Marwen Abdennebi

A new two-level scheduling algorithm for the downlink of LTE networks

The requirement of new mobile networks with ubiquitous broadband access has led the 3GPP (3rd Generation Partnership Project) to define the LTE (Long Term Evolution) system that represents an important step towards the 4G technology and brings new enhanced mechanisms with various integrated data services. The packet scheduling mechanisms play a major role to achieve this goal. So, we propose in this paper, a new scheduling algorithm that optimizes resources assignment in overbooking scenarios. This algorithm serves available resources by doing a trade-off between spectral efficiency, QoS (Quality of Service) requirements and fairness. The performances of our proposed scheme have been evaluated by using simulations. The analyses demonstrated the effectiveness of our approach by showing that it allowed a good level of fairness while improving at the same time the overall system capacity and performances of users having strict QoS requirements.

Service differentiation strategy based on MACB factor for M2M Communications in LTE-A Networks

One of the promising technologies which is being regarded in the future 5G standard long Term Evolution (LTE) Release 13 is Machine-to-Machine or M2M communications. It represents a key component of Internet of Things (IoT) and smart spaces. One of the most difficult challenges to support M2M communications is their huge number compared to available radio resources. Hence, to deal with random access channel (RACH) overload and to better control the access in LTE-A Networks, the 3GPP proposed the Access Class Barring (ACB) factor concept. In this paper, we proposed an algorithm to improve this method based on adaptive multiple ACB factors, according to M2M traffic category with respect to their access delay budget and drop rate (QoS parameters). Simulations were done for testing the effectiveness of our MACB scheme and show that using multiples ACB factors and dynamically adjusting them to the congestion level in addition to traffic type category increases the access probability and reduces overload. The obtained results were then compared to the basic ACB method and show that the access probability increases especially for high priority traffic.

Path planning of unmanned aerial vehicles with terrestrial wireless network tracking

The UAVs (Unmanned Aerial Vehicles) market is projected to grow, sustained by the technological progress in different domains related to UAVs and by the emergence of new civilian applications. However, this economical development might be held back due to increased regulation constraints. A major concern of public authorities is to ensure a safe sharing of the airspace, especially over populated areas. To reach this aim, a fundamental mechanism is to provide a permanent tracking of UAVs. In this paper, we investigate the path planning of autonomous UAVs with tracking capabilities provided by terrestrial wireless networks. We formalize this problem as a constrained shortest path problem, where the objective is to minimize the delay for reaching a destination, while ensuring a certain delivery ratio of messages reporting the drones positions.

Survey On Scheduling And Radio Resources Allocation In Lte

This paper focuses on an essential task of the enhanced NodeB eNodeB element in LTE architecture, the Radio Resource Manager RRM, which aims to accept or reject requests for connection to the network based on some constraints and ensuring optimal distribution of radio resources between Users Equipments UEs. Its main functionalities include Admission Control AC and Packet Scheduling PS. This paper will center mainly on the PS part of the RRM task, which performs the radio resource allocation in both uplink and downlink directions. Several approaches and algorithms have been proposed in the literature to address this need ie : allocate resources efficiently, the diversity and multitude of algorithms is related to the factors considered for the optimal management of radio resource, specifically, the traffic type and the QoS Quality of Service requested by the UE. In this article, an arts state of the radio resource allocation strategies and a detailed study of several scheduling algorithms proposed for LTE (uplink and downlink) are made. Therefore, we offer our evaluation and criticism.

Long - term radio resource reservation in IEEE 802.16 rtPS for video traffic

Radio resources management and scheduling are very important to provide QoS in WiMAX networks. Multimedia traffics are handled by the rtPS service where the BS can guarantee real time polling for resources allocation and re-allocation. However, even if the polling and the bandwidth requests are guaranteed, a bandwidth allocation in the next WiMAX frames could not be provided if no enough radio resources are available. It then results in important delay and/or losses. In this paper we aim to provide long-term bandwidth allocation for high priorities packets. This long-term allocation will be based on traffic prediction models. In our proposal, those requests will result in a kind of bandwidth provisioning in future WiMAX frames. We apply our proposal to H264 video traffic and simulation shows the benefits of our proposal in term of QoS.

Network selection using game theory

Heterogeneous Wireless Networks HWNs are combined networks made of different Radio Access Technologies RATs aiming to achieve the ABC (Always Best Connected) concept. In this context, users with multi interface terminal can connect to different wireless technologies such as 802.16, 802.11, UMTS, HSPA and LTE in the same time. The main issue of HWNs is the choice of the suitable access network from the available RATs list; this decision is called the network selection. Network selection process depend on several parameters such QoS, mobility, cost (money and battery-life)...etc. this paper propose a network selection model using game theory. The paper presents the network selection problem, after that, introduces the game theory models, and finally solving the network selection problem using the game theory framework.

A semi-persistent scheduling scheme for videotelephony traffics in the uplink of LTE networks

Recent studies have shown that in LTE Uplink, the handshake procedure consisting of a scheduling request message from the User Equipment and a scheduling grant from the eNB required twice a communication over the air interface and caused notable delay. It could be harmful for loss and latency-sensitive applications such as Videotelephony traffics. So, we propose in this paper a new scheme which improves resource allocation for Videotelephony traffics and reduce the delay caused by Dynamic scheduling. The key idea is to schedule Videotelephony traffics using a Semi-Persistent strategy with Provisioning. The performance of our proposed algorithm have been evaluated in real LTE environments with LTE-Sim and simulations results demonstrated its effectiveness by showing that it optimized Videotelephony traffics performance and provided the best QoS support compared to the Dynamic Scheduling.

A Flocking-Based on Demand Routing Protocol for Unmanned Aerial Vehicles

The interest shown by some community of researchers to autonomous drones or UAVs (unmanned aerial vehicles) has increased with the advent of wireless communication networks. These networks allow UAVs to cooperate more efficiently in an ad hoc manner in order to achieve specific tasks in specific environments. To do so, each drone navigates autonomously while staying connected with other nodes in its group via radio links. This connectivity can deliberately be maintained for a while constraining the mobility of the drones. This will be suitable for the drones involved in a given path of a given transmission between a source and a destination. This constraint could be removed at the end of the transmission process and the mobility of each concerned drone becomes again independent from the others. In this work, we proposed a flocking-based routing protocol for UAVs called BR-AODV. The protocol takes advantage of a well known ad hoc routing protocol for on-demand route computation, and the Boids of Reynolds mechanism for connectivity and route maintaining while data is being transmitted. Moreover, an automatic ground base stations discovery mechanism has been introduced for a proactive drones and ground networks association needed for the context of real-time applications. The performance of BR-AODV was evaluated and compared with that of classical AODV routing protocol and the results show that BR-AODV outperforms AODV in terms of delay, throughput and packet loss.

Bio-Inspired on Demand Routing Protocol for Unmanned Aerial Vehicles

The interest shown by some community of researchers to autonomous drones or UAVs (Unmanned Aerial Vehicles) has increased with the advent of wireless communication networks. These networks allow UAVs to cooperate more efficiently in an ad hoc manner in order to achieve specific tasks in specific environments. To do so, each drone navigates autonomously while staying connected with other nodes in its group via radio links. This connectivity can deliberately be maintained for a while constraining the mobility of the drones. This will be suitable for the drones involved in a given path of a given transmission between a source and a destination. This constraint could be removed at the end of the transmission process and the mobility of each concerned drone becomes again independent from the others. In this work, we have proposed a bio-inspired routing protocol for UAVs called BR- AODV. The protocol takes advantage of a well known ad hoc routing protocol for on-demand route computation, and the Boids of Reynolds mechanism for connectivity and route maintaining while data is being transmitted. The performances of BR-AODV were evaluated and compared to those of classical AODV routing protocol and the results show that BR-AODV outperforms AODV in terms of delay, throughput and packet loss.

A Heuristic Path Planning Approach for UAVs Integrating Tracking Support Through Terrestrial Wireless Networks

In this paper we propose a new approach based on a heuristic search for UAVs path planning with terrestrial wireless network tracking. In a previous work we proposed and exact solution based on an integer linear formulation of the problem. Unfortunately, the exact resolution is limited by the computation complexity. In this case, we propose in this paper a new approach based on a heuristic search. More precisely, a heuristic adaptive scheme based on Dijkstra algorithm is proposed to yield a simple but effective and fast solution. In addition, the proposed solution can cover a large area and generate a set of optimum and near optimum paths according to the drone battery capacities. Finally, the simulation results show that the drone tracking is sustainable even in noisy wireless network environment.