Multi-application resource allocation with users discrimination in cellular networks

Abstract

Abstract-In this paper, we consider resource allocation optimization problem in cellular networks for different types of users running multiple applications simultaneously. In our proposed model, each user application is assigned a utility function that represents the application type running on the user equipment (UE). The network operators assign a subscription weight to each UE based on its subscription. Each UE assigns an application weight to each of its applications based on the instantaneous usage percentage of the application. Additionally, UEs with higher priority assign applications target rates to their applications. Our objective is to allocate the resources optimally among the UEs and their applications from a single evolved node B (eNodeB) based on a utility proportional fairness policy with priority to realtime application users. A minimum quality of service (QoS) is guaranteed to each UE application based on the UE subscription weight, the UE application weight and the UE application target rate. We propose a two-stage rate allocation algorithm to allocate the eNodeB resources among users and their applications. Finally, we present simulation results for the performance of our rate allocation algorithm.

Robust Resource Allocation With Joint Carrier Aggregation in Multi-Carrier Cellular Networks

“…To incorporate the carrier aggregation feature, we have introduced a multi-stage resource allocation using carrier aggregation in [9]. In [22] and [23], we present resource allocation with users discrimination algorithms to allocate the eNodeB resources optimally among mobile users with elastic and inelastic traffic. In [24], the authors have presented a radio resource block allocation optimization problem using a utility proportional fairness approach.…”

Optimal power allocation for LTE users with different modulations

“…In our model, we use the normalized sigmoidal-like utility functions, as in [19] and [20], it can be expressed as…”

A QoS-based power allocation for cellular users with different modulations

“…It is a function of the transmitter power. It looks like sigmoidal-like function, therefore we can use the normalized sigmoidal-like utility function, as in [3] and [4]:…”

“…The utility function is a representation of each UE's QoS and it is a function of its power allocation. Earlier in [3] and [4], the utility function has been approximated as a sigmoidal-like function. The goal is therefore to maximize the network utility which is a product of all users' utilities.…”