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

Network MIMO with Partial Cooperation between Radar and Cellular Systems

To meet the growing spectrum demands, future cellular systems are expected to share the spectrum of other services such as radar. In this paper, we consider a network multiple-input multiple-output (MIMO) with partial cooperation model where radar stations cooperate with cellular base stations (BS)s to deliver messages to intended mobile users. So the radar stations act as BSs in the cellular system. However, due to the high power transmitted by radar stations for detection of far targets, the cellular receivers could burnout when receiving these high radar powers. Therefore, we propose a new projection method called small singular values space projection (SSVSP) to mitigate these harmful high power and enable radar stations to collaborate with cellular base stations. In addition, we formulate the problem into a MIMO interference channel with general constraints (MIMO-IFC-GC). Finally, we provide a solution to minimize the weighted sum mean square error minimization problem (WSMMSE) with enforcing power constraints on both radar and cellular stations.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

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

A Utility Proportional Fairness Radio Resource Block Allocation in Cellular Networks

This paper presents a radio resource block allocation optimization problem for cellular communications systems with users running delay-tolerant and real-time applications, generating elastic and inelastic traffic on the network and being modelled as logarithmic and sigmoidal utilities respectively. The optimization is cast under a utility proportional fairness framework aiming at maximizing the cellular systems utility whilst allocating users the resource blocks with an eye on application quality of service requirements and on the procedural temporal and computational efficiency. Ultimately, the sensitivity of the proposed modus operandi to the resource variations is investigated

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