In this work, we present a tutorial on how to account for the computational time complexity overhead of signal processing in the spectral efficiency (SE) analysis of wireless waveforms. Our methodology is particularly relevant in scenarios where achieving higher SE entails a penalty in complexity, a common trade-off present in 6G candidate waveforms. We consider that SE derives from the data rate, which is impacted by time-dependent overheads. Thus, neglecting the computational complexity overhead in the SE analysis grants an unfair advantage to more computationally complex waveforms, as they require larger computational resources to meet a signal processing runtime below the symbol period. We demonstrate our points with two case studies. In the first, we refer to IEEE 802.11a-compliant baseband processors from the literature to show that their runtime significantly impacts the SE perceived by upper layers. In the second case study, we show that waveforms considered less efficient in terms of SE can outperform their more computationally expensive counterparts if provided with equivalent high-performance computational resources. Based on these cases, we believe our tutorial can address the comparative SE analysis of waveforms that operate under different computational resource constraints.

翻译：本文提出了一种在无线波形频谱效率分析中考虑信号处理计算时间复杂度的教程方法。我们的方法特别适用于追求更高频谱效率必然伴随复杂度代价的场景，这是6G候选波形中普遍存在的权衡关系。我们认为频谱效率源自数据速率，而数据速率受时间相关开销的影响。因此，在频谱效率分析中忽略计算复杂度开销会赋予计算更复杂的波形不公平的优势，因为它们需要更多计算资源才能满足符号周期内的信号处理运行时间。我们通过两个案例研究来论证这一观点。在第一个案例中，我们引用文献中符合IEEE 802.11a标准的基带处理器，表明其运行时间会显著影响上层感知的频谱效率。在第二个案例研究中，我们证明若获得等效的高性能计算资源，那些在频谱效率方面被认为较差的波形可能超越计算成本更高的对应方案。基于这些案例，我们相信本教程能够解决在不同计算资源约束下运行的波形之间的比较性频谱效率分析问题。