Sharif Digital Repository

MIMO radar is the next generation radar which transmits arbitrary waveforms at each one of its apertures. It has been shown that design of waveforms for MIMO radars in order to synthesize a desired spatial beampattern is mapped into a waveform correlation matrix (R) design in the narrowband case. Searching for desired R has been modeled as a convex optimization problem which demands considerable processing power. There are also some close form solutions for special cases like rectangular beampatterns. Here we deal with the problem from a matrix eigenvalue theory perspective and show how close form solutions can be found for more general cases relaxing high computational power demand. Our... 

In this paper, based on a successively accuracy-increasing approximation of the ℓ0 norm, we propose a new algorithm for recovery of sparse vectors from underdetermined measurements. The approximations are realized with a certain class of concave functions that aggressively induce sparsity and their closeness to the ℓ0 norm can be controlled. We prove that the series of the approximations asymptotically coincides with the ℓ1 and ℓ0 norms when the approximation accuracy changes from the worst fitting to the best fitting. When measurements are noise-free, an optimization scheme is proposed that leads to a number of weighted ℓ1 minimization programs, whereas, in the presence of noise, we propose... 

This paper has presented a novel discriminative parameters calibration approach based on the Model Distance Maximizing (MDM) to improve the performance of our previous proposed robustness method named spectral subtraction (SS) in likelihoodmaximizing framework. In the previous work, for adjusting the spectral over-subtraction factor of SS, conventional ML approach is used that only utilizes the true model without considering other confused models. This makes it very probably to reach a suboptimal solution. While in MDM, by maximizing the dissimilarities among models, the performance of our speech recognizer-based spectral subtraction method could be further improved. Experimental results... 

Electricity load forecasting plays an important role for optimal power system operation. Accordingly, short term load forecast (STLF) is also becoming an important task by researchers to tackle the mentioned problem. As a consequence of the highly non-smooth and volatile trend of the load time series specially in building levels, its STLF is even a more complex procedure than that of a power system. For this purpose, in this paper we proposed a new prediction model based on a new feature selection algorithm and hybrid forecast engine of enhanced version of empirical mode decomposition named sliding window EMD bundled with an intelligent algorithm. The proposed forecast engine is combined... 

In this paper we consider a cooperative communication systems over Rayleigh fading channels. The system utilizes a combination of incremental and selective decode-and-forward (ISDF) relaying protocols. The symbol error rate (SER) of M-PSK modulation for the ISDF protocol is derived. Using an approximation of the SER expression, the optimal power allocation is investigated. In order to reduce the complexity of the receiver, we used a modified version of the ISDF protocol which does not use the storage or retransmission of the first phase signal. We also derived optimal power allocation coefficient for modified ISDF. It has been noted that for the optimal power allocation in the ISDF protocol,... 

In this paper, we have proposed an efficient and effective nonlinear feature domain noise suppression algorithm, motivated by the minimum mean square error (MMSE) optimization criterion. A Multi Layer Perceptron (MLP) neural network in the log spectral domain has been employed to minimize the difference between noisy and clean speech. By using this method, as a pre-processing stage of a speech recognition system, the recognition rate in noisy environments has been improved. We extended the application ofthe system to different environments with different noises without retraining HMMmodel. We trained the feature extraction stage with a small portion of noisy data which was created by... 

The current state of device-to-device (D2D) communication in the presence of cellular network addresses two major challenges of interference as well as throughput inadequacy. Specifically, a D2D communication underlaying fractional frequency reuse (FFR) cellular network exhibits rather high interferences due to higher occurrence of band crossing within a shared spectrum. However, due to the considerable impact of D2D communications on spectral efficiency and system capacity, the remedy for those issues may include efficient techniques of interference mitigation and average spectral efficiency maximization. In this paper, we propose a resource block (RB) allocation scheme to reduce the... 

In this paper, an adaptive channel estimation algorithm is proposed for the multi-user robust relay beamforming problem. We propose a norm-bounded channel uncertainty model for all of the channels. We employ the Extended Kalman Filter (EKF) and the Unscented Kalman Filter (UKF) for joint estimation of channel coefficients and beamforming weights, and propose a Markov model for source-relay and relay-destination channels as well as the beamforming weights in the relays. The channel coefficients and bemforming weights are shown to be well-estimated in order to minimize the total relays power transmission subject to worst-case signal to interference and noise ratio (SINR) criterion at each... 

Datapath designs that perform polynomial computations over Z 2n are used in many applications such as computer graphics and digital signal processing domains. As the market of such applications continues to grow, improvements in high-level synthesis and optimization techniques for multivariate polynomials have become really challenging. This paper presents an efficient algorithm for optimizing the implementation of a multivariate polynomial over Z2n in terms of the number of multipliers and adders. This approach makes use of promising heuristics to extract more complex common sub-expressions from the polynomial compared to the conventional methods. The proposed algorithm also utilizes a... 

In this paper a new iterative method is used to convert analog signals to digital (A/D) using sigma delta modulator (SDM). If intelligent reconstruction technique is used for decoding, either signals with higher bandwidth can be digitized or simpler circuitry can be utilized. An optimal family of SDM has recently been devised in order to improve performance of A/D converters. In this work, we improve performance of A/D converters even more, by combining this optimal family of SDM with iterative methods  

A method for two dimensional position finding of stationary targets whose bearing measurements suffers from indeterminable bias and random noise has been proposed. The algorithm uses convex optimization to minimize an error function which has been calculated based on circular as well as linear loci of error. Taking into account a number of observations, certain modifications have been applied to the initial crude method so as to arrive at a faster, more accurate method. Simulation results of the method illustrate up to 30% increase in accuracy compared with the well-known least square filter  

In this study, the authors optimise the outage probability of amplify and forward incremental relaying (IR) scheme using two different power allocation methods in the presence of channel estimation errors. The authors find the outage probability of IR scheme and minimise it subject to traditional power (TP) constraint in which the sum of nodes' powers is fixed and outage-dependent power (ODP) constraint which is compatible with the physical concept of IR and takes into account the quality of the direct path in the optimisation problem. The authors provide closed-form expressions to allocate power to pilot and data symbols of both the source and the relay. Although, their analysis uses high... 

Autocorrelation receiver (AcR) is usually used as the general receiver for transmitted reference (TR) communication systems on a quite intuitive basis. In this paper, we apply the principle of statistical invariance to obtain the optimum TR receiver on a decision-theoretic basis, and it is shown that the autocorrelation receiver is optimal only in a special case. Performance of the optimum receiver and the suboptimum AcR for some important modulation schemes is also evaluated. The results imply that allocating a part of the transmitted energy and bandwidth to reference pulses would not help improve the performance of the system and the optimal performance might be achieved via much simpler... 

In this paper, we investigate the problem of designing compact-support interpolation kernels for a given class of signals. By using calculus of variations, we simplify the optimization problem from an nonlinear infinite dimensional problem to a linear finite dimensional case, and then find the optimum compact-support function that best approximates a given filter in the least square sense (ℓ 2 norm). The benefit of compact-support interpolants is the low computational complexity in the interpolation process while the optimum compact-support interpolant guarantees the highest achievable signal-to-noise ratio (SNR). Our simulation results confirm the superior performance of the proposed kernel... 

Waveform design for Target identification and classification in MIMO radar systems has been studied in several recent works. While the previous works considered signal independent noise and found optimal signals, here we extend the results to the case where clutter is also present and then we will find the optimum waveform for MMSE estimator. Choosing optimal waveform for MMSE estimator leads to the Semidefinite programming (SDP) problem, a convex optimization problem which can be efficiently solved through numerical methods. Explicit solution is developed for this SDP problem in two cases .In the first case, target and clutter covariance matrices are jointly diagonalizable and in the second... 

In this paper, we consider transmission of a Gaussian source over a Gaussian channel under bandwidth compression in the presence of interference known only to the transmitter. We study hybrid digital-analog (HDA) joint source-channel coding schemes and propose two novel coding schemes that achieve the optimal mean-squared error (MSE) distortion. This can be viewed as the extension of results by Wilson et al. [1], originally proposed for sending a Gaussian source over a Gaussian channel in two cases: 1) Matched bandwidth with known interference only at the transmitter, 2) bandwidth compression where there is no interference in the channel. The proposed HDA codes can cancel the interference of... 

Auto-Exposure detection is a key feature in digital cameras and smart-phones. The image information can be used to detect scene over and under exposure passively. This paper introduces an effective optimal exposure detection function based on joint probability density function of the pixels in the scene  

Waveform design for target identification and classification in MIMO radar systems has been studied in several recent works. While the previous works assumed that the noise was independent of the transmission signals, here we extend the results to the signal dependent noise (clutter). We consider two scenarios. In the first scenario it is assumed that different transmit antennas see uncorrelated aspects of the target. In the second scenario, we consider the correlated target. As clutter is dependent to signal, target estimation error cannot vanish only by increasing the transmission power. It can be shown that in the second scenario, MIMO radar receiver can nullify the clutter subspace.... 

Waveform design for Target identification and classification in MIMO radar systems has been studied in several recent works. While the previous works considered signal independent noise, here we extend the results to the case where signal-dependent noise, clutter, is also present and then we find the optimum waveform for several estimators differing in the assumptions on the given statistics. Computing the optimal waveforms for MMSE estimator leads to the Semi-definite programming (SDP) problem. Finding the optimal transmit signals for CSLS estimator results in a minimax eigenvalue problem. Finally it is shown that equal power waveforms are the best transmit signals for the SLS estimator.... 

In this paper, new sequences (λn,ρn) of capacity achieving low-density parity-check (LDPC) code ensembles over the binary erasure channel (BEC) is introduced. These sequences include the existing sequences by Shokrollahi as a special case. For a fixed code rate R, in the set of proposed sequences, Shokrollahi's sequences are superior to the rest of the set in that for any given value of n, their threshold is closer to the capacity upper bound 1 - R. For any given δ, 0 < δ < 1 - R, however, there are infinitely many sequences in the set that are superior to Shokrollahi's sequences in that for each of them, there exists an integer number n0, such that for any n > n0, the sequence (λn, ρn)...