The maximum likelihood detection theory improves the error rate of a sub-optimal but cheaper, coded symbol recovery loop using oversampling proposed as an alternate solution for the decoding problem without the log-likelihood ratio computation. The former implementation delivers the output data in one-symbol delay, and the required transistor count makes this approach attractive for ultra-low-energy wireless applications. The proposed hardware upgrade includes an analog to digital converter and fixed-point accumulation logic to compute the soft values, replacing a trigger used as a hard detector. This work investigates the soft decoding in the presence of binary and non-binary source symbols. Simulation results show that the soft approach improves the signal-to-noise ratio by 3 dB and 2.5 dB when the encoding rates are 1/3 and 2/3.

最大似然检测理论使用过采样提高了次优但更便宜的编码符号恢复循环的错误率，作为解码问题的替代解决方案，无需对数似然比计算。前一种实现以一个符号延迟提供输出数据，所需的晶体管数量使这种方法对超低能耗无线应用具有吸引力。提议的硬件升级包括模数转换器和定点累加逻辑来计算软值，取代用作硬检测器的触发器。这项工作研究了存在二进制和非二进制源符号的情况下的软解码。仿真结果表明，当编码率为1/3和2/3时，软方法将信噪比提高了3 dB和2.5 dB。