Sharif Digital Repository

In this paper, a diffusion-based molecular communication channel between two nano-machines is considered. The effect of the amount of memory on performance is characterized, and a simple memory-limited decoder is proposed; its performance is shown to be close to that of the best possible decoder (without any restrictions on the computational complexity or its functional form), using genie-aided upper bounds. This effect is adapted to the case of Molecular Concentration Shift Keying; it is shown that a four-bit memory achieves nearly the same performance as infinite memory for all of the examples considered. A general class of threshold decoders is considered and shown to be suboptimal for a... 

The presence of the desired signal (DS) in the training snapshots makes the adaptive beamformer sensitive to any steering vector mismatch and dramatically reduces the convergence rate. The objective of the present study is to propose a new adaptive beamformer which is robust against direction-of-arrival (DOA) mismatch and its convergence rate is not sensitive to the presence of the DS. This method is applicable to the arrays with specific structure such as the linear array. Our approach is based on the DS elimination from the training snapshots and the sub-array beamforming technique. To accomplish this goal, a blocking matrix which converts the primary data to the DS-free data is... 

In this study, an efficient handover algorithm based on the received signal strength (RSS) prediction is presented for two-tier macro-femtocell networks in which, because of the fading effects of channel and short coverage range of femtocells, ping-pong handovers may take place. In the proposed approach, first each mobile station (MS) uses the recursive least square algorithm for predicting the RSS from the candidate base stations (BSs) including both femtocell and macrocell BSs. Then, according to the predicted RSS values, several future values of signal-to-interference plus noise ratio (SINR) are calculated. Afterwards, the candidate list of BSs is pruned according to the estimated future... 

The presence of the desired signal (DS) in the training snapshots makes the adaptive beamformer sensitive to any steering vector mismatch and dramatically reduces the convergence rate. Even the performance of the most of the existing robust adaptive beamformers is degraded when the signal-to-noise ratio (SNR) is increased. In this study, a high converging rate robust adaptive beamformer is proposed. This method is a promoted eigenspace-based beamformer. In this paper, a new signal-plus-interferences (SPI) covariance matrix estimator is proposed. The subspace of the ideal SPI covariance matrices is exploited and the estimated covariance matrix is projected into this subspace. This projection... 

Diffusion weighted imaging (DWI) is a non-invasive method for investigating the brain white matter structure. It can be used to evaluate fiber bundles in the brain. However, clinical acquisitions are often low resolution. This paper proposes a method for improving the resolution using sparse representation. In this method a non-diffusion weighted image (bO) is utilized to learn the patches and then diffusion weighted images are reconstructed based on the trained dictionary. Our method is compared with bilinear, nearest neighbor and bicubic interpolation methods. The proposed method shows improvement in terms of Peak Signal-to-Noise Ratio (PSNR) and Structural SIMilarity (SSIM)  

In this paper, we study transmission of a memoryless Laplacian source over three types of channels: additive white Laplacian noise (AWLN), additive white Gaussian noise (AWGN), and slow flat-fading Rayleigh channels under both bandwidth compression and bandwidth expansion. For this purpose, we analyze two well-known hybrid digital-analog (HDA) joint source-channel coding schemes for bandwidth compression and one for bandwidth expansion. Then we obtain achievable (absolute-error) distortion regions of the HDA schemes for the matched signal-to-noise ratio (SNR) case as well as the mismatched SNR scenario. Using numerical examples, it is shown that these schemes can achieve a distortion very... 

Response-only identification of civil structureshas attracted much attention during recent years, as input excitations are rarely measurable for ambient vibrations. Although various techniques have been developed by which identification can be carried out using ambient responses, these techniques are generally not applicable to non-stationary excitations that structures experience during moderate-to-severe earthquakes. Recently, the authors proposed a new response-only modal identification method that is applicable to strong shaking data. This new method is highly attractive for cases in which the true input motions are unavailable. For example, when soil-structure interaction effects are... 

The compute-and-forward (CMF) method has shown a great promise as an innovative approach to exploit interference towards achieving higher network throughput. The CMF was primarily introduced by means of information theory tools. Although there have been some recent works discussing different aspects of efficient and practical implementation of CMF, there are still some issues that are not covered. In this study, the authors first introduce a method to decrease the implementation complexity of the CMF method. They then evaluate the exact outage probability of the authors proposed simplified CMF scheme, and hereby provide an upper bound on the outage probability of the optimum CMF in all... 

Deterministic approach of [1] models the interaction between the bits that are received at the same signal level by the modulo 2 sum of the bits where the carry-overs that would happen with real addition are ignored. By this model in a multi-user setting, the receiver can distinguish most significant bits (MSBs) of the stronger user without any noise. A faithful implementation of the deterministic model requires one to 'neutralize interference' from previous carry over digits. This paper proposes a new implementation of 'interference neutralization' [2] using structured lattice codes. We first present our implementation strategy and then, as an application, apply this strategy to a symmetric... 

In this paper, a novel multiple antenna, high-resolution eigenvalue-based spectrum sensing algorithm based on the FFT of the received signal is introduced. The proposed platform overcomes the SNR wall problem in the conventional energy detection (ED) algorithm, enabling the detection of the weak signals at -10 dB SNR. Moreover, the utilization of FFT for the input signal channelization provides a simple, low-power design for a high-resolution spectrum sensing regime. A real-time, low-area, and low-power VLSI architecture is also developed for the algorithm, which is implemented in a 0.18 μm CMOS technology. The implemented design is the first eigenvalue-based detection (EBD) architecture... 

Signal to Noise and Distortion Ratio (SNDR) is widely chosen for dynamic characterization of ADC. For pipelined ADC in which the inner circuits' errors accumulate at the output, analysis of the origins of SNDR and its characterization can be very hard. However, due to a relationship between maximum INL of ADC and the distortion in its output codes, SNDR can be derived as a function of maximum INL value and its position in output codes. Utilizing this relationship, this paper develops two methods for SNDR enhancement that do not cost much power. The 50k sampled Monte-Carlo simulation in the behavioral level indicates 75% increase in the possibility of having SNDR > 60db just by utilizing... 

This paper presents a modified sensor-based online method for mobile robot navigation generating paths in dynamic environments. The core of the navigation algorithm is based on the velocity obstacle avoidance method and the guidance-based tracking algorithm. A fuzzy decision maker is designed to combine the two mentioned algorithms intelligently. Hence the robot will be able to decide intelligently in various situations when facing the moving obstacles and moving target. A noble noise cancellation algorithm using Neural Network is designed to navigate the robot in an uncertain dynamic environment safely. The results show that the robot can track a moving target while maneuvering safely in... 

We have recently proposed a correlated model to provide a Gaussian mixture representation of the cardiovascular signals, with promising results in identifying rhythm disturbances. The approach provides a transformation of the data into a set of integrable Gaussians distributed over time. Looking into the model from a new joint modeling perspective, it is capable of assembling a filtered estimation, and can be used to derive temporal information of the waveforms. In this paper, we present a step-by-step derivation of the joint model putting correlation assumptions together to conclude a minimal joint description for a pair of ECG-ABP signals. We then probe novel applications of this model,... 

In this paper, we present a quality-of-transmission (QoT) aware dynamic routing, modulation level, and spectrum assignment scheme referred to as QoT-aware RSA. The proposed QoT-aware RSA has three stages: path computation with QoT-aware modulation level assignment, path selection, and spectrum assignment. Two schemes are presented in the path computation stage namely, modified Dijkstra and K-shortest-path algorithms. A closed-form expression is derived to model the fiber nonlinearity effects and the impairments of intermediate routers. This expression is utilized to estimate the network dependent QoT and the transmission reach of the modulation levels. We propose to select the best path in... 

In this paper, we introduce a model-based Bayesian denoising framework for phonocardiogram (PCG) signals. The denoising framework is founded on a new dynamical model for PCG, which is capable of generating realistic synthetic PCG signals. The introduced dynamical model is based on PCG morphology and is inspired by electrocardiogram (ECG) dynamical model proposed by McSharry et al. and can represent various morphologies of normal PCG signals. The extended Kalman smoother (EKS) is the Bayesian filter that is used in this study. In order to facilitate the adaptation of the denoising framework to each input PCG signal, the parameters are selected automatically from the input signal itself. This... 

The notions of asymptotic eigenvectors and asymptotic eigenvalues are defined. Based on these notions a special probability rule for pattern selection in a Hopfield type dynamics is introduced. The underlying network is considered to be a d-regular graph, where d is an integer denoting the number of nodes connected to each neuron. It is shown that as far as the degree d is less than a critical value dc, the number of stored patterns with m μ = O(1) can be much larger than that in a standard recurrent network with Bernouill random patterns. As observed in [4] the probability rule we study here turns out to be related to the spontaneous activity of the network. So our result might be an... 

Hidden Markov model (HMM)-based minimum mean square error speech enhancement method in Mel-frequency domain is focused on and a parallel cepstral and spectral (PCS) modeling is proposed. Both Mel-frequency spectral (MFS) and Mel-frequency cepstral (MFC) features are studied and experimented for speech enhancement. To estimate clean speech waveform from a noisy signal, an inversion from the Mel-frequency domain to the spectral domain is required which introduces distortion artifacts in the spectrum estimation and the filtering. To reduce the corrupting effects of the inversion, the PCS modeling is proposed. This method performs concurrent modeling in both cepstral and magnitude spectral... 

In this work, we study the performance of polar codes for lossy compression of a Gaussian source with a side information at decoder; known as the quadratic-Gaussian Wyner-Ziv problem. First we extend the binary polar codes to q-ary for the Wyner-Ziv problem. We show that the nested q- Ary polar codes are optimal for this case. Then we present two polar coding schemes for the Gaussian Wyner-Ziv problem. In the first scheme, we achieve a rate above the Wyner-Ziv rate-distortion function with a gap of 0.5 bits compared with the optimal rate. This scheme utilizes a successive cancellation decoder and is optimal in weak side-information cases when the decoder side-information noise variance is... 

In this paper, we study a general additive state-dependent Gaussian interference channel (ASD-GIC) where we consider two-user interference channel with two independent states known non-causally at both transmitters, but unknown to either of the receivers. A special case, where there is a common additive state is studied in [1], [2], where it is shown that the gap between the achievable symmetric rate and the upper bound is less than 1 /4 bits for the strong interference case. Here, we also consider the case where interference link gains satisfy a12 ≥ N1/ N2 and a 21 ≥ N2/ N1 (Ni is the channel noise variance) and each channel state has an unbounded variance [3], which is referred to as the... 

The noise exists in almost all environments such as cellular mobile telephone systems. Various types of noise can be introduced such as speech additive noise which is the main factor of degradation in perceived speech quality. At some applications for example at the receiver of a telecommunication system, the direct value of interfering noise is not available and there is just access to noisy speech. In these cases the noise cannot be cancelled totally but it may be possible to reduce the noise in a sensible way by utilizing the statistics of the noise and speech signal. In this paper the proposed method for noise reduction is Bayesian recursive state-space Kalman filter, which is a method...