In the domain of wireless digital communication, floating-point arithmetic is generally used to conduct performance\nevaluation studies of algorithms. This is typically limited to theoretical performance evaluation in terms of\ncommunication quality and error rates. For a practical implementation perspective, using fixed-point arithmetic\ninstead of floating-point reduces significantly implementation costs in terms of area occupation and energy\nconsumption. However, this implies a complex conversion process, particularly if the considered algorithm includes\ncomplex arithmetic operations with high accuracy requirements and if the target system presents many configuration\nparameters. In this context, the purpose of the paper is to present an efficient quantization and fixed-point\nrepresentation for turbo-detection and turbo-demapping. The impact of floating-to-fixed-point conversion is\nillustrated upon the error-rate performance of the receiver for different system configurations. Only a slight\ndegradation in the error-rate performance of the receiver is observed when implementing the detector and demapper\nmodules which utilize the devised quantization and fixed-point arithmetic rather than floating-point arithmetic
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