## 2 Related Works
### CFO Case Studies in Multicarrier Modulations
\begin{table}
\begin{tabular}{p{108.4 pt} p{108.4 pt} p{108.4 pt}} \hline \hline
**Papers and Years** & **Advantages** & **Limitations** \\ \hline \multirow{6}{*}{[3] (2012)} & An iterative-detection dual-CFO compensation technique was proposed to deal with the dual phase errors experienced in a DVB-T2 MISO SFN environment. & \multirow{6}{*}{The complexity of the technique was not evaluated.} \\ \cline{3-3}  & A successive-iterative ICI cancellation technique was also proposed to deal with the additional ICI’s introduced by the MISO technique in an SFN environment. & \multirow{6}{*}{The complexity of the technique was not evaluated.} \\ \cline{3-3}  & The performance of both techniques was evaluated in DVB-T2 system using BER vs. SNR when only the iterative-detection dual-CFO compensation was used and when they were both used. & Other performance evaluation tools like MER and EVM were not considered. The Power Delay Profile (PDP) of the MISO channel was not defined. \\ \hline \multirow{3}{*}{[25] (2012)} & The numerical expression of Integer Frequency Offset (IFO) and Fractional Frequency Offset (FFO) were well developed. & The complexity of these techniques was not evaluated. \\ \cline{3-3}  & CFO estimation techniques such as frequency- and time-domain techniques were presented in detail. The performance of CFO estimation techniques Classen and Moose was evaluated in OFDM transmission using BER vs. SNR. & \multirow{3}{*}{A trade-off between the performance of these techniques and their complexity was not obtained to choose the better technique.} \\ \hline \multirow{3}{*}{[26] (2015)} & The spectral efficiency of OFDM systems was evaluated in the presence of a residual CFO included in the signal after applying a CFO estimation technique. & The numerical expression of the Signal-to-Interference-plus-Noise Ratio (SINR) was derived but the relationship between SINR and spectral efficiency was not established. \\ \cline{3-3}  & The spectral efficiency of cyclic prefix-based and training-based CFO estimators were evaluated and compared to the theory (Shannon capacity). The MISO transmission case was also considered. & \multirow{3}{*}{PDP of the fading channel used for imperfect CSI case was not highlighted.} \\ \hline \multirow{6}{*}{[1] (2015)} & The stochastic and deterministic maximum likelihood (SML and DML) CFO estimation methods were derived using the special structure of the P1 symbol in DVB-T2 system. & The performance of these algorithms was evaluated in the DVB-T2 system by using BER vs. SNR. Only Cramer–Rao lower bounds and the Mean Square Error were used for the algorithms’ performance. \\ \cline{3-3}  & These algorithms were derived with the assumption that the CSI was unknown & There was no information about the channel PDP used for simulation. \\ \cline{3-3}  & The performance of these techniques was evaluated and compared to the previous estimation methods proposed in the literature. These algorithms could estimate the receive signal power, the time delays, and the CFO. & The complexity of these algorithms was evaluated by just evaluating the elapsed time of the proposed algorithms and comparing them to previous CFO estimation methods proposed. \\ \hline \multirow{3}{*}{[27] (2016)} & The impact of the CFO on the UFMC system performance was evaluated and compared to those values used. & There was a lack of justification of the CFO values used. \\ \cline{3-3}  & A zero-forcing equalizer was used for both OFDM and UFMC. The Symbol Error Rate (SER) was the tool exploited for the performance evaluation & The channel PDP used was not highlighted. \\ \hline \multirow{3}{*}{[28] (2017)} & The performance of single-user UFMC, multi-user UFMC, and MIMO-MU-UFMC systems was evaluated and compared to that of OFDM in the presence of a CFO. & There was a lack of justification of the CFO values used. \\ \cline{3-3}  & Zero-forcing and MMSE equalizers were both used and their performance was compared. SER was the tool used. & The channel PDP used was not highlighted. \\ \hline \hline \end{tabular}
\end{table}