Abdallah Moubayed

Wireless Resource Virtualization With Device-to-Device Communication Underlaying LTE Network

Wireless resource virtualization is a potential solution for meeting the increasing demand for mobile data services. Virtualization allows for more efficient utilization of the spectrum, reduces capital expenditures and operating expenditures, and can support higher peak rates. Device-to-device (D2D) communication as an underlay to cellular networks is also a potential solution to satisfy the data demand. Due to the proximity of devices and thus the higher signal-to-interference and noise ratio, higher data rates can be achieved using D2D communication. This is beneficial in cases of multimedia sharing where data can be broadcast to several nearby users. However, the interference that D2D pairs introduce to cellular users should be below a target threshold so as not to reduce their performance. In this paper, the problem of wireless resource virtualization with D2D communication underlaying the LTE network is formulated. Since the problem is an integer non-linear programming problem, it is divided into two smaller linear integer programs that are solved to optimality. Two lower complexity heuristic algorithms, each solving one of the subproblems are introduced. Results show that the heuristic achieves close to optimal results while having a much lower computational complexity.

Efficient Low-Complexity Scheduler for Wireless Resource Virtualization

This letter proposes an efficient low-complexity scheduler to virtualize the wireless resource blocks (RBs) and share them between users of multiple mobile network operators (MNOs). The scheduler aims at maximizing the throughput while maintaining access proportional fairness (APF) among users as well as MNOs. Normalized signal-to-noise ratio (SNR) selection criterion is used to impose APF between the users of each MNO, while APF between MNOs is maintained by assigning different weights to the normalized SNRs. The optimal weights for all MNOs are computed offline using iterative search method. Analytical and simulation results show that the proposed scheme can maintain APF at the user and MNO levels. Moreover, the throughput of the proposed scheduler is consistently higher than in the static sharing scenario.

Virtualized allocation performance analysis in 5G two-tier cellular networks

Enhancement of quality of services (QoS) parameters is a challenging requirement in the Fifth Generation (5G) networks. Delay sensitive applications such as voice over internet protocol, online gaming, and live video are easily affected especially in high data traffic with limited available resources. Moreover; virtualization in standard long term evolution (LTE) systems is considered as an integral promising solution in the next generation networking architecture. In this paper, we aim to enhance the delay performance of such applications by utilizing the extra resources available in two-tier cellular network architecture with macro- and micro-cells. Virtualization is considered by allowing users belonging to the macro-cell to be allocated resources of the micro-cell when located in the micro-cell range. The average delays for various traffic types are evaluated to verify the frameworks performance effectiveness before and after resources sharing scenario. Simulation results show that the proposed framework considerably reduces UEs average delay when compared with the non-sharing scheme.

Power-Aware Wireless Virtualized Resource Allocation with D2D Communication Underlaying LTE Network

To meet the increasing mobile data services de- mand, several solutions have been proposed such as wireless resource virtualization and device-to-device (D2D) communica- tion. Virtualization allows for more efficient utilization of the spectrum, reduces expenditures, and can support higher peak rates. D2D communication can achieve higher data rates due to the proximity of devices while controlling the interference it causes to cellular communication. However, the increase in data rate multimedia demand has led to an increase in global energy consumption. Thus, it is crucial to employ more energy- aware schemes as this would provide both environmental and financial gains for service providers. In this paper, we extend our work in [1] by formulating the problem of power-aware wireless resource virtualization with D2D communication underlaying the LTE network. Since the problem is a mixed integer non-linear programming problem (MINLP), it is divided into four smaller linear programs, each of which is solved to optimality. Two lower complexity heuristic algorithms to solve the power allocation problems are introduced. Results show significant savings at both eNodeB and D2D devices.

Towards Intelligent LTE Mobility Management through MME Pooling

Long term evolution (LTE) is a leading mobile technology that provides very high speeds, low latency, and better quality-of-service (QoS). However, because of the exponential growth in the number of mobile users, the variety of new handheld devices, and the incremental use of different applications, the core network experiences a significant signaling overhead. This demand requires the design of intelligent, optimized mobility management methods. The present work attempts to overcome signaling overhead expansion and to define the fundamental basis for designing a tracking area list (TAL). In this context, we differ from other studies by introducing a model that relates the tracking area list to the mobility management entity (MME) which enables more control and adds intelligence to the system. Two MME pooling schemes are investigated namely, centralized and distributed MME schemes. The proposed model is NP-hard; thus, the problem can be simplified with a few assumptions (which do not violate the constraints of the problem) to become a solvable linear problem (LP). Moreover, a low-complexity heuristic algorithm is developed by determining the percentage use of the lists/MME in each cell. The results show that the centralized scheme outperforms the distributed one. Also, the heuristic algorithm offers sub-optimal results when compared to the LP solution.

QoS-Aware Energy and Jitter-Efficient Downlink Predictive Scheduler for Heterogeneous Traffic LTE Networks

Energy-efficient communications have become one fundamental aspect for todays cutting-edge wireless technologies due to its valuable impact on the environment. In this paper, we augment our earlier study for the user equipments (UE) energy efficiency (EE) in the long-term evolution (LTE) downlink by looking at real-time heterogeneous traffic QoS requirements. In particular, we utilize the previously proposed cloud radio access network (C-RAN) and ray tracing (RT)-based scheduling model to optimize both of the EE and the packet delay jitter for real-time applications with fixed packet delay budget subject to other traffic types requirements. Using the utility-based scheduling approach, we formulate the resource allocation problem as a weighted sum binary integer programming (BIP) problem. Due to the inherent complexity of the problem formulation which hinders finding its solution directly, four heuristic algorithms are proposed to solve the optimization problem. Numerical simulations are conducted on three different traffic types each belonging to one of the popular QoS classes; best-effort class, rate, and delay-constrained classes. The obtained results demonstrate a substantial improvement in the systems performance achieved by our proposed schemes compared to other existing schemes.