Browsing by Subject "White noise"

Now showing 1 - 8 of 8

Open Access
Bounds on the capacity of random insertion and deletion-additive noise channels
(IEEE, 2013) Rahmati, M.; Duman, T. M.
We develop several analytical lower bounds on the capacity of binary insertion and deletion channels by considering independent uniformly distributed (i.u.d.) inputs and computing lower bounds on the mutual information between the input and output sequences. For the deletion channel, we consider two different models: i.i.d. deletion-substitution channel and i.i.d. deletion channel with additive white Gaussian noise (AWGN). These two models are considered to incorporate effects of the channel noise along with the synchronization errors. For the insertion channel case, we consider Gallager's model in which the transmitted bits are replaced with two random bits and uniform over the four possibilities independently of any other insertion events. The general approach taken is similar in all cases, however the specific computations differ. Furthermore, the approach yields a useful lower bound on the capacity for a wide range of deletion probabilities of the deletion channels, while it provides a beneficial bound only for small insertion probabilities (less than 0.25) of the insertion model adopted. We emphasize the importance of these results by noting that: 1) our results are the first analytical bounds on the capacity of deletion-AWGN channels, 2) the results developed are the best available analytical lower bounds on the deletion-substitution case, 3) for the Gallager insertion channel model, the new lower bound improves the existing results for small insertion probabilities. © 1963-2012 IEEE.
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
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
Input sequence estimation and blind channel identification in HF communication
(IEEE, 2000) Khames, Mariam; Miled, B. H.; Arıkan, Orhan
A new algorithm is proposed for reliable communication over HF tropospheric links in the presence of rapid channel variations. In the proposed approach, using fractionally space channel outputs, sequential estimation of channel characteristics and input sequence is performed by utilizing subspace tracking and Kalman filtering. Simulation based comparisons with the existing algorithms show that the proposed approaches significantly improve the performance of the communication system and enable us to utilize HF communication in bad conditions.
Open Access
Iterative technique for 3-D motion estimation in videophone applications
(IEEE, 1994-04) Bozdağı, Gözde; Tekalp, A. M.; Onural, Levent
In object based coding of facial images, the accuracy of motion and depth parameter estimates strongly affects the coding efficiency. We propose an improved algorithm based on stochastic relaxation for 3-D motion and depth estimation that converges to true motion and depth parameters even in the presence of 50% error in the initial depth estimates. The proposed method is compared with an existing algorithm (MBASIC) in case of different number of point correspondences. The simulation results show that the proposed method provides significantly better results than the MBASIC algorithm.
Open Access
Lower bounds on the error probability of turbo codes
(IEEE, 2014-06-07) Özçelikkale, Ayça; Duman, Tolga M.
We present lower bounds on the error probability of turbo codes under maximum likelihood (ML) decoding. We focus on additive white Gaussian noise (AWGN) channels, and consider both ensembles of codes with uniform interleaving and specific turbo codes with fixed interleavers. To calculate the lower bounds, instead of using the traditional approach that only makes use of the distance spectrum, we propose to utilize the exact second order distance spectrum. This approach together with a proper restriction of the error events results in promising lower bounds. © 2014 IEEE.
Open Access
Optimal image restoration with the fractional Fourier transform
(OSA - The Optical Society, 1998-04) Kutay, M. A.; Özaktaş, Haldun M.
The classical Wiener filter, which can be implemented in O(N log N) time, is suited best for space-invariant degradation models and space-invariant signal and noise characteristics. For space-varying degradations and nonstationary processes, however, the optimal linear estimate requires O(N2) time for implementation. Optimal filtering in fractional Fourier domains permits reduction of the error compared with ordinary Fourier domain Wiener filtering for certain types of degradation and noise while requiring only O(N log N) implementation time. The amount of reduction in error depends on the signal and noise statistics as well as on the degradation model. The largest improvements are typically obtained for chirplike degradations and noise, but other types of degradation and noise may also benefit substantially from the method (e.g., nonconstant velocity motion blur and degradation by inhomegeneous atmospheric turbulence). In any event, these reductions are achieved at no additional cost. © 1998 Optical Society of America.
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.