[D] Benefits of ML in signal processing
There is plenty of research on ML in signal processing. The majority of it, so it seams to me, is about showing feasibility of ML-based receivers (end-to-end or individual functional blocks of). To me, we are past that – pretty much everybody realizes that ML-based OFDM receiver is possible and can probably achieve comparable performance to that of a conventional receiver. Furthermore, even if/when someone manages to show some (probably marginal) performance gain, that would probably have academic value, but not much beyond that.
To me, there are two fundamental questions, for which I haven’t found answers in the literature and would really appreciate some pointers:
- Can ML-based receiver achieve comparable performance with comparable complexity (to these of a conventional receiver)?
- Beyond (probably marginal) performance gains, what can be commercial benefits of switching from a conventional receiver to an ML-based one?