Abstract. Unsupervised algorithms can be used in digital communications to estimate the channel at the receiver without using pilot symbols, thus obtaining a considerable improvement in terms of data rate, spectral efficiency, and energy consumption. Unfortunately, the computational load is considerably high since they require to estimate Higher Order Statistics. For addressing this issue, it has been recently presented a decision-aided channel estimation strategy, which implemented a decision rule to determine if a new channel estimate was required or not. If channel estimation is not needed, a previous estimate was used to recover the transmitted signals. Based on this idea, we propose a lowercomplexity decision criterion and we evaluate its performance over realworld indoor channels measured using a hardware platform working at the Industrial, Scientific and Medical band at 5 GHz
