# Buffer-aided Resource Allocation for a Price Based Opportunistic Cognitive Radio Network

## TL;DR

This paper proposes a resource allocation framework for a cooperative cognitive radio network that maximizes revenue at the fusion center by optimally selecting users and allocating transmission times based on utility functions.

## Contribution

It introduces a novel optimization approach for resource allocation in cognitive radio networks considering revenue maximization and user selection.

## Key findings

- Optimized user selection improves revenue.
- The proposed method balances primary user activity and cognitive radio throughput.
- Simulation results demonstrate increased efficiency and revenue.

## Abstract

In this paper, a resource allocation problem for an opportunistic cooperative cognitive radio network is considered, where cognitive radio nodes send their hard decisions to the fusion center. The fusion center plays dual role, i.e., takes the global decision (i.e., decision about the primary user's activity) as well as allocates transmission time durations among cognitive radio nodes. Revenue based utility functions are considered at the fusion center and cognitive radio nodes. An optimization problem is formulated to maximize the fusion center's revenue while satisfying some well defined constraints. User selection among cognitive radio nodes is performed in order to make the optimization problem feasible.