Yahong Rosa Zheng

Improved models for the generation of multiple uncorrelated Rayleigh fading waveforms

An improved sum-of-sinusoids simulation model is proposed for Rayleigh fading channels. The new model employs random initial phase, and conditional random Doppler frequency for all individual sinusoids. The second-order statistics of the new simulator match the desired ones exactly even if the number of sinusoids is a single-digit integer. Other key statistics of the new simulator approach the desired ones of Clarkes (1968) reference model as the number of sinusoids approaches infinity, while good convergence is achieved when the number of sinusoids is small. Moreover, the new simulator can be directly used to generate multiple uncorrelated fading waveforms; it is also pointed out that a class of 16 different simulators, which have identical statistical properties, can be developed for Rayleigh fading channels.

Novel Sum-of-Sinusoids Simulation Models for Rayleigh and Rician Fading Channels

The statistical properties of Clarkes fading model with a finite number of sinusoids are analyzed, and an improved reference model is proposed for the simulation of Rayleigh fading channels. A novel statistical simulation model for Rician fading channels is examined. The new Rician fading simulation model employs a zero-mean stochastic sinusoid as the specular (line-of-sight) component, in contrast to existing Rician fading simulators that utilize a non-zero deterministic specular component. The statistical properties of the proposed Rician fading simulation model are analyzed in detail. It is shown that the probability density function of the Rician fading phase is not only independent of time but also uniformly distributed over [-pi, pi). This property is different from that of existing Rician fading simulators. The statistical properties of the new simulators are confirmed by extensive simulation results, showing good agreement with theoretical analysis in all cases. An explicit formula for the level-crossing rate is derived for general Rician fading when the specular component has non-zero Doppler frequency

Globally Optimal Linear Precoders for Finite Alphabet Signals Over Complex Vector Gaussian Channels

We study the design optimization of linear precoders for maximizing the mutual information between finite alphabet input and the corresponding output over complex-valued vector channels. This mutual information is a nonlinear and non-concave function of the precoder parameters, posing a major obstacle to precoder design optimization. Our work presents three main contributions: First, we prove that the mutual information is a concave function of a matrix which itself is a quadratic function of the precoder matrix. Second, we propose a parameterized iterative algorithm for finding optimal linear precoders to achieve the global maximum of the mutual information. The proposed iterative algorithm is numerically robust, computationally efficient, and globally convergent. Third, we demonstrate that maximizing the mutual information between a discrete constellation input and the corresponding output of a vector channel not only provides the highest practically achievable rate but also serves as an excellent criterion for minimizing the coded bit error rate. Our numerical examples show that the proposed algorithm achieves mutual information very close to the channel capacity for channel coding rate under 0.75, and also exhibits a large gain over existing linear precoding and/or power allocation algorithms. Moreover, our examples show that certain existing methods are susceptible to being trapped at locally optimal precoders.

An Affine Projection Sign Algorithm Robust Against Impulsive Interferences

A new affine projection sign algorithm (APSA) is proposed, which is robust against non-Gaussian impulsive interferences and has fast convergence. The conventional affine projection algorithm (APA) converges fast at a high cost in terms of computational complexity and it also suffers performance degradation in the presence of impulsive interferences. The family of sign algorithms (SAs) stands out due to its low complexity and robustness against impulsive noise. The proposed APSA combines the benefits of the APA and SA by updating its weight vector according to the L 1-norm optimization criterion while using multiple projections. The features of the APA and the L 1-norm minimization guarantee the APSA an excellent candidate for combatting impulsive interference and speeding up the convergence rate for colored inputs at a low computational complexity. Simulations in a system identification context show that the proposed APSA outperforms the normalized least-mean-square (NLMS) algorithm, APA, and normalized sign algorithm (NSA) in terms of convergence rate and steady-state error. The robustness of the APSA against impulsive interference is also demonstrated.

Proportionate Affine Projection Sign Algorithms for Network Echo Cancellation

Two proportionate affine projection sign algorithms (APSAs) are proposed for network echo cancellation (NEC) applications where the impulse response is often real-valued with sparse coefficients and long filter length. The proposed proportionate-type algorithms can achieve fast convergence and low steady-state misalignment by adopting a proportionate regularization matrix to the APSA. Benefiting from the characteristics of l1-norm optimization, affine projection, and proportionate matrix, the new algorithms are more robust to impulsive interferences and colored input than the proportionate least mean squares (PNLMS) algorithm and the robust proportionate affine projection algorithm (Robust PAPA). The new algorithms also achieve much faster convergence rate in sparse impulse responses than the original APSA and the normalized sign algorithm (NSA). The new algorithms are robust to all types of NEC impulse response with different sparseness without the need to change parameters or estimate the sparseness of the impulse response. The computational complexity of the new algorithms is lower than the affine projection algorithm (APA) family due to the elimination of the matrix inversion.

Robust near-field adaptive beamforming with distance discrimination

This paper proposes a robust near-field adaptive beamformer for microphone array applications in small rooms. Robustness against location errors is crucial for near-field adaptive beamforming due to the difficulty in estimating near-field signal locations especially the radial distances. A near-field regionally constrained adaptive beamformer is proposed to design a set of linear constraints by filtering on a low rank subspace of the near-field signal over a spatial region and frequency band such that the beamformer response over the designed spatial-temporal region can be accurately controlled by a small number of linear constraint vectors. The proposed constraint design method is a systematic approach which guarantees real arithmetic implementation and direct time domain algorithms for broadband beamforming. It improves the robustness against large errors in distance and directions of arrival, and achieves good distance discrimination simultaneously. We show with a nine-element uniform linear array that the proposed near-field adaptive beamformer is robust against distance errors as large as /spl plusmn/32% of the presumed radial distance and angle errors up to /spl plusmn/20/spl deg/. It can suppress a far field interfering signal with the same angle of incidence as a near-field target by more than 20 dB with no loss of the array gain at the near-field target. The significant distance discrimination of the proposed near-field beamformer also helps to improve the dereverberation gain and reduce the desired signal cancellation in reverberant environments.

On the Mutual Information and Power Allocation for Vector Gaussian Channels with Finite Discrete Inputs

In this paper, the mutual information and power allocation are discussed for vector Gaussian channels with finite discrete inputs. It is shown that the classic waterfilling and mercury-waterfilling policies, which are allocating power to a bank of independent parallel channels, may lead to significant loss compared to the original system without power allocation for finite discrete inputs. A generalized linear precoder, which is a non-diagonal and non-unitary matrix, is proposed for cross-channel power allocation to maximize the mutual information for vector channels. Numerical examples show that the new precoding-based power allocation provides significant gain for a broad region of signal-to-noise ratios.

Robust MIMO Underwater Acoustic Communications Using Turbo Block Decision-Feedback Equalization

In this paper, a robust detection scheme is proposed for high data rate single-carrier multiple-input-multiple-output (MIMO) underwater acoustic communications. The new scheme adopts turbo block decision-feedback equalization, where the soft-decision equalizer performs successive soft interference cancellation of both the intersymbol interference in the time domain, and the multiplexing interference in the space domain. Attributed to the inherent advantage of the block decision-feedback equalizer (BDFE) over other conventional equalizers, the MIMO turbo detection algorithm provides high performance with fast convergence speed. With the interblock interference properly removed, the MIMO BDFE is performed with overlapped information blocks without guard intervals, thus a high transmission efficiency is guaranteed and the performance degradation at the tail of each block is prevented. The MIMO channel is treated as time invariant over each small block, and is estimated with either the pilot symbols in the training mode or the previously detected symbols in the decision-directed mode. The proposed detection scheme has been tested by extensive experimental data and proved to be robust to different transmission environments. The experimental results for the undersea 2008 Surface Processes and Acoustic Communications Experiment (SPACE08) and the 2008 Gulf of Mexico Experiment (GOMEX08) are both reported.

Energy Efficiency and Spectral Efficiency Tradeoff in Type-I ARQ Systems

The optimum energy efficient and spectral efficient designs for type-I automatic-repeat-request (ARQ) systems in Rayleigh flat fading channels are studied in this paper. Three optimum designs are considered: the first scheme maximizes the energy efficiency (EE), or equivalently, minimizes the total energy per information bit without considering the spectral efficiency (SE); the second scheme minimizes a new metric, the energy per information bit normalized by the SE; and the third scheme maximizes the EE under the constraint of a minimum SE. For given physical and link layer parameters, such as hardware power consumption, coding rate, modulation, bit rate, number of overhead bits, and communication distance, the three schemes are optimized with respect to the average transmission energy and the number of information bits per frame. The fundamental EE-SE tradeoff curve is analytically identified via the optimization of the third scheme, and it is shown that the optimum EE is quansiconcave in SE in a type-I ARQ system. The optimum solutions to the first two schemes are special operating points on the EE-SE tradeoff curve. Computer simulation results verify the analytical solutions.

Mobile speed estimation for broadband wireless communications over Rician fading channels

In this paper, a new algorithm is proposed to estimate mobile speed for broadband wireless communications, which often encounter large number of fading channel taps causing severe intersymbol interference. Different from existing algorithms, which commonly assume that the fading channel coefficients are available for the speed estimators, the proposed algorithm is based on the received signals which contain unknown transmitted data, unknown frequency selective fading channel coefficients possibly including line-of-sight (LOS) components, and random receiver noise. Theoretical analysis is first carried out from the received signals, and a practical algorithm is proposed based on the analytical results. The algorithm employs a modified normalized auto-covariance of received signal power to estimate the speed of mobiles. The algorithm works well for frequency selective Rayleigh and Rician channels. The algorithm is very resistant to noise, it provides accurate speed estimation even if the signal-to-noise ratio (SNR) is as low as 0 dB. Simulation results indicate that the new algorithm is very reliable and effective to estimate mobile speed corresponding to a maximum Doppler up to 500 Hz. The algorithm has high computational efficiency and low estimation latency, with results being available within one second after communication is established.