Context-Aware Resource Allocation in Cellular Networks

We define and propose a resource allocation architecture for cellular networks. The architecture combines content-aware, time-aware and location-aware resource allocation for next generation broadband wireless systems. The architecture ensures content-aware resource allocation by prioritizing real-time applications users over delay-tolerant applications users when allocating resources. It enables time-aware resource allocation via traffic-dependent pricing that varies during different hours of day (e.g. peak and off-peak traffic hours). Additionally, location-aware resource allocation is integrable in this architecture by including carrier aggregation of various frequency bands. The context-aware resource allocation is an optimal and flexible architecture that can be easily implemented in practical cellular networks. We highlight the advantages of the proposed network architecture with a discussion on the future research directions for context-aware resource allocation architecture. We also provide experimental results to illustrate a general proof of concept for this new architecture.Comment: (c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other work

An Optimal Application-Aware Resource Block Scheduling in LTE

In this paper, we introduce an approach for application-aware resource block scheduling of elastic and inelastic adaptive real-time traffic in fourth generation Long Term Evolution (LTE) systems. The users are assigned to resource blocks. A transmission may use multiple resource blocks scheduled over frequency and time. In our model, we use logarithmic and sigmoidal-like utility functions to represent the users applications running on different user equipments (UE)s. We present an optimal problem with utility proportional fairness policy, where the fairness among users is in utility percentage (i.e user satisfaction with the service) of the corresponding applications. Our objective is to allocate the resources to the users with priority given to the adaptive real-time application users. In addition, a minimum resource allocation for users with elastic and inelastic traffic should be guaranteed. Every user subscribing for the mobile service should have a minimum quality-of-service (QoS) with a priority criterion. We prove that our scheduling policy exists and achieves the maximum. Therefore the optimal solution is tractable. We present a centralized scheduling algorithm to allocate evolved NodeB (eNodeB) resources optimally with a priority criterion. Finally, we present simulation results for the performance of our scheduling algorithm and compare our results with conventional proportional fairness approaches. The results show that the user satisfaction is higher with our proposed method.Comment: 5 page

A Multi-Game Framework for Harmonized LTE-U and WiFi Coexistence over Unlicensed Bands

The introduction of LTE over unlicensed bands (LTE-U) will enable LTE base stations (BSs) to boost their capacity and offload their traffic by exploiting the underused unlicensed bands. However, to reap the benefits of LTE-U, it is necessary to address various new challenges associated with LTE-U and WiFi coexistence. In particular, new resource management techniques must be developed to optimize the usage of the network resources while handling the interdependence between WiFi and LTE users and ensuring that WiFi users are not jeopardized. To this end, in this paper, a new game theoretic tool, dubbed as \emph{multi-game} framework is proposed as a promising approach for modeling resource allocation problems in LTE-U. In such a framework, multiple, co-existing and coupled games across heterogeneous channels can be formulated to capture the specific characteristics of LTE-U. Such games can be of different properties and types but their outcomes are largely interdependent. After introducing the basics of the multi-game framework, two classes of algorithms are outlined to achieve the new solution concepts of multi-games. Simulation results are then conducted to show how such a multi-game can effectively capture the specific properties of LTE-U and make of it a "friendly" neighbor to WiFi.Comment: Accepted for publication at IEEE Wireless Communications Magazine, Special Issue on LTE in Unlicensed Spectru

An Application-Aware Spectrum Sharing Approach for Commercial Use of 3.5 GHz Spectrum

In this paper, we introduce an application-aware spectrum sharing approach for sharing the Federal under-utilized 3.5 GHz spectrum with commercial users. In our model, users are running elastic or inelastic traffic and each application running on the user equipment (UE) is assigned a utility function based on its type. Furthermore, each of the small cells users has a minimum required target utility for its application. In order for users located under the coverage area of the small cells' eNodeBs, with the 3.5 GHz band resources, to meet their minimum required quality of experience (QoE), the network operator makes a decision regarding the need for sharing the macro cell's resources to obtain additional resources. Our objective is to provide each user with a rate that satisfies its application's minimum required utility through spectrum sharing approach and improve the overall QoE in the network. We present an application-aware spectrum sharing algorithm that is based on resource allocation with carrier aggregation to allocate macro cell permanent resources and small cells' leased resources to UEs and allocate each user's application an aggregated rate that can at minimum achieves the application's minimum required utility. Finally, we present simulation results for the performance of the proposed algorithm.Comment: Submitted to IEE

A Utility Proportional Fairness Resource Allocation in Spectrally Radar-Coexistent Cellular Networks

Spectrum sharing is an elegant solution to addressing the scarcity of the bandwidth for wireless communications systems. This research studies the feasibility of sharing the spectrum between sectorized cellular systems and stationary radars interfering with certain sectors of the communications infrastructure. It also explores allocating optimal resources to mobile devices in order to provide with the quality of service for all running applications whilst growing the communications network spectrally coexistent with the radar systems. The rate allocation problem is formulated as two convex optimizations, where the radar-interfering sector assignments are extracted from the portion of the spectrum non-overlapping with the radar operating frequency. Such a double-stage resource allocation procedure inherits the fairness into the rate allocation scheme by first assigning the spectrally radar-overlapping resources