conventional decoders, optimized for AWGN channels is not promising in non-Gaussian environments. In order to achieve improved performance in impulsive environments the decoder structure needs to be adapted in accordance with the impulsive noise model. This paper provides performance analysis of turbo codes over fully interleaved Nakagami-m fading channels with Middleton's additive white Class-A impulsive noise (MAWCAIN). Simulation results for memoryless Nakagami-m fading channels under coherent BPSK signaling are provided for the cases of ideal channel state information (ICSI) and no channel state information (NCSI) at the decoder. As in the 3GPP UMTS forward link an eight state turbo encoder having (1, 13/15, 13/15) generator polynomial is used throughout the analysis. The novelty of this work lies in the fact that this is an initial attempt to provide a detailed analysis of turbo codes over Nakagami-m fading channels with impulsive noise rather than fading channels with AWGN. © 2007 IEEE.
Open Access
Performance analysis of turbo codes over Rician fading channels with impulsive noise
(IEEE, 2007) Ali, Syed Amjad; Ince, E.A.
The statistical characteristics of impulsive noise differ greatly from those of Gaussian noise. Hence, the performance of conventional decoders, optimized for additive white Gaussian noise (AWGN) channels is not promising in non-Gaussian environments. In order to achieve improved performance in impulsive environments the decoder structure needs to be modified in accordance with the impulsive noise model. This paper provides performance analysis of turbo codes over fully interleaved Rician fading channels with Middleton's additive white Class-A impulsive noise (MAWCAIN). Simulation results for the memoryless Rician fading channels using coherent BPSK signaling for both the cases of ideal channel state information (ICSI) and no channel state information (NCSI) at the decoder are provided. An eight state turbo encoder having (1, 13/15, 13/15) generator polynomial is used throughout the analysis. The novelty of this work lies in the fact that this is an initial attempt to provide a detailed analysis of turbo codes over Rician fading channels with impulsive noise rather than AWGN. ©2007 IEEE.
Open Access
Spectrum sensing via restricted neyman-pearson approach in the presence of non-Gaussian noise
(IEEE, 2013) Turgut, Esma; Gezici, Sinan
In this paper, spectrum sensing in cognitive radio systems is studied for non-Gaussian channels in the presence of prior distribution uncertainty. In most practical cases, some amount of prior information about signals of primary users is available to secondary users but that information is never perfect. In order to design optimal spectrum sensing algorithms in such cases, we propose to employ the restricted Neyman-Pearson (NP) approach, which maximizes the average detection probability under constraints on the worst-case detection and false-alarm probabilities. We derive a restricted NP based spectrum sensing algorithm for additive Gaussian mixture noise channels, and compare its performance against the generalized likelihood ratio test (GLRT) and the energy detector. Simulation results show that the proposed spectrum sensing algorithm provides improvements over the other approaches in terms of minimum (worst-case) and/or average detection probabilities. © 2013 IEEE.