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One important innovation in information and coding theory is polar code, which delivers capacity attaining error correction performance varying code rates and block lengths. In recent times, polar codes are preferred to offer channel coding in the physical control channels of the 5G (5th Generation) wireless standard by 3GPP (Third Generation Partnership Project) New Radio (NR) group. Being a part of the physical layer, Channel coding plays key role in deciding latency and reliability of a communication system. However, the error correction performance degrades with decreased message lengths. 5G NR requires channel codes with low rates, very low error floors with short message lengths and low latency in coding process. In this work, Distributed Cyclic Redundancy Check Aided polar (DCA-polar) code along with Cyclic Redundancy Check Aided polar (CA-polar) code, the two variant of polar codes have been proposed which provide significant error-correction performance in the regime of short block lengths and enable early termination of decoding processes. While CRC bits improve the performance of SCL (successive cancellation list) decoding by increasing distance properties, distributed CRC bits permit path trimming and early-termination of the decoding process. The design can reduce the decoding latency and energy consumption of hardware, which is crucial for mobile applications like 5G. The work also considers the performance analysis of NR polar codes over AWGN (Additive White Gaussian Noise) for short information block lengths at low code rates in the uplink and downlink control channels using SNR (Signal to Noise Ratio) and FAR (False Alarm Rate) as the performance measures. Simulation results illustrate different trade-offs between error-correction and detection performances comparing proposed NR polar coding schemes. [ABSTRACT FROM AUTHOR]

Aiming to address the problems of the high bit error rate (BER) of demodulation or low classification accuracy of modulation signals with a low signal-to-noise ratio (SNR), we propose a double-residual denoising autoencoder method with a channel attention mechanism, referred to as DRdA-CA, to improve the SNR of modulation signals. The proposed DRdA-CA consists of an encoding module and a decoding module. A squeeze-and-excitation (SE) ResNet module containing one residual connection is modified and then introduced into the autoencoder as the channel attention mechanism, to better extract the characteristics of the modulation signals and reduce the computational complexity of the model. Moreover, the other residual connection is further added inside the encoding and decoding modules to optimize the network degradation problem, which is beneficial for fully exploiting the multi-level features of modulation signals and improving the reconstruction quality of the signal. The ablation experiments prove that both the improved SE module and dual residual connections in the proposed method play an important role in improving the denoising performance. The subsequent experimental results show that the proposed DRdA-CA significantly improves the SNR values of eight modulation types in the range of −12 dB to 8 dB. Especially for 16QAM and 64QAM, the SNR is improved by 8.38 dB and 8.27 dB on average, respectively. Compared to the DnCNN denoising method, the proposed DRdA-CA makes the average classification accuracy increase by 67.59∼74.94% over the entire SNR range. When it comes to the demodulation, compared with the RLS and the DnCNN denoising algorithms, the proposed denoising method reduces the BER of 16QAM by an average of 63.5% and 40.5%, and reduces the BER of 64QAM by an average of 46.7% and 18.6%. The above results show that the proposed DRdA-CA achieves the optimal noise reduction effect. [ABSTRACT FROM AUTHOR]

Image noise occurs during acquisition and transmission and adversely affects processes, such as image segmentation and object recognition and classification. Various techniques are being studied for noise removal, and with the recent development of hardware and image processing algorithms, noise removal techniques that combine non-local techniques are attracting attention. However, one disadvantage of this method is that blurring occurs in the edges and boundary line of the resulting image. In this study, we proposed a modified local steering kernel based on image matching to improve these shortcomings. The proposed technique uses image matching to differentiate the weight obtained by the steering kernel according to the local characteristics of the image and calculates the weight of the filter based on the similarity between the center window and the matching window. The resulting images were quantitatively evaluation and enlargement of images were used and compared with the existing noise removal algorithms. The proposed algorithm showed clearer contrast in the enlarged images and better results than the conventional image restoration techniques in the quantitative evaluation using peak signal-to-noise ratio and structural similarity index. [ABSTRACT FROM AUTHOR]

We consider the distributional connection between the lossy compressed representation of a high-dimensional signal X using a random spherical code and the observation of X under an additive white Gaussian noise (AWGN). We show that the Wasserstein distance between a bitrate-R compressed version of X and its observation under an AWGN-channel of signal-to-noise ratio 22R−1 is bounded in the problem dimension. We utilize this fact to connect the risk of an estimator based on the compressed version of X to the risk attained by the same estimator when fed the AWGN-corrupted version of X. We demonstrate the usefulness of this connection by deriving various novel results for inference problems under compression constraints, including minimax estimation, sparse regression, compressed sensing, and universality of linear estimation in remote source coding. [ABSTRACT FROM AUTHOR]

Impulsive noise significantly deteriorates the performance of orthogonal frequency-division multiplexing (OFDM)-based underwater acoustic (UWA) communication systems. The pulse blanking (PB) based approach can mitigate the impulsive noise. However, it causes inter-carrier interference (ICI) and signal attenuation to the receiver. In this work, we first show that the ICI introduces pronounced non-Gaussianity to the receiver chain and leads to significant performance degradation. We then propose a non-Gaussianity-aware iterative ICI cancelation scheme to mitigate the adverse impacts of PB. A companding transformation scheme is incorporated into the soft symbol computation to alleviate the non-Gaussianity of the log-likelihood ratios (LLRs) caused by the residual ICI and impulsive noise. Simulation results illustrate that the proposed non-Gaussianity-aware iterative receiver achieves significant performance gains over the conventional non-Gaussianity-agnostic one with even lower computational complexity. [ABSTRACT FROM AUTHOR]

Blind noise-level estimation (NLE) is a fundamental issue in digital image processing. This paper provides a noise-level estimator for additive white Gaussian noise and multiplicative Gaussian noise using principal texture patches (PTPs). The proposed algorithm first identifies the principal texture of the noisy image by using the principal component analysis, and then, it chooses PTPs to calculate the noise level. The major contributions of this paper toward addressing the challenges in the NLE literature include: 1) analyzing the nonlinear relationship between the smallest eigenvalue, true noise level, number of chosen patches, and block size; 2) extracting PTPs; and 3) computing noise level using PTPs. The abundant experimental results show that the proposed method works well for various natural images over a large range of noise levels and it performs well for multiplicative noise. Compared with some state-of-the-art approaches, our method has the best performance and a faster running speed. [ABSTRACT FROM AUTHOR]

In this paper, we present a unique modulation classification method that is based on determining an attractive relation between higher-order cumulants (HOCs) using a decision tree-classifier to improve the extracted features employed for the recognition of modulation schemes, such as phase shift keying (PSK) and quadrature amplitude modulation (QAM). A threshold algorithm is applied to the proposed classifier, which consists of sub-classifiers, each comprising a single feature, and each being capable of distinguishing the modulation types individually. In this work, a high-accuracy classifier system is utilized to recognize modulation schemes, such as QAM (16, 32, 64, 128, and 256) and (2, 4, and 8) PSK at a low signal-to-noise ratio (SNR). In this study, 1000 signals are studied for each SNR of –5 dB to 30 dB. The most prominent results of the classifier decisions range from 88% to 100% with regard to distinguishing the same types of PSK and QAM. In the long run, the proposed classifier module will be advantageous in terms of accuracy and computational complexity relative to the other classifiers in the literature. The results demonstrate that the proposed algorithm has a significantly better classification accuracy in comparison with the previously proposed ones. • A new method for automatic modulation classification is presented. • Optimize the extracted features distribution using logarithmic properties. • Multiple logarithmic hierarchical classifier outperforms over conventional classifiers. • Enhanced classification performance through multiple tree algorithm. • Simulation results confirmed the efficiency of the proposed algorithm under different noise scenarios. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of different modulation techniques for digital communication systems that employ quadrature phase shift keying (QPSK) and quadrature amplitude modulation (16-QAM and 64-QAM) to transmit images over AWGN and Rayleigh fading channels for the cellular mobile networks. In the further steps, wiener and median filters has been adopted to the simulation are used at the receiver side to remove the impulsive noise present in the received image. This work is performed to evaluate the transmission of two dimensional (2D) gray-scale and color-scale (RGB) images with different values from signal to noise ratios (SNR), such as; (5, 10 and 15) dB over different channels. The correct conclusions are made by comparing many of the observed Matlab simulation results. This was carried out through the results that measure the quality of received image, which is analyzes in terms of SNRimage peak signal to noise ratio (PSNR) and mean square error (MSE). [ABSTRACT FROM AUTHOR]

This paper presents a novel autocorrelation-based algorithm that uses statistical knowledge to detect orthogonal frequency division multiplexing signals in channels where frequency offset is present. The algorithm may be viewed as a significant improvement over other types of autocorrelation algorithms that appear in literature that lead to false alarm due to the hardware impairment of frequency offset. The algorithm works by making an unbiased estimate of the square of an autocorrelation coefficient and from that deduces an appropriate probability density function for the phase angle of the complex test statistic and thereby palliating the effect of phase distortion introduced by the frequency offset. It is shown that the algorithm presented in this paper can be implemented on a testbed, as well as overcome simulations that have been specifically designed to have worst case frequency offset phase distortion conditions. [ABSTRACT FROM AUTHOR]

Multi-layer broadcast systems distribute services across time and frequency domain by means of power-division multiplexing. Successive interference cancelation is required, in general, in order to extract the content of all services. For a low-complexity implementation, the receiver can obtain the strongest (top-layer) signal assuming underlying signals to behave like thermal noise. The thermal noise assumption may not be valid under certain conditions and a more accurate characterization of the interference could bring improved performance. This paper analyzes the validity of the noise-like assumption considering the power ratio between signals and the required carrier-to-noise ratio for error-free reception. The main contribution of the paper is the proposal of a demapping algorithm that exploits the knowledge of the constellation of underlying signals. Generalized mutual information, performance evaluation, and complexity analysis are provided with the additive white Gaussian noise-like assumptions and with the proposed alternative in order to assess the potential performance improvements that can be achieved. [ABSTRACT FROM AUTHOR]

In this paper, we revisit the design of Raptor codes for binary input additive white Gaussian noise channels, where we are interested in very low signal to noise ratios (SNRs). A linear programming degree distribution optimization problem is defined for Raptor codes in the low SNR regime through several approximations. We also provide an exact expression for the polynomial representation of the degree distribution with infinite maximum output node degree in the low SNR regime, which enables us to calculate the exact value of the fractions of output nodes of small degrees. A more practical degree distribution design is also proposed for Raptor codes in the low SNR regime, where we include the rate efficiency and the decoding complexity in the optimization problem, and an upper bound on the maximum rate efficiency is derived for given design parameters. Simulation results show that the Raptor code with the designed degree distributions can approach rate efficiencies larger than 0.95 in the low SNR regime. [ABSTRACT FROM PUBLISHER]

In this paper, we propose to derive an approximate theoretical distribution under the null hypothesis of the low-rank adaptive normalized matched filter (LR-ANMF). This detector is used to detect a target when the disturbance is composed of a low-rank Gaussian contribution (called clutter) and an additive white Gaussian noise. In the LR-ANMF, the estimated covariance matrix is replaced by the estimated orthogonal projector onto the subspace clutter. The method to derive this distribution is based on perturbation analysis and assumes a steering vector far from the clutter and a large clutter-to-noise ratio. Simulations on a space?time adaptive processing example validate our theoretical result. The impact of both hypotheses is also studied. [ABSTRACT FROM PUBLISHER]

We denoise Poisson images with an iterative algorithm that progressively improves the effectiveness of variance-stabilizing transformations (VST) for Gaussian denoising filters. At each iteration, a combination of the Poisson observations with the denoised estimate from the previous iteration is treated as scaled Poisson data and filtered through a VST scheme. Due to the slight mismatch between a true scaled Poisson distribution and this combination, a special exact unbiased inverse is designed. We present an implementation of this approach based on the BM3D Gaussian denoising filter. With a computational cost at worst twice that of the noniterative scheme, the proposed algorithm provides significantly better quality, particularly at low signal-to-noise ratio, outperforming much costlier state-of-the-art alternatives. [ABSTRACT FROM PUBLISHER]

In this paper, we estimate the achievable localization error in an ultra-wideband (UWB) precise positioning system. The system is based on the time difference of arrival of narrow pulses to a multitude of base-stations. A mathematical model and simulation platform are developed to describe the behavior of the UWB indoor localization system. Limits on the location accuracy as a function of the parameters of the UWB system are described. A discussion of the dominant errors is presented including picosecond pulse generator jitter, sampling clock jitter, sampling rate, and system additive white Gaussian noise. We show a simple method to calculate the total system jitter, and describe error biasing phenomenon as the tag moves, approaching one base-station and moving away from another. Design curves are provided to determine the required specifications of the various system components to achieve a certain positioning accuracy. [ABSTRACT FROM AUTHOR]

In this paper, an FrFT appended OFDM system has been proposed. In the proposed system, the FrFT block has been appended at the output of OFDM transmitter to combat the effect of multipath fading. The performance of the proposed system in terms of BER has been evaluated in different channel environments like AWGN, Rayleigh, Rician and Nakagami for a 1024-PSK and 1024-QAM modulation technique. From the simulation results, it has been found that the proposed system provides a gain of 5.5 dB in SNR to achieving BER of 10 −2.1 for 1024-PSK modulation technique in Rayleigh fading channel as compared to the traditional OFDM system. For 1024-QAM modulation technique, the proposed system provides an improvement of 4.6 dB to achieve 10 −2.4 BER in Rayleigh fading channel. [ABSTRACT FROM AUTHOR]

In this letter, a new subspace based estimator that can effectively provide the order and frequencies of multiple sinusoids in noise is proposed. The estimator, referred to as SAS-Est (Subspace Aligning and Separating Estimator), simultaneously seeks to separate the steering vectors from the noise subspace and align them to the signal subspace. The angles between subspaces and the generalized Kullback-Leibler divergence are used in characterizing the alignment and separation. Minimizing the divergence leads to maximal subspace separation and best alignment, thus allowing improved performance. Simulations in additive white Gaussian noise show that the new estimator offers an improvement for both model order and frequency estimation. When compared with other methods, the improvement is more pronounced for high model orders and low signal-to-noise ratio values. [ABSTRACT FROM AUTHOR]

Higher order M-ary phase shift keying (MPSK) and differential phase shift keying (MDPSK) (M≥ 4) are used in optical communications for increased spectral efficiency. This paper proposes a unified and systematic approach to predicting the error probability of MPSK with phase reference error (PRE) and MDPSK with residual phase noise (RPN) in additive white Gaussian noise (AWGN) channel. It is shown that AWGN leads to an equivalent additive observation phase noise (AOPN), whose probability density function (pdf) conditioned on knowing the received signal magnitude is Tikhonov. For high signal-to-noise ratio (SNR), the Tikhonov pdf can be accurately approximated by a Gaussian pdf. This AOPN can be combined with the PRE/RPN, and the distribution of the combined phase noise (AOPN + PRE/RPN) facilitates the computation of the probability of the received signal phasor falling in any sector in the complex plane. It thus enables us to express the symbol error probability of MPSK/MDPSK with phase noise as one Gaussian Q-function. Moreover, it facilitates the analysis of bit error probability (BEP) with Gray code mapping for MPSK/MDPSK. All the new BEP expressions obtained are linear combinations of single Gaussian Q-functions, and do not involve the product of Gaussian Q-functions. It is shown that our Gaussian AOPN + PRE/RPN model provides a simpler and quicker way to accurately estimate the error performance as a function of the phase error variance. Our unified approach is increasingly more accurate as M increases. [ABSTRACT FROM PUBLISHER]

Forward error correction (FEC) plays a vital role in coherent optical systems employing multi-level modulation. However, much of coding theory assumes that additive white Gaussian noise (AWGN) is dominant, whereas coherent optical systems have significant phase noise (PN) in addition to AWGN. This changes the error statistics and impacts FEC performance. In this paper, we propose a novel semianalytical method for dimensioning binary Bose-Chaudhuri-Hocquenghem (BCH) codes for systems with PN. Our method involves extracting statistics from pre-FEC bit error rate (BER) simulations. We use these statistics to parameterize a bivariate binomial model that describes the distribution of bit errors. In this way, we relate pre-FEC statistics to post-FEC BER and BCH codes. Our method is applicable to pre-FEC BER around 10-3 and any post-FEC BER. Using numerical simulations, we evaluate the accuracy of our approach for a target post-FEC BER of 10-5. Codes dimensioned with our bivariate binomial model meet the target within 0.2-dB signal-to-noise ratio. [ABSTRACT FROM PUBLISHER]

The ability to recognize various forms of contaminants in surface electromyography (EMG) signals and to ascertain the overall quality of such signals is important in many EMG-enabled rehabilitation systems. In this paper, new methods for the automatic identification of commonly occurring contaminant types in surface EMG signals are presented. Such methods are advantageous because the contaminant type is typically not known in advance. The presented approach uses support vector machines as the main classification system. Both simulated and real EMG signals are used to assess the performance of the methods. The contaminants considered include: 1) electrocardiogram interference; 2) motion artifact; 3) power line interference; 4) amplifier saturation; and 5) additive white Gaussian noise. Results show that the contaminants can readily be distinguished at lower signal to noise ratios, with a growing degree of confusion at higher signal to noise ratios, where their effects on signal quality are less significant. [ABSTRACT FROM AUTHOR]

Time Hopping-Ultra Wideband (TH-UWB) is a relatively new technology that might have a big effect on improving wireless communication. This technology uses short pulses in order to transmit large amounts of digital data over a wide spectrum of frequency bands with a very low power. Unfortunately, in order to process ultra-wideband signals, an extremely large sampling rate is mandatory. Thus, even in very fast workstations, the total computing time in order to estimate Bit Error Rate (BER) can be very high. In this work, a THUWB system is simulated using fast TH-System Simulator. Thanks to this approach, BER performance of a TH-UWB System in different scenarios is presented and low complexity for real time implementation and the good performance in terms of BER versus Signal to Noise Ratio (SNR) are achieved. [ABSTRACT FROM AUTHOR]

The outage probability of a multiuser two-hop amplify-and-forward relaying system employing opportunistic scheduling is investigated. A practically important case where there are cochannel interference signals present at the network is considered for the analysis. Exact expressions and closed-form lower bounds are derived for the outage probability. Exact closed-form expressions are derived for the system outage probability when interference signals are present at the relay and at the destination separately. A closed-form lower bound is derived for the outage probability when the relay and the destination nodes are affected by interference simultaneously. The effects of channel state information feedback delay are investigated for special cases. In addition, asymptotic outage probability results are derived to obtain useful insights on the effects of interference and feedback delay. The novel expressions can be used by practicing engineers to obtain reliable and realistic performance estimates for dual-hop multiuser relay networks. The results are useful for understanding the capabilities of the feedback channel required in this system. [ABSTRACT FROM AUTHOR]

This paper presents the theoretical foundation for time-domain, phase-based estimation of the frequency and phase of a single sinusoid in additive white Gaussian noise (AWGN), analogous to the theoretical foundation provided by Rife and Boorstyn for frequency-domain, Fourier-transform-based estimation. It is shown from the maximum a posteriori probability (MAP) and the maximum likelihood (ML) estimation principles that with the additive observation phase noise (AOPN), due to the AWGN, being described by its a posteriori distribution conditioned on the received signal magnitude, the received signal phase is a sufficient statistic for estimating the single-sinusoid angle parameters. Using a geometric approach, the exact statistical model for the AOPN is derived, where the a posteriori probability density function (pdf) and the corresponding a priori pdf are given by explicit, closed-form expressions that are valid for arbitrary signal-to-noise ratios (SNRs). The a posteriori pdf is Tikhonov, and is of particular interest as it establishes the AOPN model for phase-based frequency/phase MAP/ML estimation in the time domain. It is further illustrated that the results derived can yield various AOPN models as special cases, and the underlying physical insights and interconnections that exist among these models are revealed. It is shown that the model derived by Tretter is an ultimate specialization in the high SNR limit of the AOPN models developed here. For high SNR, the a posteriori Tikhonov pdf can be accurately approximated by a Gaussian distribution, which leads to the best linearized AOPN model. The applications of these AOPN models to the design of linear estimators, including the linear minimum mean square error (LMMSE) estimator, the linear minimum variance estimator, and the LMMSE implementation of the weighted phase averager are presented, and their estimation performances are compared through computer simulations, with the Cramer–Rao lower bound (CRLB) and the Bayesian CRLB as the benchmark. To facilitate estimator design, the a priori statistical models of the frequency and phase are proposed from the information-theoretic perspective, and an improved phase unwrapping algorithm over that given by Fu and Kam is presented. It is shown that by incorporating all the information available in the AOPN, the estimation accuracy can be much improved. [ABSTRACT FROM PUBLISHER]

A study of the effects of co-channel interference on a multirelay system with decode-and-forward (DF) protocol is presented. Orthogonal relaying is considered, and all relays that correctly decode the message in the broadcasting phase participate in the adaptive relaying phase. First, the effective signal-to-interference-plus-noise ratio (SINR) at the receiver is derived. Then, considering outage as the performance metric, we obtain exact closed-form expression for the outage probability. Simple and general asymptotic expressions for the outage probability, which explicitly show the coding and the diversity gains, are also derived and discussed. Furthermore, we present optimal energy-allocation schemes for minimizing outage under different resource constraints. Monte Carlo simulations are further provided to confirm the analytical results and illustrate the outage performance for different interference conditions and optimization schemes. [ABSTRACT FROM PUBLISHER]

The focus of this paper is to study the performance of the quantize-and-forward (QF) scheme over a half-duplex relay channel that is slowly fading, with the assumption that the channel state information (CSI) is available only at the receiver side. In order to do so, three steps are taken. The first step is to characterize the achievable rate of the QF scheme over a discrete memoryless half-duplex relay channel. Then, the achievable rate over a corresponding additive white Gaussian noise channel is obtained (the specific assumption regarding the CSI in this paper makes this step nontrivial). With the results from the first two steps, performance measures such as outage probability, expected rate, and diversity-multiplexing tradeoff (DMT) over slow fading channels are evaluated. It is shown that the QF scheme can significantly outperform the compress-and-forward scheme at finite signal-to-noise ratio (SNR) and it can achieve the optimal DMT at asymptotically high SNR. Moreover, it is shown that simple feedback from the destination node to the relay node can further improve the performance of the QF scheme. [ABSTRACT FROM AUTHOR]

Performance of indoor home networks can be improved by simultaneous use of wireless and powerline communication (PLC) channels. A narrowband model representing an OFDM subcarrier is used to analyze the performance of several diversity combining schemes including optimum combining (OC), saturated metric combining (SMC) and maximal ratio combining (MRC). Results from BER analysis show that SMC achieves good performance in highly impulsive noise and is relatively insensitive to error in noise parameter estimates. Indoor measurements from 3 detached homes show that parallel wireless and PLC channels have a wide, but similar, signal-to-noise ratio (SNR) range. Measurement data is used with link throughput analysis to show that wireless/PLC diversity can be used to minimize the likelihood of low throughput links. [ABSTRACT FROM AUTHOR]

The application of a pulse-compression procedure based on pseudorandom m-sequences to air-coupled ultrasonic nondestructive testing is presented. The signal-to-noise ratio enhancement assured by this technique is theoretically analyzed and experimentally verified, particularly focusing on the positive effect of the procedure to reduce quantization noise. The possibility of faithfully reconstructing signals whose amplitudes are lower than the quantization step of the analog-to-digital converter (ADC) board is analyzed theoretically and experimentally verified. [ABSTRACT FROM PUBLISHER]

This paper compares the partial-decode-forward and the complete-decode-forward coding strategies for the half-duplex Gaussian single-relay channel. We analytically show that the rate achievable by partial-decode-forward outperforms that of the more straightforward complete-decode-forward by at most 12.5%. Furthermore, in the following asymptotic cases, the gap between the partial-decode-forward and the complete-decode-forward rates diminishes: (i) when the relay is close to the source, (ii) when the relay is close to the destination, and (iii) when the SNR is low. In addition, when the SNR increases, this gap, when normalized to the complete-decode-forward rate, also diminishes. Consequently, significant performance improvements are not achieved by optimizing the fraction of data the relay should decode and forward, over simply decoding the entire source message. [ABSTRACT FROM AUTHOR]

Analog-to-digital converters that maximize the information rate between the quantized channel output sequence and the channel input sequence are designed for discrete-time channels with intersymbol-interference, additive noise, and for independent and identically distributed signaling. Optimized scalar quantizers with Λ regions achieve the full information rate of log_2(Λ) bits per channel use with a transmit alphabet of size Λ at infinite signal-to-noise ratio; these quantizers, however, are not necessarily uniform quantizers. Low-precision scalar and two-dimensional analog-to-digital converters are designed at finite signal-to-noise ratio, and an upper bound on the information rate is derived. Simulation results demonstrate the effectiveness of the designed quantizers over conventional quantizers. The advantage of the new quantizers is further emphasized by an example of a channel for which a slicer (with a single threshold at zero) and a carefully optimized channel input with memory fail to achieve a rate of one bit per channel use at high signal-to-noise ratio, in contrast to memoryless binary signaling and an optimized quantizer. [ABSTRACT FROM PUBLISHER]

The L-user additive white Gaussian noise multiway relay channel is investigated, where L users exchange information at the same rate through a single relay. A new achievable rate region, based on the functional-decode-forward coding strategy, is derived. For the case where there are three or more users, and all nodes transmit at the same power, the capacity is obtained. For the case where the relay power scales with the number of users, it is shown that both compress-forward and functional-decode-forward achieve rates within a constant number of bits of the capacity at all SNR levels; in addition, functional-decode-forward outperforms compress-forward and complete-decode-forward at high SNR levels. [ABSTRACT FROM AUTHOR]

Suppressing intertrack interference (ITI) and intersymbol interference (ISI) is crucial for achieving high-density magnetic recording beyond 10 Tera bits/inch^2. We propose a novel iterative method for reducing errors caused by ITI and ISI involving the adaptive estimation of ITI and the log likelihood ratios obtained from signals of neighboring tracks. This method is useful for decoding signals recorded by bit-patterned media and conventional media. Moreover, the method is extended to decode signals from the Voronoi-based discrete grain model for shingled write recording (SWR), accounting for four neighboring bits. Bit errors due to both neighboring track shifts of approximately 20% can be canceled for BPM and SWR. [ABSTRACT FROM AUTHOR]

Most existing stopping criteria for turbo decoding have their root in hypothesis test, requiring a subjective threshold for decision making. A consequence is that the turbo decoding receiver so-constructed can converge at high signal-to-noise ratios (SNRs) but fails at low SNRs, thereby calling for a new design philosophy for stopping criteria. In this correspondence, the problem is tackled in the framework of information theoretic criterion, which enables the turbo decoding to properly work in a changing SNR environment. Numerical results are presented for illustrating the good performance of the proposed method. [ABSTRACT FROM AUTHOR]

BER Performance of a fading channel could be improved by antenna Diversity Technique. Antenna Diversity Technique improves the signal to noise ratio (SNR) by combining multiple received signals. Performance of any communication system reduced by the channel noise and fading that loss some information of the transmitted data. In this paper we represented the effect of noise and multiple fading on the transmitted signal. Simulation study show how antenna Diversity Technique improves BER performance of the fading channel. [ABSTRACT FROM AUTHOR]

Abstract: Collaborative communication produces high power gain and significantly mitigates the fading if both frequency and phase synchronization are achieved. In this paper, a novel collaborative communication system with imperfect phase synchronization that includes the influence of noise and Rayleigh fading is proposed, modelled, theoretically analyzed and simulated. Mathematical expressions for both received power as a function of number of collaborative nodes and bit error rate (BER) as a function of SNR are derived. To analyze the energy efficiency of our proposed collaborative communication system, energy consumption of the system is modelled, simulated and analyzed by considering the parameters of the off-the-shelf products. Exploration of performance shows that the proposed system mitigates the fading, hence, significant power gain and significant reduction in BER can be achieved in the presence of phase errors, AWGN and Rayleigh fading. A detailed theoretical analysis and Monte Carlo simulation revealed that proposed collaborative communication system is an energy efficient communication system that can be implemented in sensor networks as approximately (number of collaborative nodes) times less total transmitted power is required than for the single-input single-output (SISO) communication for a specific transmission range. [Copyright &y& Elsevier]

• This article used a high-resolution time frequency analysis called VFCDM technique for denoising electrocardiogram (ECG) signals under different noisy conditions. • A thorough discussion of the limitations and drawbacks of the existing denoising techniques are presented and their performances are compared with the proposed denoising method. • The proposed denoising technique provides superior denoising performance in terms of standard performance metric when compared to existing denoising methods • The successful application of the proposed denoising techniques on a wearable armband ECG showed a significant improvement in QRS complex detection accuracy. Thus, proposed denoising technique when applied on the wearable armband ECG could results in better arrhythmia detection such as atrial fibrillation (AF). Electrocardiogram (ECG) is widely used for the detection and diagnosis of cardiac arrhythmias such as atrial fibrillation. Most of the computer-based automatic cardiac abnormality detection algorithms require accurate identification of ECG components such as QRS complexes in order to provide a reliable result. However, ECGs are often contaminated by noise and artifacts, especially if they are obtained using wearable sensors, therefore, identification of accurate QRS complexes often becomes challenging. Most of the existing denoising methods were validated using simulated noise added to a clean ECG signal and they did not consider authentically noisy ECG signals. Moreover, many of them are model-dependent and sampling-frequency dependent and require a large amount of computational time. This paper presents a novel ECG denoising technique using the variable frequency complex demodulation (VFCDM) algorithm, which considers noises from a variety of sources. We used the sub-band decomposition of the noise-contaminated ECG signals using VFCDM to remove the noise components so that better-quality ECGs could be reconstructed. An adaptive automated masking is proposed in order to preserve the QRS complexes while removing the unnecessary noise components. Finally, the ECG was reconstructed using a dynamic reconstruction rule based on automatic identification of the severity of the noise contamination. The ECG signal quality was further improved by removing baseline drift and smoothing via adaptive mean filtering. Evaluation results on the standard MIT-BIH Arrhythmia database suggest that the proposed denoising technique provides superior denoising performance compared to studies in the literature. Moreover, the proposed method was validated using real-life noise sources collected from the noise stress test database (NSTDB) and data from an armband ECG device which contains significant muscle artifacts. Results from both the wearable armband ECG data and NSTDB data suggest that the proposed denoising method provides significantly better performance in terms of accurate QRS complex detection and signal to noise ratio (SNR) improvement when compared to some of the recent existing denoising algorithms. The detailed qualitative and quantitative analysis demonstrated that the proposed denoising method has been robust in filtering varieties of noises present in the ECG. The QRS detection performance of the denoised armband ECG signals indicates that the proposed denoising method has the potential to increase the amount of usable armband ECG data, thus, the armband device with the proposed denoising method could be used for long term monitoring of atrial fibrillation. [ABSTRACT FROM AUTHOR]

Wireless communication systems with transmit and receive antenna arrays are studied when antenna selection is used. A case with very limited feedback of information from the receiver to the transmitter is considered, where the only information fed back is the selected subset of transmit antennas to be employed. It is shown that the optimum signaling, for largest ergodic capacity with antenna selection, is generally different from that which is optimum without antenna selection for some range of signal-to-noise ratios. [ABSTRACT FROM PUBLISHER]

We derive Cramer-Rao lower bounds (CRLBs) for the estimation of signal-to-noise ratio (SNR) of binary phase-shift keying (BPSK) and quaternary phase-shift keying (QPSK) modulated signals. The received signal is corrupted by additive white Gaussian noise (AWGN). The lower bounds are derived for non-data-aided estimation where the transmitted symbols are unknown at the receiver. The bounds are compared to those for data-aided estimations (known symbols at the receiver). It is shown that at low SNR there is a significant difference between the bounds for non-data-aided and data-aided estimations [ABSTRACT FROM PUBLISHER]

In this letter, we investigate the performance of generalized selection combining in channels impaired by generalized fading and generic noise with finite moments. In particular, we derive accurate high signal—to—noise ratio approximations for the bit and symbol error rates of linear modulation schemes, which offer significant insight into the impact of the number of selected diversity branches, the type of fading, and the type of noise. Our analysis is applicable to all practically relevant types of fading including Rayleigh, Rician, Nakagami—q, and Nakagami—m fading, all types of noise with finite moments including Gaussian noise, Gaussian mixture noise, generalized Gaussian noise, and co—channel interference, and non—identically distributed fading and noise across the diversity branches. Our results reveal that while performance always improves with increasing number of selected branches for identically distributed noise, this is not necessarily true for non—identically distributed noise. [ABSTRACT FROM PUBLISHER]

Coded orthogonal frequency division multiplexing (OFDM), like several other coded waveforms, exhibits inherent high range sidelobes after matched filtering. Consequently special processing at the receiver is required that can serve for sidelobe suppression in order to avoid target masking. However unmasking is not the only concern. It is crucial to evaluate the filtering scheme both in terms of sidelobe suppression capability and in terms of output signal-to-noise ratio (SNR). This last criterion is essential when aiming at detecting weaker reflections also. The theoretical performance of the reiterated filtering technique based on the linear minimum mean square error (LMMSE), as implemented in the adaptive pulse compression (APC) scheme, is derived and compared with the matched filter (MF). The analysis of the performance is done for a multi-target scenario where targets are close enough for the sidelobes of a target to interfere with the mainlobe of another target. Consequently the unmasking capabilities are relevant, but also output power figures. Complex-valued filter output peaks are also evaluated and compared with the MF output peaks. Moreover the performance of the method is evaluated for OFDM communication-encoded radar waveforms and compared with linear frequency modulated waveforms aiming at simultaneous use of the radar signal for both communication and radar. [ABSTRACT FROM AUTHOR]

The present article is focused in the area of control over networks. The main difference with classic control is that we deal with an explicit communication channel model in the feedback control structure. The channel model is modeled as to have limited bandwidth and additive colored Gaussian noise. This allows us to study the interaction between the control and communication goals. We first briefly revisit the assumption behind the present work and formally define the problem at hand. We then review its solution in the form of the Signal-to-Noise Ratio (SNR) fundamental limitation for stabilizability result. We extend the stabilizability result to include the following performance scenarios: closed-loop arbitrary pole assignment, robustness, set point tracking and the effect of channel input quantization. We finally conclude the present paper by studying the capacity resulting from these performance limitations for the case of a memoryless additive white Gaussian noise (AWGN) channel. [ABSTRACT FROM PUBLISHER]

This paper proposes a new soft-reliability information-based post-Viterbi processor with advanced noise-robustness for reducing probability of miss-correction and no correction of a conventional soft-reliability-based post-Viterbi processor. Among all likely error starting positions for prescribed error events, the two schemes are equal to attempt to correct error-type corresponding to a position with minimum one only if there exist positions where a soft-reliability estimate is negative. The main difference between the two schemes is how they acquire the softreliability estimate. The soft-reliability estimate of the new scheme is obtained through the elimination of the noisesensitive component from the log-likelihood ratio of the posteriori probabilities, which is the soft-reliability estimate of conventional scheme. As a result, the new scheme is based on more reliable soft-reliability information so reducing the probability of miss-correction and no correction. [ABSTRACT FROM AUTHOR]

Cooperative communications can significantly enhance the performance of wireless systems by exploiting the inherent spatial diversity gains. In this work, a decode-and-forward cooperative cellular system with spatial random users is investigated. Under a realistic channel model including path loss, shadowing and multipath fading, the users are selected as relays depending on their instantaneous SNR so that error propagation caused by detection errors at the relays can be mitigated. The locations of users are modeled as random point processes. Based on the theory of point processes, an analytic approach to system performance is developed to accommodate the random location of users as well as the underlying channel. The locations of the selected relays are investigated and the outage performance averaging over all possible user locations is analyzed. The accuracy of the analytical results is verified by Monte-Carlo simulations. Various issues, such as power allocation, are also investigated using the numerical results. [ABSTRACT FROM PUBLISHER]

In this paper, we consider the full-duplex and half-duplex Gaussian relay channels where the noises at the relay and destination are arbitrarily correlated. We first derive the capacity upper bound and the achievable rates with three existing schemes: Decode-and-Forward (DF), Compress-and-Forward (CF), and Amplify-and-Forward (AF). We present two capacity results under specific noise correlation coefficients, one being achieved by DF and the other being achieved by direct link transmission (or a special case of CF). The channel for the former capacity result is equivalent to the traditional Gaussian degraded relay channel and the latter corresponds to the Gaussian reversely-degraded relay channel. For CF and AF schemes, we show that their achievable rates are strictly decreasing functions of the correlation coefficient when the correlation coefficient is negative. Moreover, when the noise correlation coefficient is positive, the CF achievable rate may also outperform the independent-noise case if the noise correlation coefficient is within a certain range. Through numerical comparisons under different channel settings, we observe that although DF completely disregards the noise correlation while the other two can potentially exploit such extra information, none of the three relay schemes always outperforms the others over different correlation coefficients. Moreover, the exploitation of noise correlation by CF and AF accrues more benefit when the source-relay link is weak. This paper also considers the optimal power allocation problem under the correlated-noise channel setting. With individual power constraints at the relay and the source, it is shown that the relay should use all its available power to maximize the achievable rates under any correlation coefficient. With a total power constraint across the source and the relay, the achievable rates are proved to be concave functions over the power allocation factor for AF and CF under full-duplex mode, where the closed-form power allocation strategy is derived. [ABSTRACT FROM PUBLISHER]

We propose a quantizer design method for practical half-duplex estimate-and-forward (EF) relaying. First, we identify the regime in which EF relaying yields substantial gains - where the SNR is low and the relay-destination link is strong. Then we discover design simplifications that reduce complexity with little loss in the above regime. For relay quantizer design, we first consider mean-squared distortion minimization. To illustrate the unsuitability of the approach, we present an example with AWGN links and a BPSK source where the quantizer with worst mean squared distortion in a given set maximizes achievable rate. A distortion-minimizing quantizer attempts to preserve the received signal at the relay. The quantizer should instead preserve source information. In information theoretical terms, the quantizer should maximize the mutual information between the source transmission and the quantizer output conditioned on the side information at the destination subject to a rate constraint. The above conclusion, derived from information theoretical principles, is then translated to a quantizer design method for the low SNR regime. Using LDPC codes of blocklength 100000, BPSK modulation, and quantizers designed using the proposed criterion, we observe performance less than a decibel away from the achievable rate at a BER of 10^-4. [ABSTRACT FROM AUTHOR]