2 citations · 2 across the 5 of their papers we have counts for
5 papers
ML-Assisted Bulk Resource Allocation: Custom Outage-Based Loss Function and Reliability Analysis
Amir Masoud Molaei, Nidhi Simmons, David E. Simmons +2
Machine learning (ML)-assisted outage-based resource allocation has recently emerged as an effective alternative to conventional scheduling methods in reliability-critical wireless…
To Trust or Not to Trust: On Calibration in ML-based Resource Allocation for Wireless Networks
Rashika Raina, Nidhi Simmons, David E. Simmons +2
In next-generation communications and networks, machine learning (ML) models are expected to deliver not only accurate predictions but also well-calibrated confidence scores that r…
Outage Performance and Novel Loss Function for an ML-Assisted Resource Allocation: An Exact Analytical Framework
Nidhi Simmons, David E Simmons, Michel Daoud Yacoub
We introduce a novel loss function to minimize the outage probability of an ML-based resource allocation system. A single-user multi-resource greedy allocation strategy constitutes…
AI-Based Channel Prediction in D2D Links: An Empirical Validation
Nidhi Simmons, Samuel B. Ferreira Gomes, Michel Daoud Yacoub +3
Device-to-Device (D2D) communication propelled by artificial intelligence (AI) will be an allied technology that will improve system performance and support new services in advance…
On Shadowing the - Fading Model
Nidhi Simmons, Carlos Rafael Nogueira da Silva, Simon L. Cotton +3
In this paper, we extensively investigate the way in which - fading channels can be impacted by shadowing. A family of shadowed - fading models are introduced and class…