  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.
