Toward reliable and high-quality 6G communications: a two-phase evaluation of physical-layer metrics and QoE

The performance of 6G wireless communication systems is significantly affected by the combined effects of transmission power, communication distance, and modulation scheme selection; however, these elements are frequently examined in isolation, failing to connect physical-layer performance with user-perceived quality. This research presents a cohesive two-phase evaluation framework to bridge this gap by concurrently assessing signal-level performance and Quality of Experience (QoE). This framework evaluates the QPSK, 16QAM, and 64QAM at 20 dBm, 30 dBm, and 40 dBm at various communication distances for a 6G channel model that is frequency dependent and includes the combination of 3GPP Urban-Macro path loss, atmospheric molecular absorption at 100 GHz, and Rayleigh/Rician small-scale fading. SNR, BER and throughput are used to measure the performance in Phase I. The end-to-end delay, jitter, and MOS are used in Phase II, and are derived analytically from the ITU-T G.107.2 E-model and not considered as an independent output. Phase I and Phase II are not conceptually connected, but rather connected explicitly by an analytical coupling function. The results show that the longer the transmission distance, the lower the SNR, the less throughput, the higher the BER and the larger the delay/jitter, which effect is more significant at lower power levels. The higher the transmission power, the better the performance will be in all the measures. QPSK remains comparatively stable over long distances, while 16QAM and 64QAM achieve higher throughput under favorable conditions but are markedly more sensitive to signal degradation. The MOS results confirm a trade-off between transmission reliability and perceived quality. A newly added energy-efficiency analysis further shows that QPSK sustains a target MOS of 4 at 500 m at roughly one-third to one-half the energy cost per bit of 16QAM, and all reported trends are validated with 95% confidence intervals over 10,000 Monte Carlo trials per configuration. The suggested approach offers pragmatic insights for enhancing the reliability and quality of 6G communication systems.