# Proportional Fair RAT Aggregation in HetNets

**Authors:** Ehsan Aryafar, Alireza Keshavarz-Haddad, Carlee Joe-Wong

arXiv: 1906.00284 · 2019-06-04

## TL;DR

This paper proposes a simple distributed algorithm for resource allocation in multi-RAT HetNets that achieves proportional fairness, ensuring improved throughput and fairness without requiring inter-BS coordination.

## Contribution

It introduces a novel distributed resource allocation algorithm for multi-RAT HetNets that guarantees convergence to proportional fairness without inter-BS coordination.

## Key findings

- The algorithm converges to the proportional fairness solution.
- It provides bounds on convergence speed.
- The algorithm's outcomes are proven to be optimal.

## Abstract

Heterogeneity in wireless network architectures (i.e., the coexistence of 3G, LTE, 5G, WiFi, etc.) has become a key component of current and future generation cellular networks. Simultaneous aggregation of each client's traffic across multiple such radio access technologies (RATs) / base stations (BSs) can significantly increase the system throughput, and has become an important feature of cellular standards on multi-RAT integration. Distributed algorithms that can realize the full potential of this aggregation are thus of great importance to operators. In this paper, we study the problem of resource allocation for multi-RAT traffic aggregation in HetNets (heterogeneous networks). Our goal is to ensure that the resources at each BS are allocated so that the aggregate throughput achieved by each client across its RATs satisfies a proportional fairness (PF) criterion. In particular, we provide a simple distributed algorithm for resource allocation at each BS that extends the PF allocation algorithm for a single BS. Despite its simplicity and lack of coordination across the BSs, we show that our algorithm converges to the desired PF solution and provide (tight) bounds on its convergence speed. We also study the characteristics of the optimal solution and use its properties to prove the optimality of our algorithm's outcomes.

## Full text

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## Figures

13 figures with captions in the complete paper: https://tomesphere.com/paper/1906.00284/full.md

## References

28 references — full list in the complete paper: https://tomesphere.com/paper/1906.00284/full.md

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Source: https://tomesphere.com/paper/1906.00284