Performance prediction of dab modulation and transmission using matlab modeling

Abstract

Abstract — A Simulink-Matlab simulation model is described that enables an accurate performance prediction of complete DAB (digital audio broadcasting) transmission channels. Embedded compiled C-code subroutines include modulation protocols, error correction and MPEG layer-2 perceptual audio coding. Rapid assessment of critical design related factors could be performed that include channel interference, multi-path reflection and a range of modulation-parameters. Software is PC compatible with both DAB system and transmission channel configurable using a bespoke graphical user interface, which facilitates changing on the fly modulation and transmission-path related parameters. Overall audio quality can also be assessed 1 . Index Terms — DAB, Matlab, Modulation, Simulation. I. I NTRODUCTION TO DAB IGITAL audio broadcasting (DAB) was developed in the early 1990’s by the European consortium Eureka 147 [1], mainly to replace the widely used analogue frequency modulation (FM) broadcasting system. The VHF band is a scarce resource in many parts of the world, so there was a need for a spectrally more efficient modulation method than FM. In DAB, this is achieved by multiplexing several programmes into a so-called ensemble with a bandwidth of 1.536 MHz, where the number of programmes per ensemble is flexible and depends on individual programme bandwidth requirements. Further, conventional analogue techniques do not provide satisfactory performance in a mobile environment, because they are highly affected by multi-path propagation and thus fading. In DAB, orthogonal frequency division multiplex (OFDM) has been chosen to overcome the effects of multi-path propagation, enabling the system to operate in so-called single-frequency networks (SFN). The modeling and processing of a DAB system is well suited for Simulink and Matlab. Less common blocks can be implemented in Simulink by programming appropriate 'C'-code that can be compiled and dynamically linked to the model by means of