Discrete interferences optimum beamformer in correlated signal and interfering noise

This paper introduces a significant special situation where the noise is a collection of D-plane interference signals and the correlated noise of D+1 is less than the number of array components. An optimal beamforming processor based on the minimum variance distortionless response (MVDR) generates and combines appropriate statistics for the D+1 model. Instead of the original space of the N-dimensional problem, the interference signal subspace is reduced to D+1. Typical antenna arrays in many modern communication networks absorb waves generated from multiple point sources. An analytical formula was derived to improve the signal to interference and noise ratio (SINR) obtained from the steering errors of the two beamformers. The proposed MVDR processor-based beamforming does not enforce general constraints. Therefore, it can also be used in systems where the steering vector is compromised by gain. Simulation results show that the output of the proposed beamformer based on the MVDR processor is usually close to the ideal state within a wide range of signal-to-noise ratio and signal-to-interference ratio. The MVDR processor-based beamformer has been experimentally evaluated. The proposed processor-based MVDR system significantly improves performance for large interference white noise ratio (INR) in the sidelobe region and provide an appropriate beam pattern.

An Efficient DOA Estimation Algorithm Based on Diagonal-Symmetric Loading

In order to solve the problem that the subspace-like direction of arrival (DOA) estimation performs poor due to the error of sources number, this paper proposes a new super-resolution DOA estimation algorithm based on the diagonal-symmetric loading (DSL). Specifically, orthogonality principle of the minimum eigenvector of the specific covariance matrix and the source number estimation based on the improved K-means method were adopted to construct the spatial spectrum. Then, by considering the signal-to-interference-to-noise ratio (SINR), the theoretical basis for selecting parameters was given and verified by numerical experiment. To evaluate the effectiveness of the proposed algorithm, this paper compared it with the methods of minimum variance distortionless response (MVDR) and new signal subspace processing (NSSP). Experimental results prove that the proposed DSL has higher resolution and better estimation accuracy than the MVDR and NSSP.

Maximum Element Dichotomous Coordinate Descent Based Minimum Variance Distortionless Response DoA Estimator

In this paper, we devise an efficient approach for estimating the direction of arrival (DoA). The proposed DoA estimation approach is based on minimum variance distortionless response (MVDR) criteria within a recursive least squares (RLS) framework. The dichotomous coordinate descent algorithm is used to modify the calculation of the output power spectrum, and a diagonal loading term is applied to improve the robustness of the DoA estimator. These modifications allow us to both reduce the computational complexity of the RLS DoA estimator and increase the estimation performance. A numerical comparison confirms that the proposed DoA estimator outperforms the conventional RLS DoA estimator in terms of the computational complexity and DoA estimation error. Finally, the proposed theoretical DoA estimator is implemented on a field-programmable gate array (FPGA) board to verify the feasibility of the method. The numerical results of a fixed-point implementation demonstrate that the performance of the proposed method is very close to that of its floating-point counterpart.

Optimal Resource Allocation for Multicarrier NOMA in Short Packet Communications

Wireless communication system needs a spectrum efficient, a power efficient and a cost efficient communication with high throughput to provide communication for ubiquities applications such as voice, data, picture, video, movies, multimedia services, Global Positional System (GPS), navigational system, telemedicine and other value added communication. Non-Orthogonal Frequency Division Multiplexing (NOMA) has become a popular technique for transmission of signals over wireless channels. In the first phase, MIMO system which uses NOMA is used. User signals are divided into parallel streams, using NOMA and are transmitted by the antenna array which propagates through the fading channel. signals are weighted using the Minimum Variance Distortionless Response (MVDR) where the weights are such that the output signal has minimum variance and the desired signal is not distorted. The parallel weighting scheme for interference cancellation leads to a faster, reliable and higher capacity system and results in parallel interference cancellation. Iterative process is also presented in this work, where the approximate weights are found out based on the minimum error value. Both the MVDR weighting and the approximate weighting are evaluated with the help of Bit Error Rate (BER) curves. The curves are plotted for both the Rayleigh and Rician channels. Various plots are obtained by varying the number of antennas in the array and also by varying the length of the user signal. All the BER curves achieved good results and from the analysis it is found that system performs better when Rayleigh channel was considered.

An integrated MVDR beamformer for speech enhancement using a local microphone array and external microphones

An integrated version of the minimum variance distortionless response (MVDR) beamformer for speech enhancement using a microphone array has been recently developed, which merges the benefits of imposing constraints defined from both a relative transfer function (RTF) vector based on a priori knowledge and an RTF vector based on a data-dependent estimate. In this paper, the integrated MVDR beamformer is extended for use with a microphone configuration where a microphone array, local to a speech processing device, has access to the signals from multiple external microphones (XMs) randomly located in the acoustic environment. The integrated MVDR beamformer is reformulated as a quadratically constrained quadratic program (QCQP) with two constraints, one of which is related to the maximum tolerable speech distortion for the imposition of the a priori RTF vector and the other related to the maximum tolerable speech distortion for the imposition of the data-dependent RTF vector. An analysis of how these maximum tolerable speech distortions affect the behaviour of the QCQP is presented, followed by the discussion of a general tuning framework. The integrated MVDR beamformer is then evaluated with audio recordings from behind-the-ear hearing aid microphones and three XMs for a single desired speech source in a noisy environment. In comparison to relying solely on an a priori RTF vector or a data-dependent RTF vector, the results demonstrate that the integrated MVDR beamformer can be tuned to yield different enhanced speech signals, which may be more suitable for improving speech intelligibility despite changes in the desired speech source position and imperfectly estimated spatial correlation matrices.

Speech Intelligibility and Spatial Release From Masking Improvements Using Spatial Noise Reduction Algorithms in Bimodal Cochlear Implant Users

This study investigated the speech intelligibility benefit of using two different spatial noise reduction algorithms in cochlear implant (CI) users who use a hearing aid (HA) on the contralateral side (bimodal CI users). The study controlled for head movements by using head-related impulse responses to simulate a realistic cafeteria scenario and controlled for HA and CI manufacturer differences by using the master hearing aid platform (MHA) to apply both hearing loss compensation and the noise reduction algorithms (beamformers). Ten bimodal CI users with moderate to severe hearing loss contralateral to their CI participated in the study, and data from nine listeners were included in the data analysis. The beamformers evaluated were the adaptive differential microphones (ADM) implemented independently on each side of the listener and the (binaurally implemented) minimum variance distortionless response (MVDR). For frontal speech and stationary noise from either left or right, an improvement (reduction) of the speech reception threshold of 5.4 dB and 5.5 dB was observed using the ADM, and 6.4 dB and 7.0 dB using the MVDR, respectively. As expected, no improvement was observed for either algorithm for colocated speech and noise. In a 20-talker babble noise scenario, the benefit observed was 3.5 dB for ADM and 7.5 dB for MVDR. The binaural MVDR algorithm outperformed the bilaterally applied monaural ADM. These results encourage the use of beamformer algorithms such as the ADM and MVDR by bimodal CI users in everyday life scenarios.

Robust adaptive beamforming based on the direct biconvex optimization modeling

It is well known that the performance of the minimum variance distortionless response beamformer is sensitive to steering vector mismatch, which motivates the development of robust adaptive beamforming(RAB). However, robust adaptive beamforming (RAB) is usually modeled as a nonconvex optimization problem. The most state-of-art methods solve it indirectly by approximating the nonconvex problem to the convex optimization problem, which causes the approximation errors and performance degradation. To circumvent this problem, a novel method that is against the mismatch of the signal look direction errors, which reformulates RAB as the biconvex form directly, is proposed. This method imposes ideal response constraints to guarantee the gain of the angular region in which the actual signal lies and suppresses the signals in the remaining region, and constructs a four-order problem. Then, an auxiliary variable is introduced to reformulate it as a biconvex problem without approximation process, which can be efficiently solved iteratively by the alternating direction method of multipliers (ADMM) algorithm. Simulation results show that the proposed method can obtain a better performance on the signal-to-interference-plus-noise (SINR) and flexible control of error range.