An optimisation model for minimising changes in frequency allocations

In this paper we deal with a problem associated with frequency assignment. Suppose we have a number of transmitters, each of which has been allocated a frequency. The problem we consider is how, given one (or more) transmitters are requesting a new frequency allocation, for example because of the interference they are currently suffering, to decide the new frequencies. Here we wish to constrain overall interference, but minimise the number of frequency changes needed for transmitters that have not requested a change.We present an optimisation model for frequency allocation that minimises changes in the existing allocation, whilst limiting interference. We consider the standard mathematical representation of interference in the literature and show that we can represent it in a way that involves far fewer variables and constraints.We make use of this new representation of interference in our zero-one integer linear program for deciding a new frequency allocation. We also show how our formulation can be adapted to deal with a number of other possibilities, specifically allocating frequencies to new transmitters with known locations and also deciding a location (and frequency) for a single new transmitter.We present computational results for our approach making use of minimum interference frequency assignment test problems taken from the literature. We compare the results from our new representation of interference with those obtained using the standard representation.(c) 2022 The Author(s). Published by Elsevier Ltd on behalf of Association of European Operational Research Societies (EURO). This is an open access article under the CC BY-NC-ND license

Automated summary

This paper addresses the problem of frequency assignment, specifically how to decide new frequency allocations while limiting interference and minimizing changes to the existing allocation. The authors propose an optimization model that minimizes changes and simplifies the representation of interference. They also explore adaptations for other scenarios and present computational results comparing their approach to the standard representation.