Sharif Digital Repository

In this paper, we propose a novel method for demodulating Pulse Position Modulation (PPM) signals based on Reed-Solomon decoding algorithm. It is shown that the proposed technique outperforms the conventional demodulating method base on Reed-Solomon algorithm in case that the PPM signals are corrupted by Additive White Gaussian Noise (AWGN). © Springer-Verlag 2004  

In this paper, we consider the problem of transmitting a Bi-variate Gaussian source S = (S1, S2) over an average-power-limited additive White Gaussian noise (AWGN) channel. The receiver wants to estimate both S1 and S2. We propose a new Hybrid Digital Analog (HDA) joint source-channel coding scheme and obtain its achievable distortion region. For comparison, we also obtain an outer bound for the set of all achievable distortion pairs  

This paper analyzes the problem of transmitting a Gaussian source over an additive white Gaussian noise (AWGN) channel in the presence of an unknown interference. The goal is to estimate the source at the receiver with minimum mean squared error (MMSE) distortion. We introduce a lattice-based coding scheme and calculate its achievable distortion. If the interference distribution and the lattice voronoi region satisfy some conditions, the effect of interference can be reduced  

Recent studies have revealed that spectrum congestion is due to the inefficient usage of spectrum against the availability. Cognitive radio is viewed as an approach for improving the utilisation of radio spectrum. The spectrally encoded (spread-time) code-division multiple access (SE-CDMA) technique (which is regarded as the dual of spread spectrum CDMA) is considered and its performance in cognitive radio networks is studied. In cognitive network spectrum, overlay and underlay techniques are employed to enable the primary and secondary users to coexist while improving the overall spectrum efficiency. It is shown that SE-CDMA provides considerable flexibility to design overlay and underlay... 

This paper studies denoising of images contaminated with additive white Gaussian noise (AWGN). In recent years, clustering-based methods have shown promising performances. In this paper we show that low-rank subspace clustering provides a suitable clustering problem that minimizes the lower bound on the MSE of the denoising, which is optimum for Gaussian noise. Solving the corresponding clustering problem is not easy. We study some global and local sub-optimal solutions already presented in the literature and show that those that solve a better approximation of our problem result in better performances. A simple image denoising method based on dictionary learning using the idea of... 

In this brief, a new blind spectrum sensing method is proposed based on frequency comparison using a phase frequency detector (PFD). The PFD output patterns are utilized in a way to sense the spectrum with no knowledge of incoming signals, noise, or channel parameters. The detection and false alarm error probabilities are analytically calculated for additive white Gaussian noise and sine-wave input and are simulated for different inputs. It is shown that the required detection and false alarm probabilities can be achieved by changing the system parameters. The results show that the proposed method has lower complexity and outperforms the previous single-antenna blind method over flat fading... 

In this paper we propose a new algorithm for learning low-dimensional linear subspaces. Our proposed algorithm performs by sequentially finding some low-dimensional subspaces on which a set of training data lies. Each subspace is found in such a way that the number of signals lying on (or near to) it is maximized. Once we found a subset of the training data that is sufficiently close to a subspace, then we omit these signals from the set of training signals and repeat the procedure for the remaining signals until all training signals are assigned to a subspace. This data reduction procedure results in a significant improvement to the runtime of our algorithm. We then propose a robust version... 

In this paper, we propose a modified joint source-channel coding (JSCC) scheme on the transmission of an analog Gaussian source over an additive white Gaussian noise (AWGN) channel in the presence of an interference, correlated with the source. This setting naturally generalizes the problem of sending a single Gaussian source over an AWGN channel, in the case of bandwidth-matched, and with uncorrelated interference in which separation-based scheme with Costa coding is optimal. We analyze the modifeied scheme to obtain achievable (mean-squared error) distortion-power tradeoff. For comparison, we also obtain a new outer bound for the achievable distortion-power tradeoff. Using numerical... 

The authors consider the problem of broadcast-relay-networks with two cooperative relays. There are a transmitter, two relays and two receivers in the network. The message of the transmitter intended to the receivers has common and private parts. The relays fully cooperate with each other and with the transmitter to send the common part of the message, whereas the private parts of the message are sent through the direct links between the transmitter and receivers. The authors found an achievable rate region for this network by using the symmetric relaying strategy. In this strategy, each relay completely decodes the message of other relay. In the proof the authors took advantage of regular... 

In this paper, we consider the generalized point-to-point Additive White Gaussian Noise (AWGN) channel with state: The State-Dependent Gaussian Interference Channel (SD-GIC) with a common message in which two senders transmit a common message to two receivers. Transmitter 1 knows only message μ1 while transmitter 2 in addition μ1 also knows the channel state sequence non-causally. In this paper, we consider the strong interference case where the channel state has unbounded variance. First, we show that a scheme based on Gelfand-Pinsker coding cannot achieve the capacity within a constant gap for channel gains smaller than unity. In contrast, we propose a lattice-based transmission scheme... 

In this study, the authors introduce an efficient secure channel coding (joint cryptography-channel coding) scheme based on Latin square low-density lattice codes (Latin square LDLCs) over unconstrained power additive white Gaussian noise channel. They benefit the properties of Latin square LDLCs to dramatically reduce the key size of the proposed scheme while having an acceptable level of security compared with previous similar schemes. To reduce the key size, they consider two approaches: (i) saving the generating sequence of parity-check matrix of used Latin square LDLC as the part of secret key set; (ii) employing the Hermite normal form of the generator matrix of used Latin square LDLC... 

In this paper a sub-optimal control technique is proposed for a linear Gaussian system with a few distributed interacting sub-systems. Controller of each sub-system has only access to its own measurement and a noisy version of measurement and control vectors of other sub-systems that are communicated through an Additive White Gaussian Noise (AWGN) communication network. The power to be allocated to each transmitter antenna is calculated so that the received signal is the transmitted signal plus additive white Gaussian noise. Under some conditions it is shown that the proposed sub-optimal control technique results in bounded mean square stability. The satisfactory performance of the proposed... 

In this paper we address the problem of learning low-dimensional subspaces using a given set of training data. To this aim, we propose an algorithm that performs by sequentially fitting a number of low-dimensional subspaces to the training data. Once we found a subset of the training data that is sufficiently near a fitted subspace, we omit these signals from the set of training signals and repeat the same procedure for the remaining signals until all training signals are assigned to a subspace. We then propose a robust version of the algorithm to address the situation in which the training signals are contaminated by additive white Gaussian noise (AWGN). Experimental results on both... 

We consider transmission of a Gaussian source over a Gaussian channel under bandwidth compression in the presence of an interference known only to the transmitter. We study hybrid digital-analog (HDA) joint source-channel coding schemes and propose two novel layered coding schemes that achieve the optimal mean-squared error (MSE) distortion. This can be viewed as the extension of results by Wilson ["Joint Source Channel Coding With Side Information Using Hybrid Digital Analog Codes," IEEE Trans. Inf. Theory, vol. 56, no. 10, pp. 4922-2940, Oct. 2010], originally proposed for sending a Gaussian source over a Gaussian channel in two cases: 1) Matched bandwidth with known interference only at... 

In this study the authors present an in-depth study, analysis and discussion on maximum likelihood (ML)-based receiver for a typical spectrally encoded spread-time CDMA in the presence of multiple narrowband interference (NBI) signals in an additive white Gaussian noise channel. Furthermore, the authors demonstrate that by combining useful properties of ML-based receiver and three-level codes, that is, codes with values of -1, 0, +1, the authors can introduce a new strategy in which superior performance with respect to previous receiver structure based on two-level codes, that is, codes with values of -1, +1, can be attained. With the help of an example, the authors drive, first, the... 

In this study, kernel least mean square (KLMS) algorithm with fractionally spaced equalizing structure is proposed for electrical compensation of chromatic dispersion (CD) and nonlinear phase noise (NLPN) in a dual polarization optical communications system with coherent detection. We consider single mode fiber channel. At the receiver, the additive optical noise is represented as additive white Gaussian noise. Phase modification is utilized at high signal powers to maintain the validity of Gaussian model of noise. We consider QAM and PSK modulations and evaluate the performance of the proposed method in terms of error rate, phase error, and error vector magnitude (EVM). The results are... 

The authors present an improved achievable rate region for two-pair bidirectional Gaussian relay networks based on successive compute-and-forward method. In these networks, one relay helps in the communication between two pairs of users. In their proposed scheme, the authors use nested lattice codes for encoding the messages at the users, and Gaussian random codes for the encoding at the relay. They use the successive compute-and-forward strategy to decode two integer linear combinations of the lattice codewords in the uplink, and successive interference cancellation for decoding the Gaussian codewords in the downlink. The downlink channel can be considered as a broadcast channel with two... 

The nonlinear characteristic of an laser diode, LD, impacts on the performance of optical wireless systems using OFDM(orthogonal frequency division multiplexing). First, the influence of the nonlinear characteristic on bit-error performance is analyzed using a high power LD (LML-808.7B-XX). Next, the paper proposes a pre-distorter to compensate the nonlinearities. Finally, the coherent optical OFDM (CO-OFDM) system is considered and the performance without linearization and after linearization is analyzed via simulations in an AWGN (additive white Gaussian noise) environment. It is shown that LD nonlinearity can significantly degrade the performance. However, it is demonstrated that this... 

In this paper, the optimal sampling strategies (uniform or nonuniform) and distortion tradeoffs for Gaussian bandlimited periodic signals with additive white Gaussian noise are studied. Our emphasis is on characterizing the optimal sampling locations as well as the optimal pre-sampling filter to minimize the reconstruction distortion. We first show that to achieve the optimal distortion, no pre-sampling filter is necessary for any arbitrary sampling rate. Then, we provide a complete characterization of optimal distortion for low and high sampling rates (with respect to the signal bandwidth). We also provide bounds on the reconstruction distortion for rates in the intermediate region. It is... 

We investigate the performance of wavelet shrinkage methods for the denoising of symmetric- α -stable (S αS) self-similar stochastic processes corrupted by additive white Gaussian noise (AWGN), where α is tied to the sparsity of the process. The wavelet transform is assumed to be orthonormal and the shrinkage function minimizes the mean-square approximation error (MMSE estimator). We derive the corresponding formula for the expected value of the averaged estimation error. We show that the predicted MMSE is a monotone function of a simple criterion that depends on the wavelet and the statistical parameters of the process. Using the calculus of variations, we then optimize this criterion to...