The phrase "assuming error" is correct and usable in written English.
It can be used in contexts where you want to indicate that you are considering the possibility of an error occurring in a situation or calculation.
Example: "Assuming error in the measurements, we should adjust our calculations accordingly."
Alternatives: "assuming a mistake" or "considering an error".
Results from comparing a logit model assuming error-free inputs and the integrated hybrid model revealed significant impacts on the generated policy scenarios.
Strong consistency of the least-squares estimates in stochastic regression models is established assuming errors with variance not necessarily defined.
Assuming error-free transmission in wireless networks is not reasonable and the extension of network coding to wireless networks is not straightforward.
The fact that we have two independent paths from the relays to the destination allows us to achieve diversity, assuming error-free links from source to relays.
The analytical PEP derivation is corroborated by the BER performance obtained through Monte Carlo simulations, for the RA scheme with 1 antenna in each relay, assuming error-free transmission between BS and the RNs.
We observe that differences between this case and assuming error-free links until the relays are not significant, differing less than 1.5 dB, for BER = 10-3, independently of the considered scenario.
Assuming error-prone channel conditions, we derive probability distributions for frame backoff time, waiting time in queue, collision probability of a transmission, and normalized throughput for each channel and each data class with different transmission rates depending on the vehicle's distance from the RSU.
However, we want to draw attention to the fact that the MSE of the conventional scheme is evaluated assuming error-free feedback of the CSI from the relay to the users; therefore, the curve in the graph represents the lower-bound limit.
Therefore, we can conclude that even assuming errors, the utilization of tag estimators is worth to be considered.
Linear regression models were fitted using the Prais-Winsten Generalised Least Squares method, assuming errors have a first-order autocorrelation structure.
