Upgrading an Analog Recovery Loop for Optimized Decoding Jointly to an Increased data-Rate

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.