A Branch-and-Price Approach to a Variant of the Cognitive Radio Resource Allocation Problem
Hossein Falsafain, Mohammad Reza Heidarpour, Soroush Vahidi

TL;DR
This paper introduces a branch-and-price method for a complex spectrum allocation problem in cognitive radio networks, considering hardware constraints that limit spectrum aggregation range, and demonstrates its efficiency through numerical results.
Contribution
It presents a novel ILP formulation and a branch-and-price framework to efficiently solve the NP-hard MAR-constrained spectrum allocation problem.
Findings
LP relaxation bounds are very tight, enabling effective pruning.
The proposed method requires less computational effort than previous formulations.
Numerical results confirm the efficiency of the approach.
Abstract
Radio-frequency portion of the electromagnetic spectrum is a scarce resource. Cognitive radio technology has emerged as a promising solution to overcome the spectrum scarcity bottleneck. Through this technology, secondary users (SUs) sense the spectrum opportunities free from primary users (PUs), and opportunistically take advantage of these (temporarily) idle portions, known as spectrum holes. In this correspondence, we consider a variant of the cognitive radio resource allocation problem posed by Martinovic et al. in 2017. The distinguishing feature of this version of the problem is that each SU, due to its hardware limitations, imposes the requirement that the to-be-aggregated spectrum holes cannot be arbitrarily far from each other. We call this restriction as the Maximal Aggregation Range (MAR) constraint, and refer to this variant of the problem as the MAR-constrained hole…
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