# All-Integer Quantization for Low-Complexity Min-Sum Successive Cancellation Polar Decoder
## 7 Conclusions  
Quantization plays a crucial role in making polar decoders feasible for real-world applications. Among various quantization techniques, all-integer quantization stands out as a highly efficient approach that significantly reduces computational complexity, making it well suited to hardware-constrained environments. While it is computationally challenging, it eliminates the need for floating-point operations, ensuring faster and more energy-efficient decoding in practical implementations. This study demonstrates that all-integer quantization is particularly effective for MS-SC decoders. Specifically, a 5-bit all-integer quantization closely approximates the performance of infinite-precision decoding while maintaining computational efficiency. Our results confirm that this method remains viable even in fading channels, with a negligible performance gap of 0.2 dB compared to floating-point calculations, making it highly efficient for practical implementation. Additionally, integer-based computations can reduce computational complexity by up to 75%, making decoding significantly more efficient. The proposed all-integer quantization method enables substantial reductions in hardware resource requirements, making it particularly valuable for resource-constrained environments. This method is applicable to low-power systems such as IoT devices, wireless sensor networks, and storage systems, where hardware complexity, energy efficiency, and error correction accuracy are prioritized, respectively. By eliminating complex floating-point arithmetic, this approach aligns well with the growing demand for energy-efficient, real-time decoding solutions in modern communication systems. Future research could explore methods to mitigate precision loss, such as nonuniform quantization approaches that combine integer techniques and nonuniform quantization schemes to balance complexity and accuracy. Quantization techniques could also be applied to SC-flip decoding and SCL decoding to further enhance the decoding performance. Additionally, further studies should assess the real-world hardware implementations of this method across various communication systems to ensure robustness and adaptability in diverse practical scenarios.  
Overall, the proposed all-integer quantization method for MS-SC decoding offers a promising balance between performance and hardware efficiency. As communication systems continue to evolve, this approach presents a compelling solution to meet the increasing demand for low-latency and energy-efficient decoding methods in next-generation networks.  
Conceptualization, W.P. and P.S.; methodology, W.P.; software, W.P.; validation, P.S., V.I. and P.M.; formal analysis, P.S.; investigation, W.P.; resources, W.P.; data curation, W.P.; writing--original draft preparation, W.P.; writing--review and editing, V.I., P.S. and P.M.; visualization, W.P.; supervision, V.I.; project administration, V.I.; funding acquisition, V.I. All authors have read and agreed to the published version of the manuscript.  
The research presented in this work received financial support from the Royal Golden Jubilee Ph.D. Program under Grant No. PHD/0033/2559.  
Not applicable.  
The raw data supporting the conclusions of this article will be made available by the authors on request.  
We would also like to express our gratitude to Professor [PERSON] and his laboratory team in Yokohama National University for their valuable knowledge and technical support to this work.  
The authors declare no conflicts of interest.