Design of robust broadband beamformers with discrete coefficients and least squared criterion

This brief investigates the performance of robust and nonrobust broadband beamformers with least squares and discrete coefficients to achieve low complexity and efficient hardware implementation. The broadband beamformer coefficients are expressed as the sum of power-of-two terms with a restriction on the total number of power-of-two terms for the beamformer coefficients. An iterative algorithm is employed to reduce the number of nonzero coefficients and, thereby, multipliers in both the robust and nonrobust beamformers. A quantization scheme in combination with a random search is then applied to efficiently distribute the power-of-two terms for the beamformer coefficients. Design examples show that the number of nonzero coefficients for the beamformers can be significantly reduced without a significant degradation in the integral squared error. In addition, robust beamformers are shown to be less sensitive to nonzero coefficient reduction and quantization than nonrobust beamformers. This brief investigates the performance of robust and nonrobust broadband beamformers with least squares and discrete coefficients to achieve low complexity and efficient hardware implementation. The broadband beamformer coefficients are expressed as the sum of power-of-two terms with a restriction on the total number of power-of-two terms for the beamformer coefficients. An iterative algorithm is employed to reduce the number of nonzero coefficients and, thereby, multipliers in both the robust and nonrobust beamformers. A quantization scheme in combination with a random search is then applied to efficiently distribute the power-of-two terms for the beamformer coefficients.Design examples show that the number of nonzero coefficients for the beamformers can be significantly reduced without a significant degradation in the integral squared error. In addition, robust beamformers are shown to be less sensitive to nonzero coefficient reduction and quantization than nonrobust beamformers

On the indoor beamformer design with reverberation

Beamforming remains to be an important technique for signal enhancement. For applications in open space, the transfer function describing waves propagation has an explicit expression, which can be employed for beamformer design. However, the function becomes very complex in an indoor environment due to the effects of reverberation. In this paper, this problem is discussed. A method based on the image source method (ISM) is applied to model the room impulse responses (RIRs), which will act as the transfer function between source and sensor. The indoor beamformer design problem is formulated as a minimax optimization problem. We propose and study several optimization models based on the -norm to design the beamformer. We found that it is advantageous to separate early and late reverberations in the design process and better designs can be achieved. Several numerical experiments are presented using both simulated data and real recordings to evaluate the proposed methods

Robust Source Localization in Reverberant Environments Based on Weighted Fuzzy Clustering

Successful localization of sound sources in reverberant enclosures is an important prerequisite for many spatial signal processing algorithms. We investigate the use of a weighted fuzzy-means cluster algorithm for robust source localization using location cues extracted from a microphone array. In orderto increase the algorithm's robustness against sound reflections, we incorporate observation weights to emphasize reliable cues over unreliable ones. The weights are computed from local feature statistics around sound onsets because it is known that these regions are least affected by reverberation. Experimental results illustrate the superiority of the method when compared with standard fuzzy clustering. The proposed algorithm successfully located two speech sources for a range of angular separations in room environments with reverberation times of up to 600 ms

On the sparse beamformer design

In designing acoustic broadband beamformers, the complexity can grow significantly when the number of microphones and the filter length increase. It is advantageous if many of the filter coefficients are zeroes so that the implementation can be executed with less computation. Moreover, the size of the array can also be pruned to reduce complexity. These problems are addressed in this paper. A suitable optimization model is proposed. Both array pruning and filter thinning can be solved together as a two-stage optimization problem to yield the final sparse designs. Numerical results show that the complexity of the designed beamformers can be reduced significantly with minimal effect on performance

Simplified MMSE Precoding Design in Interference Two-Way MIMO Relay Systems

We investigate the transceiver design for interference two-way amplify-And-forward multiple-input multiple-output relay communication systems. A novel algorithm with a closed-form solution is developed to optimize the relay precoding matrix based on its optimal structure and a modified transmission power constraint at the relay node. An iterative algorithm is proposed to minimize the sum mean-squared error of the signal waveform estimation. Simulation results demonstrate that the proposed algorithm achieves a better performance-complexity tradeoff compared with existing techniques

Transceiver optimization for interference MIMO relay systems using the structure of relay matrix

In this paper, we study the transceiver design problem for amplify-and-forward interference multiple-input multiple-output (MIMO) relay communication systems, where multiple transmitter-receiver pairs communicate simultaneously with the aid of a relay node. We aim at minimizing the mean-squared error (MSE) of the signal waveform estimation at the receivers subjecting to transmission power constraints at the transmitters and the relay node. Since the transceiver optimization problem is nonconvex with matrix variables, the globally optimal solution is intractable to obtain. To overcome the challenge, we propose an iterative transceiver design algorithm where the transmitter, relay, and receiver matrices are optimized iteratively by exploiting the optimal structure of the relay precoding matrix. Simulation results show that the proposed algorithm performs better than the existing technique in terms of both MSE and bit-error-rate

MMSE-based joint source and relay optimization for interference MIMO relay systems

In this paper, we investigate the transceiver design for amplify-and-forward (AF) interference multiple-input multiple-output (MIMO) relay communication systems when the direct links between the source and destination nodes are taken into consideration. The minimum mean-squared error (MMSE) of the signal waveform estimation at the destination nodes is chosen as the design criterion to optimize the source, relay, and receiver matrices for interference suppression. As the joint source, relay, and receiver optimization problem is nonconvex with matrix variables, a globally optimal solution is computationally intractable to obtain. We propose two iterative algorithms to provide computationally efficient solutions to the original problem through solving convex subproblems. These two algorithms provide efficient performance-complexity trade-off. Simulation results demonstrate that the proposed algorithms converge quickly after a few iterations and significantly outperform existing scheme in terms of the system bit error rate

Feedback cancellation with probe shaping compensation

Adaptive feedback cancellation methods may integrate the use of probe signals to assist with the biased optimal solution in acoustic systems working in closed-loop. However, injecting a probe noise in the loudspeaker decreases the signal quality perceived by users of assistive listening devices. To counter this, probe signals are usually shaped to provide some level of perceptual masking. In this letter we show the impact of using a shaping filter on the system behavior in terms of convergence rate and steady state error. From this study, it can be concluded that shaping the probe signal may have detrimental influence in terms of system performance. Accordingly, we propose to use the unshaped probe signal combined with an inverse filter of the shaping filter to identify the feedback channel. This restructure of the problem restores convergence rate of LMS type algorithms. Furthermore, we also show that an adequate forward path delay is required to obtain an unbiased solution and that the suggested scheme reduces this delay