# A Survey on Optimal Channel Estimation Methods for RIS-Aided Communication Systems
## 5 Conclusions  
The current research delivered an inclusive and up-to-date survey of papers in RIS-assisted wireless communication, such as MIMO and MISO systems communications. Emphasis was placed on the practical challenges of BS, RIS and user channels to estimate them using optimized algorithms with different channel models and system configurations. Then, for various practical scenarios of available CSI, namely I-CSI and S-CSI, we introduced a detailed overview of the research results, depending on the system structure. Different model systems were presented for MISO and MIMO systems using techniques, such as tensor, RL, SDR and others to find the optimal channel estimation algorithm. For the MISO systems, the SDR technique algorithm, the Q-learning RL algorithm and the main PPO algorithm were presented. The PPO algorithm has presented a low and moderate SNR, the BS transmission power was similar to the ADMM algorithm. The preferred algorithms were I-CSI, S-CSI type and the BS-RIS-UE links, which were deterministic. The Q-learning RL algorithm increased the performance and reprocessed the received data. For MIMO systems that were divided into cell and cell-free, some of the algorithms presented were the 3D-MMV 3D-MLAOMP algorithm, two-stage based cascaded channel estimation algorithm, algorithm for an RIS-assisted AB-HBF system and algorithms that use LTI and STI methods. Of the mentioned algorithms, the 3D-MMV 3D-MLAOMP algorithm has been more interesting because it is a tensor-type algorithm, it has presented a low SNR and is preferred for low processing latency. Table 2 presented the characteristics of the above algorithms. Considering all the above, we found that channel estimation in RIS-assisted communication systems is improved by creating new or optimizing existing algorithms. Improvement was observed in estimation time, performance, how the BS-RIS and RIS-UE channels are calculated and create scenarios for users with high mobility. It was found that the performance of the system depends on the location of the RIS and how many elements it consists of. As a result, the optimized algorithms helped to reduce the pilot signal header and their complexity. For instance, for an RIS-assisted MU-MISO system in [74], an optimized PPO-based algorithm was proposed, which used S-CSI, and the algorithm had a fast convergence compared to same category algorithms. In addition, for an RIS-assisted mMIMO system in [3], they proposed an optimized algorithm for high user mobility with efficient complexity O(MN\({}^{2}\) + N +M) and used S-CSI. According to the researchers, it is necessary to further study the methods in broadband systems, to study more the required number of RIS elements to have the maximum performance of the system and the window size to reduce the channel aging. The contribution of neural networks to channel estimation in RIS-assisted systems should be further investigated. In addition, there should be more scenarios for high user mobility versus channel aging. In our future work, we will simulate the mentioned algorithms for RIS-assisted MISO and MIMO systems, respectively, to confirm their optimization in terms of channel estimation. According to the settings of the systems used by these authors, but also by simulating them with other parameters. We hope this research provides information to researchers and professionals working on the new technologies of communication systems in order to further explore the problems that have emerged. Conceptualization, S.F.D. and N.I.M. ; methodology, S.F.D. ; validation, S.F.D., N.I.M., H.C.L. and P.A.K. ; investigation, S.F.D. ; resources, S.F.D. ; data curation, S.F.D., N.I.M., H.C.L. and P.A.K. ; writing--original draft preparation, S.F.D. ; writing, editing, S.F.D., N.I.M., H.C.L. and P.A.K. ; review H.C.L. ; supervision, P.A.K. All authors have read and agreed to the published version of the manuscript. This research received no external funding. **Institutional Review Board Statement:** Not applicable. **Informed Consent Statement:** Not applicable.