The in-service measurable block-error-rate (BLER) is the only transmission performance indicator aimed for wireless network operators to test the physical-layer of the long-term evolution and the emerging 5G new radio systems, both utilizing the orthogonal frequency-division multiplexing (OFDM). However, the small so obtained BLER values may not be accurate, which compromises estimation of the residual channel that the physical layer delivers to higher-layer protocols, finally affecting the application-layer performance and efficiency. Moreover, this is not the only reason why the out-of-service testing of the bit-error-rate (BER)—still the ultimate physical-layer performance indicator representing the probability of a bit error, remains inevitable in research, development and equipment manufacturing. Specifically, it is often needed to estimate the peak OFDM performance usually referred to as error floor or residual BER (which can be used for BLER estimation), straight from common and physically interpretable parameters. So, in this paper, after identifying the optimal sample instant in a power delay profile, the sub-optimal sampling just upon the first pulse arrival, is found to add minor residual BER degradation, and therefore can be adopted to provide a simple OFDM error floor prediction that is linear with the rms delay spread. The proposed model is verified by Monte Carlo simulations.

服务中可测量的误块率（BLER）是旨在无线网络运营商测试长期演进的物理层和新兴5G新无线电系统的唯一传输性能指标，两者均利用正交频率-除法复用（OFDM）。但是，如此获得的较小的BLER值可能不准确，这损害了对物理层传递给高层协议的剩余信道的估计，最终影响了应用程序层的性能和效率。此外，这并不是为什么误码率（BER）停止服务测试（仍然是代表误码率的最终物理层性能指标）仍是研究，开发和开发中不可避免的原因。设备制造。特别，通常需要直接根据常见的和可物理解释的参数来估算通常称为误码本底或残留BER（可用于BLER估算）的峰值OFDM性能。因此，在本文中，在确定了功率延迟曲线中的最佳采样时刻之后，发现刚好在第一个脉冲到达时的次优采样会增加较小的残留BER退化，因此可以用来提供简单的OFDM错误与均方根延迟扩展呈线性关系的下限预测。提出的模型通过蒙特卡洛仿真验证。发现刚好在第一个脉冲到达时进行次优采样会增加较小的残留BER降级，因此可以采用该采样来提供与rms延迟扩展呈线性关系的简单OFDM错误底限预测。提出的模型通过蒙特卡洛仿真验证。发现刚好在第一个脉冲到达时进行次优采样会增加较小的残留BER降级，因此可以采用该采样来提供与rms延迟扩展呈线性关系的简单OFDM错误底限预测。提出的模型通过蒙特卡洛仿真验证。