# Physical Layer Latency Management Mechanisms: A Study for Millimeter-Wave Wi-Fi
## 5 Results
### Tuning the RX DBB Components  
The final part of the analysis explores the latency management mechanisms in the PHY, in addition to MCS switching. It firstly focuses on the demapper instance switching to establish the effects of different demapping algorithms on latency. Figure 11 shows the exact demapping algorithm noticeably delays data reception, especially when employing 64 QAM. The latency peaks at MCS indexes 10 and 12.3 correspond to an increase in constellation size from 4- to 16- and from 16- to 64 symbols. The switch from MCS index 5 to 6 does not add to latency because of similar demapper performance in both cases. Approximative demapping manages to substantially reduce the incurred latency and achieve equally low time delays at higher MCS indexes as decision threshold demapping. It does, however, include similar peaks at the points of constellation size increase as exact demapping. Increasing the number of parallel demappers would improve the throughput; yet, it would also bring with it unwanted effects such as larger area occupation, increased complexity, and higher cost. As discussed in Section 3.2.3, implementing the approximative demapper in 65- instead of in 90 nm technology could benefit its throughput and prevent it from becoming a bottleneck. On the other hand, decision threshold demapping reliably outpaces the approximative algorithm up to MCS index 10. From there on, it shows a higher spread of latency values, which are in some cases as high as those incurred during approximative demapping. However, the additional latency is generated by the decoder, posing a bottleneck at high MCS indexes and low \(\frac{E_{b}}{N_{0}}\) values, as demonstrated in Figure 10c. Hence, the decision threshold algorithm is the most timely of the three. The second part of the RX DBB tuning consists of incrementally setting the number of allowed LDPC decoder iterations. This is done in steps 1, 5, and 10 in iteration ranges 1-10, 1-50, and 50-100, respectively. Figure 12 summarizes the incurred MPDU latency and BER results for the corner case when allowing up to 100 iterations. The MCS-dependent latency values follow a similar trend to those presented in Figure 10c. The main difference is that there are no more linear dependencies at 100 allowed iterations. Consequently, achieving minimum latency at different \(\frac{E_{b}}{N_{0}}\) values requires even more frequent MCS switching. Maximum latency per-MCS in Figure 12a is observed at 100 incurred iterations; in the descending part of each curve, the number of iterations gradually falls towards 1. The corresponding BER values benefit from a maximum 1 dB coding gain when allowing  
Figure 10: Counterclockwise from top left: incurred BER during transmission (**a**); average number of executed decoding iterations (**b**); resulting MPDU latency (**c**). Obtained using the decision threshold demapper and allowing up to 10 LDPC decoding iterations. The dashed line in (**a**) represents the \(10^{-5}\) BER limit, as defined by 5G NR. up to 100 decoding iterations instead of 10. The results serve an exploratory purpose since the return on investment in terms of lower BER might not justify the higher power requirements for performing extra decoding iterations in practice. Minimal achievable MPDU latency is further elaborated in Figure 13. With reference to Figure 12a, only the lowest latency values and their corresponding MCSs are illustrated. This is repeated for 1 to 100 allowed decoding iterations. For a small number of iterations, the decoder never becomes a bottleneck and, therefore, MCS 12.5 always yields the lowest latency. The first improvements at other MCSs start to appear at 10 iterations. This is a consequence of the MCSs at higher indexes less likely to satisfy the early exit criterion--absence of detected bit errors within individual codewords--in presence of high noise levels, therefore, the RX must execute more time-consuming decoding iterations. Figure 11: MPDU latency for exact, approximative, and decision threshold demapping.