  This paper proposes low complexity detection for internet of underwater
things (IoUT)s communication. The signal is transmitted from the source to the
destination using several sensors. To simplify the computational operations at
the transmitter and the sensory nodes, a single carrier frequency domain
equalizer (SC-FDE) is proposed and amplify-and-forward (AF) protocols are
employed. Fast Fourier transform (FFT) and use of cyclic prefix (CP) are also
proposed to simplify these algorithms when compared to time-domain
equalization. As precise channel data is difficult to capture in underwater
communications, the adaptive implementation of FDE is proposed as a solution
that can be employed when the channel experiences a fast doppler shift. The two
adaptive detectors are based on the least mean-square (LMS) and recursive least
square (RLS) principles. Numerical simulations show that the performance of the
bit error rate (BER) performance of the proposed detectors is close to that of
the ideal minimum mean square error (MMSE).
