Robust Resource Allocation with Joint Carrier Aggregation for Multi-Carrier Cellular Networks

TL;DR

This paper introduces a robust, utility-based resource allocation algorithm for multi-carrier cellular networks that ensures fair, optimal distribution of resources among users with different traffic types, adapting to traffic conditions.

Contribution

It proposes a novel, distributed algorithm for joint carrier aggregation that prevents resource allocation fluctuations and guarantees minimum QoS based on application type.

Findings

Algorithm prevents fluctuations in resource allocation.

Provides traffic-dependent pricing for network providers.

Achieves optimal rates for users in various traffic scenarios.

Abstract

In this paper, we present a novel approach for robust optimal resource allocation with joint carrier aggregation to allocate multiple carriers resources optimally among users with elastic and inelastic traffic in cellular networks. We use utility proportional fairness allocation policy, where the fairness among users is in utility percentage of the application running on the user equipment (UE). Each UE is assigned an application utility function based on the type of its application. Our objective is to allocate multiple carriers resources optimally among users subscribing for mobile services. In addition, each user is guaranteed a minimum quality of service (QoS) that varies based on the user's application type. We present a robust algorithm that solves the drawback in the algorithm presented in [1] by preventing the fluctuations in the resource allocation process, in the case of scarce resources, and allocates optimal rates for both high-traffic and low-traffic situations. Our distributed resource allocation algorithm allocates an optimal rate to each user from all carriers in its range while providing the minimum price for the allocated rate. In addition, we analyze the convergence of the algorithm with different network traffic densities and show that our algorithm provides traffic dependent pricing for network providers. Finally, we present simulation results for the performance of our resource allocation algorithm.