Multicore Simulation of Acoustic Beamforming Using a Microphone Array

This example shows how to beamform signals received by an array of microphones to extract a desired speech signal in a noisy environment. It uses the dataflow domain in Simulink® to partition the data-driven portions of the system into multiple threads and thereby improving the performance of the simulation by executing it on your desktop's multiple cores.

Introduction

The model simulates receiving three audio signals from different directions on a 10-element uniformly linear microphone array (ULA). After the addition of thermal noise at the receiver, beamforming is applied and the result played on a sound device.

Received Audio Simulation

The Audio Sources subsystem reads from audio files and specifies the direction for each audio source. The Wideband Rx Array block simulates receiving audio signals at the ULA. The first input to the Wideband Rx Array block is a 1000x3 matrix, where the three columns of the input correspond to the three audio sources. The second input (Ang) specifies the incident direction of the signals. The first row of Ang specifies the azimuth angle in degrees for each signal and the second row specifies the elevation angle in degrees for each signal. The output of this block is a 1000x10 matrix. Each column of the output corresponds to the audio recorded at each element of the microphone array. The microphone array's configuration is specified in the Sensor Array tab of the block dialog panel. The Receiver Preamp block adds white noise to the received signals.

Beamforming

There are three Frost Beamformer blocks that perform beamforming on the matrix passed via the input port X along the direction specified by the input port Ang. Each of the three beamformers steers their beam towards one of the three sources. The output of the beamformer is played in the Audio Device Writer block. Different sources can be selected using the Select Source block.

Improve Simulation Performance Using Multithreading

This example can use the dataflow domain in Simulink to automatically partition the data-driven portions of the system into multiple threads and thereby improving the performance of the simulation by executing it on your desktop's multiple cores. To learn more about dataflow and how to run Simulink models using multiple threads, see Multicore Execution using Dataflow Domain (DSP System Toolbox).

Setting up Dataflow Subsystem

In Simulink, you specify dataflow as the execution domain for a subsystem by setting the Domain parameter to Dataflow using Property Inspector. Dataflow domains automatically partition your model and simulate the system using multiple threads for better simulation performance. Once you set the Domain parameter to Dataflow, you can use Dataflow Simulation Assistant to analyze your model to get better performance. You can open the Dataflow Simulation Assistant by clicking on the Dataflow assistant button below the Automatic frame size calculation parameter in Property Inspector.

Analyzing Concurrency in Dataflow Subsystem

In the Dataflow Simulation Assistant, click the Analyze button to start the analysis of the dataflow domain for simulation performance. Once the analysis is finished, the Dataflow Simulation Assistant shows how many threads the dataflow subsystem will use during simulation.

For this model the assistant shows three threads because the three Frost Beamformer blocks are computationally intensive and they can run in parallel. However, the three Frost Beamformer blocks depend on the Microphone Array and Receiver blocks to finish before they start execution. Concurrency can be increased for this model by using pipeline delays between the beamformer blocks and the source simulation blocks. Dataflow Simulation Assistant shows the recommended number of pipeline delays as Suggested Latency. For this model, the suggested latency is one. Click the Accept button next to Suggested Latency in the Dataflow Simulation Assistant to use the recommended latency for the Dataflow Subsystem.

Multicore Simulation Performance

To measure performance improvement gained by using dataflow, compare execution time of the model with and without dataflow. The Audio Device Writer runs in real time and limits the simulation speed of the model to real time. Comment out the Audio Device Writer block when measuring execution time. On a Windows desktop computer with Intel® Xeon® CPU E5-1650 v3 @ 3.5 GHz 6 Cores 12 Threads processor this model using dataflow domain executes 1.7x times faster compared to original model.

Summary

This example showed how to beamform signals received by an array of microphones to extract a desired speech signal in a noisy environment. It also shows how to use the dataflow domain to automatically partition the data-driven part of the model into concurrent execution threads and run the model using multiple threads.