Downsampling (taking every Dth sample and discarding the rest) is an identical process to sampling a continuous time signal; so you approach the continuous time signal as your sampling rate is increased. So you can access the impact of a lower sampling rate by simply downsampling a signal that has a higher number of samples.
Note that down-sampling and sampling does not distort a signal that only occupies a spectrum that is contained within 0 to $F_s/2$ for a real signal and 0 to $F_s$ for a complex signal, as well as any integer multiple of the ranges (where $F_s$ is the sampling rate. Distortion does come from aliasing and quantization noise. Aliasing occurs when there are additional signal or noise components in other frequencies prior to sampling (or downsampling) other than the range of interest, and quantization noise is the error from quantizing each sample directly (or in the case of a sampled/quantized signal that you are downsampling if you further round or truncate this would have the same quantization noise effect). This quantization noise is often well approximated as a uniform white noise process, meaning it's energy is equally distributed across all frequencies: If you increase the sampling rate, the same energy is spread across more frequencies, so the energy per unit bandwidth goes down. If your signal occupies a fixed bandwidth, a higher sampling rate will reduce the amount quantization noise in-band and thus increase SNR if the noise is limited by the quantization noise component (and assuming the out-of-band noise is further filtered digitally after sampling).
To combat aliasing we require anti-alias filtering prior to the sampling process. This would be a low pass filter when the signal of interest occupies the range of $0$ to $F_s/2$ (for the real case) or could be a bandpass filter when the signal of interest is at a higher frequency in which case the sampler also serves as the down-conversion. As we make the sampling rate lower, we place a stricter requirement on filter design - but given a realizable filter with sufficient rejection of the signals that can alias the quantization noise effect detailed earlier would be the only performance impact.
There are also reasons of convenience to choose a particular sampling rate- for example it is common in many implementations to use a sampling rate of 2 samples per symbol- this works well with certain timing recovery implementations and allows for simple derivation of the symbol clock was the delay offset is corrected.
I further detail performance versus sampling rate in this post: What are advantages of having higher sampling rate of a signal?