## 5 Discussion  
In the realm of digital communication systems, the implementation of a rate of 2/3 for the QC-LDPC decoder architecture brings substantial advantages, particularly in terms of area efficiency. This architecture, by design, allows for a more compact layout, thereby reducing the system's overall footprint. This area reduction not only leads to cost savings in  
Figure 9: Resource utilization report (Flow_AreaOptimized_high) of the proposed decoder. terms of hardware, but also contributes to lower power consumption and heat dissipation, which are critical factors in the design and operation of efficient communication systems. Therefore, choosing a rate of 2/3 can be a strategic decision in creating compact, cost-effective, and efficient communication systems. Figure 10 presents the different timing constraints based on the Flow_AreaOptimized_high. The worst negative slack (WNS) represents the maximum delay violation in our design. We can explain it as the amount by which our circuit's slowest path fails to meet the required timing constraints. The total number of endpoints significantly impacts the complexity of our digital design. More endpoints mean more connectivity within a design, more resource consumption, and more complex routing structures. As presented in Figure 10, our design met all the specified timing constraints for a maximum operating frequency of 304.5 MHz. Furthermore, our design has a total of four endpoints, resulting in a flexible, low-complexity, and area-efficient design implementation. The implementation's peak frequency signifies swift processing rates and diminished data transmission delays. This equates to approximately 3.28 nanoseconds for each cycle, demonstrating the system's capacity to execute tasks in a high-performance computing setting where rapidity and effectiveness are crucial. This is particularly advantageous for applications requiring real-time processing and quick response times. The profiling reports of resource utilization and timing consumption are presented as follows. Figure 11a illustrates that the top_rd block is the most time-consuming, accounting for 62% of the total timing. This is a significant majority compared to the other components, with memories consuming 37%, the CNPU consuming only 1%, and the VN and LLR not consuming any measurable timing. Figure 11b shows a similar distribution, with top_rd utilizing a dominant 90% of the resources. The CNPU accounts for 5%, top_wt for 4%, and memories for 1%, whereas \"LLR\" and \"VN\" do not use any resources. These charts highlight the disproportionate impact of the \"top_rd\" block on both timing and resource allocation within the decoder system, indicating its critical role and a potential area for optimization. Table 3 provides a comparative analysis of performance metrics with the current state-of-the-art. The decoder presented here has multiple advantages. It boasts a peak frequency of 304.5 MHz, surpassing the performance of references [2,4] and approaching [3,5]. It also shows a notable normalized throughput enhancement of 17.8 Gbps. Distinct from reference [2], our design does not use any DSPs, suggesting a more efficient design with potentially lower power consumption and complexity. The code rate stands at 2/3, on equal footing with competing references, maintaining comparable error correction strength. Moreover, this decoder is characterized by a distinctive channel length of 13,440 bits and a memory allocation of 231.35 kb, underscoring its tailored optimization for particular use cases. Registers were used for memory storage, as opposed to BRAMs used by others, and resulted in faster access times. Overall, this research stands out due to its higher performance, efficient hardware usage, and innovative design choices, making it a strong candidate for the high-performance demands of 5G-NR protocols. Although the research  
Figure 10: Timing report of the implemented design in nanoseconds, with blue color indicating an acceptable worst slack.