Quantization and fixed-point arithmetic for MIMO MMSE-IC linear turbo-equalization

Mostafa Rizk, A. Baghdadi, M. Jézéquel, Y. Mohanna, Y. Atat
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引用次数: 6

Abstract

In digital communication applications, floating-point arithmetic is generally used to conduct performance evaluation studies of new proposed algorithms. This is typically limited to theoretical performance evaluation in terms of communication quality and error rates. For a practical implementation perspective, using fixed-point arithmetic instead of floating-point reduces significantly the costs in terms of area occupation and energy consumption. However, this implies a complex conversion process, particularly if the considered algorithm includes complex arithmetic operations with high accuracy requirements and if the target system presents many configuration parameters. In this context, the purpose of the paper is to investigate the influence on error rate performance related to the implementation of minimum mean-squared error (MMSE) linear turbo-equalization algorithm for multiple-input multiple-output (MIMO) systems utilizing fixed-point rather than floating-point arithmetic.
MIMO MMSE-IC线性涡轮均衡的量化与定点算法
在数字通信应用中,通常使用浮点算法对新算法进行性能评估研究。这通常局限于通信质量和错误率方面的理论性能评估。从实际实现的角度来看,使用定点算法而不是浮点算法在面积占用和能耗方面显著降低了成本。然而,这意味着一个复杂的转换过程,特别是如果考虑的算法包含具有高精度要求的复杂算术运算,并且目标系统提供许多配置参数。在这种情况下,本文的目的是研究与实现最小均方误差(MMSE)线性涡轮均衡算法有关的错误率性能的影响,该算法用于多输入多输出(MIMO)系统,利用定点而不是浮点算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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