In the development of complex signal processing and communication technologies, the discontinuity of the design process is increasingly destructive and costly. At the same time, the need to shorten the design and verification cycles has further magnified the effects of design discontinuities. This article presents recent developments in modeling, simulation, and code generation tools and methods by introducing several use cases in algorithm design, system architecture, and hardware design.
Algorithm design of flow systemMore and more engineers are now using the floating point operations in MATLAB to develop signal processing and communication system algorithms. These algorithm developers can take advantage of MATLAB's powerful signal acquisition and analysis capabilities, as well as a library of built-in algorithms for multiple toolboxes. However, in some teams, for algorithmic optimization implementations, engineers rewrite these algorithms in C code, convert them to fixed-point or integer operations, or integrate them with other design elements. This rewrite step is a potential, costly and disruptive typical discontinuity in the design process.
Hundreds of new components for signal processing, communication, imaging, and video processing from MATLAB are available as System Object libraries. In MATLAB, the System object library is designed for designing real-time systems, and is an algorithm implementation of ready-to-use packaging. They implicitly handle streaming, indexing, buffering, and state management, making it easier to write, debug, and maintain code.
Figure 1 shows a block diagram representation of a basic communication system with transmitter, channel and receiver components. To model and simulate such a system, engineers need to write thousands of lines of C code and then look for ways to integrate the design with the test equipment or analyze the simulation results.
Figure 1: Block diagram of the physical layer of a typical communication system.
Compared to the thousands of lines of C code (generally written to implement this communication system), the MATLAB code shown in Figure 2 uses several System objects from the DSP System Toolbox and the CommunicaTIons System Toolbox.
Figure 2: Part of the MATLAB code showing the use of System objects from DSP System Toolbox and CommunicaTIons System Toolbox.
For example, to model the emitter, engineers can instantiate and call Reed-Solomon encoders, convolutional encoders, block interleavers, rectangular QAM modulators, and orthogonal space-time block codes in CommunicaTIons System Toolbox in sequence. System object (as shown in Figure 2). This code structure allows engineers to easily compare it to the original specifications or block diagrams. Algorithm designers can quickly combine this code with their existing MATLAB code and test these algorithms using real-time streaming data from test instruments.
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