Turbo codes for modern error correction coding provide high error rate performance near the Shannon limits of error-correcting performance [19]. These excellent features of turbo codes have led to their adoption in many communication standards, including high-speed downlink packet access (HSDPA), wireless local area network (WLAN), LTE/LTE-A, and some portion of mMTC in 5G technology, although the performance of turbo codes comes at the expense of high decoding complexity and consequently high-power consumption [16] at the receiver for proper decoding. Actually, the computational difficulty of the turbo decoder far exceeds that of other components in an LTE and NB-IoT receiver, especially for higher data rate and low latency communications. To make the uplink system more flexible, a frequency-domain minimum mean squared error (MMSE) equalizer in a soft interference cancellation (SIC) scheme has been used in the LTE uplink receiver for SC-FDMA. Motivated by this, the frequency domain equalizer (FDE) can be utilized [16]. Several iterative turbo decoding and equalization receiver schemes have been proposed \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Technology** & **LTE-A** & **EC-GSM** & **NB-IoT** \\ \hline \multirow{2}{*}{Deployment Bandwidth} & \multirow{2}{*}{In-band LTE} & \multirow{2}{*}{In-band GSM} & In-band, Guard-band, \\  & & & and Stand-alone \\  & & & 200 kHz per channel. & 180 kHz \\  & & & 164 dB, with 33 dBm & \\ Network Coverage & 155.7 dB & power class. 154 dBm, & 164 dB for \\  & & with 23 dBm & stand-alone and FFS \\  & & power class & for others \\ Downlink Technology & OFDMA, with & TDMA, FDMA, & OFDM with \\  & 15 kHz SCS & GMSK and 8 PSK & 15 kHz SCS \\  & & & Single-tone \\  & & & SC-FDMA with both \\  & & & 15 kHz and 3.75 kHz. \\  & & & GMSK and 8 PSK & Multi-tone SC-FDMA \\  & & & with 15 kHz \\  & & & 70 Kbps with TDMA, & \\ Data Rates & 1 Mbps for both UL & FDMA for both UL & 28 kbps for DL and \\  & and DL & and DL and 240 kbps & 63 kbps for UL \\  & & with 8 PSK & \\ Duplexing & FD and HD (type B), & HD and FDD & HD (type B) and FDD \\  & PSDM, ext. 1 DRX, & PSM, ext. 1-DRX & PSM, ext. 1 DRX, \\ Power class & 23 dBm, 20 dBm & 33 dBm, 23 dBm & 23 dBm, other TBD \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Technical specification of LPWA network technology. in the literature [20; 21]. In [21], during the iterations, the equalizer coefficients remained constant, while in [22] during the iterations, the equalizer was updated in conformity with a priori information received from the decoder. It was presented in [23] that frequency domain equalization (FDE) can easily be applied to uplink NB-IoT system to eliminate the Inter-Symbol Interference (ISI) effect. To further resolve this problem, efficient turbo decoding and equalization is needed, where the frequency domain equalizer and the turbo channel decoder can jointly exchange their soft-decision information by performing iterative detection, thereby canceling the ISI. The turbo decoding and FD-TE considered in the receiver are first formulated to estimate the ISI and sensitivity error among the NPUSCHs subcarrier. By using the repeated data sequence and symbols selection on the NPUSCH subcarriers, the residual ISI can be estimated. Then, the FD-TE equalizer can be introduced using the minimum mean square (MMSE) [22] estimation method and circulant matrix operations to compute the frequency domain estimates of the received signal. The proposed receiver jointly performs the equalization and turbo decoding on specific NPUSCH resources. The analytical results are verified by the mean square error (MSE) and block error rate (BLER) simulation performance of the proposed NPUSCH receiver. Finally, this paper presents a sufficiently robust scheme compared to the conventional FDTE MMSE, which can improve the reliability of the transmission of UE data in NPUSCH and thus reduce the computational complexity suitable for a LPWA NBIoT system.