Venceslav Kafedziski

On the correlation and scattering functions of the WSSUS channel for mobile communications

The wide-sense stationary-uncorrelated scattering (WSSUS) channel model is a commonly employed model for the multipath channel experienced in mobile communications. The second order statistics of these channels are described by the delay cross-power density /spl phi//sub h/(/spl tau/;/spl Delta/t) or by its /spl Delta/t-Fourier transform, the scattering function S/sub h/(/spl tau/;/spl lambda/). This paper presents an analysis of the delay cross-power density and scattering functions for mobile communications channels. We assume an arbitrary spatially uncorrelated scattering (US) field with arbitrary propagation-loss factors. Our first result is a general integral expression for /spl phi//sub h/(/spl tau/;/spl Delta/t) that holds with both transmitter and receiver being mobile. We then derive more detailed results for the case of a stationary base station. We derive an infinite Bessel series for /spl phi//sub h/(/spl tau/;/spl Delta/t) and a closed-form expression for S/sub h/(/spl tau/; /spl lambda/). These results generalize the well-known classical approximation for the time-correlation function /spl phi/~/sub h/(/spl Delta/t)=/sup def//spl int//spl phi//sub h/(/spl tau/;/spl Delta/t)d/spl tau//spl ap/ J/sub 0/(2/spl pi//spl lambda//sub m//spl Delta/t), which corresponds to the zeroth term of our Bessel series.

Vector quantization over Gaussian channels with memory

We consider the problem of transmission of a vector quantized Markov source over channels with memory. A maximum a posteriori (MAP) symbol-by-symbol algorithm is used to obtain a soft decision VQ decoder which approximates the minimum mean-squared error estimate of the source vectors. This algorithm also accounts for the residual redundancy left at the vector quantizer output. The results obtained using this approach are compared to the results obtained by using a hard decision VQ decoder. Also, this decoder is used in conjunction with a channel optimized vector quantizer (COVQ), which is designed using a nonrecursive symbol by symbol detector instead of the optimal MAP symbol by symbol detector, thus reducing the dimensionality considerably. We also introduce simplified design procedure, obtained by determining the channel transition matrix of an equivalent discrete memoryless channel, and then applying well known COVQ procedures for discrete memoryless channels. We find that the soft decision decoder considerably improves reconstruction fidelity at low channel SNRs, and that COVQ further improves the performance.

Compressive sampling with chaotic dynamical systems

We investigate the possibility of using different chaotic sequences to construct measurement matrices in compressive sampling. In particular, we consider sequences generated by Chua, Lorenz and Rössler dynamical systems and investigate the accuracy of reconstruction when using each of them to construct measurement matrices. Chua and Lorenz sequences appear to be suitable to construct measurement matrices. We compare the recovery rate of the original sequence with that obtained by using Gaussian, Bernoulli and uniformly distributed random measurement matrices. We also investigate the impact of correlation on the recovery rate. It appears that correlation does not influence the probability of exact reconstruction significantly.

Estimation of Sparse Time Dispersive Channels in Pilot Aided OFDM Using Atomic Norm

We propose the use of the atomic norm minimization for the estimation of sparse time dispersive channels. The proposed estimation approach combines the atomic norm minimization, a super resolution method and the least squares (LS) method, and is intended for pilot aided channel estimation in OFDM systems. The combination of the atomic norm minimization and the super resolution method allows for gridless estimation of arbitrary delays of the individual paths in the channel impulse response, and the gains of those paths are then estimated using the LS method. To further improve the performance we also propose a version of the approach with reweighted atomic norm minimization. We compare the performance of the proposed approach with other grid based approaches for sparse channel estimation.

Capacity of frequency selective fading channels with side information

We derive a formula for the capacity of discrete time frequency selective fading channels, with channel impulse responses described by stationary ergodic processes. We express the information capacity as an integral with respect to the limiting distribution of the eigenvalues of a matrix that depends on the channel impulse response. Simulation results show that in a broad SNR range capacity is close to the capacity of a flat fading channel.

Convergence Properties of the Bi-CGSTAB Method for the Solution of the 3D Poisson and 3D Electron Current Continuity Equations for Scaled Si MOSFETs

As semiconductor technology continues to evolve, numerical modeling of semiconductor devices becomes an indispensible tool for the prediction of device characteristics. The simple drift-diffusion model is still widely used, especially in the study of subthreshold behavior in MOSFETs. The numerical solution of these two equations offers difficulties in small devices and special methods are required for the case when dealing with 3D problems that demand large CPU times. In this work we investigate the convergence properties of the Bi-CGSTAB method. We find that this method shows superior convergence properties when compared to more commonly used ILU and SIP methods.

Achievable rates of the amplify-and-forward strategy for the Gaussian relay channel

We present achievable rates of the amplify-and-forward (AF) cooperative strategy for the Gaussian relay channel. In our analysis we consider both full-duplex and half-duplex modes of operation of the relay channel, assuming that perfect transmit channel state information (CSI) is available at the transmitter and relay. These rates are compared under different channel conditions to their corresponding upper capacity bounds and to the rate of direct transmission in order to investigate when it is beneficial to use AF relaying.

Optimal adaptive equalization of multipath fading channels

In this paper, we investigate optimal channel equalization techniques that incorporate a priori statistical information about multipath fading channels for mobile radio. We use a transformation from a physical ray model to a discrete-time finite impulse response model, along with statistical assumptions about the ray paths, to obtain a state-space model of the time evolution of the channel impulse response. This model as used with the Kalman filter to develop optimal channel estimators. We also implemented these estimators in a blind equalization scheme, based on MAP symbol-by-symbol detector. We present simulation results that characterize the performance of the proposed channel estimator and blind equalizer.<<ETX>>

Compressed Sensing MRI Using Discrete Nonseparable Shearlet Transform and FISTA

We propose a new compressed sensing MRI approach that uses the discrete nonseparable shearlet transform (DNST) as a sparsifying transform and the fast iterative soft thresholding algorithm (FISTA) for reconstruction. FISTA has a simple design and has shown good convergence behavior. The DNST transform has excellent localization properties within the space domain and excellent directional selectivity. We utilize the frequency representation of the DNST canonical dual filters to obtain a memory efficient modified FISTA based algorithm with a simple and efficient way of calculating the update, tuned to the non tight frame DNST transform. The proposed approach shows improved performance and similar execution time when compared with other state of the art reconstruction approaches.

Frequency-Space Interference Alignment in Multi-Cell MIMO OFDM Downlink Systems

We consider two approaches to frequency-space Interference Alignment (IA) in multi-cell systems that use Orthogonal Frequency Division Multiplexing (OFDM) and Multiple Input Multiple Output (MIMO). In the first approach, which we call frequency-space IA, we align and remove the interference from the signals radiated from the base stations intended for the users from the other cells (inter-cell interference) using transmit precoders and receive decoders, and we remove the interference from the users within the cell (intra-cell interference) by using additional Zero-Forcing (ZF) precoding that precedes the IA precoding at the transmiter (base station). In the second approach, we assume that Orthogonal Frequency Division Multiple Access (OFDMA) downlink is used for transmission to the users within the cell, which avoids the intra-cell interference, and we apply frequency-space IA to the inter-cell interference only. Simulation results show that the first approach outperforms the second in a broad SNR region.