Alexandre Ragaleux

Bio: Alexandre Ragaleux is an academic researcher from University of Paris. The author has contributed to research in topics: Wireless network & Scheduling (computing). The author has an hindex of 3, co-authored 3 publications receiving 32 citations.

Standard-Compliant LTE-A Uplink Scheduling Scheme With Quality of Service

Abstract: In this paper, we focus on uplink scheduling with the practical constraints imposed by the Long-Term Evolution/Long-Term Evolution-Advanced (LTE/LTE-A) standard. We consider multimedia traffic generated by mobile users with heterogeneous quality-of-service (QoS) requirements. To tackle the resulting time and frequency problem, we then propose an adaptive and potential aware scheduling scheme (APASS), which is standard compliant and covers a wide range of scheduling objectives. This scheduling scheme is composed of three algorithms, which work jointly to provide an efficient solution. Our performance evaluation shows that the APASS outperforms other state-of-the-art scheduling schemes in terms of user satisfaction and delay.

Adaptive and Generic Scheduling Scheme for LTE/LTE-A Mobile Networks

Abstract: Schedulers for multi-carrier wireless networks are a central element of cellular systems and are subject to extensive research. However, state-of-the-art schedulers are hardly implementable in a real system such as long term evolution advanced (LTE-A), which imposes additional constraints on how resources are allocated. To address this problem, we first propose adaptive and generic scheduling scheme (AGSS) a generic resource allocation procedure that enables the implementation of state-of-the-art scheduling policies for building a LTE scheduler. In a second step, we propose our own scheduling policy called opportunistic PDOR aware (OPA) that both optimizes the use of the radio spectrum and provides the quality of service actually expected by applications. We show how to implement this policy using our generic scheduling scheme. We then compare the performance of AGSS to the classic scheme in a LTE environment when used with a given policy. We show that the proposed scheme outperforms the classic scheme whatever the policy. We also establish that OPA offers the best performances in terms of capacity and quality of service compared to state-of-the-art policies.

An efficient and generic downlink resource allocation procedure for pre‐5G networks

Abstract: This paper addresses the downlink resource allocation problem in pre-5G (LTE-B) networks. At each time slot, the problem is to share the radio resources between users in order to maximize a given objective function. We expressed this problem considering the LTE standard constraints, which are rarely considered in the literature. Mainly, for any given user, the base station is constrained to transmit with a single Modulation and Coding Scheme (MCS). We show that this problem is NP-Hard, and therefore, we propose a generic approximation algorithm which covers a large variety of objectives. This algorithm is composed of three routines that enable an effective resource sharing procedure. The first routine computes a solution for a relaxation of our main problem, while the second routine selects the most suitable MCS for each user. Finally, the last routine effectively distributes the unallocated resources. For the Max Rate policy, simulation results show that our algorithm outperforms other existing algorithms in terms of capacity, and remains close to the optimal. Under the Proportional Fairness policy, our solution also provides a very good fairness while maintaining a near-optimal capacity.

An Improved Radio Resource Management with Carrier Aggregation in LTE Advanced

Abstract: Long term evolution-advanced (LTE-A) system introduces carrier aggregation (CA) technique to improve the user throughput by aggregating multiple component carriers (CCs). Previous research works related to downlink radio resource allocation with carrier aggregation have not considered the delay factor and the error probability. Therefore, the previous methods are unable to provide better quality of service (QoS) compared to the LTE-A standard. This paper considers the radio resource management problem by zooming into the head of line delay, probability of packet loss, and the delay threshold for different types of data. In doing this, several constraints are imposed following the specifications of LTE-A system. Hence, an improved method is developed in this study to enhance the system throughput and to maintain the computational complexity. Extensive simulations were carried out with other well-known methods to verify the overall performance of the proposed method. The result obtained indicates that the proposed method outperforms the previous methods in the measurement of average user throughput, average cell throughput, fairness index, and spectral efficiency.

Joint Energy and QoS-Aware Memetic-Based Scheduling for M2M Communications in LTE-M

Abstract: As a result of the increasing number of machine-type devices connected through the Internet, several challenges remain to date to support machine-to-machine (M2M) communications over long term evolution (LTE) cellular networks. In this paper, we tackle one important challenge of scheduling M2M traffic in uplink over LTE-M mobile networks. We propose a novel cross-layer scheme that considers packet scheduling in time and frequency domain using a memetic-based algorithm and aims to optimize resource allocation of M2M devices by considering their quality of service (QoS) needs while minimizing at the same time their energy consumption. After integrating an energy module for LTE in NS3 simulator, we perform simulations in a realistic M2M scenario and we evaluate the results which show how our proposed scheduling scheme outperforms other existing scheduling methods from the literature such as round robin and proportional-fair algorithms in terms of throughput, energy consumption and the percentage of satisfied devices with regard to their delay and throughput requirements.

Content-Sensing Based Resource Allocation for Delay-Sensitive VR Video Uploading in 5G H-CRAN

Abstract: Virtual reality (VR) is emerging as one of key applications in future fifth-generation (5G) networks. Uploading VR video in 5G network is expected to boom in near future, as general consumers could generate high-quality VR videos with portable 360-degree cameras and are willing to share with others. Heterogeneous networks integrating with 5G cloud-radio access networks (H-CRAN) provides high transmission rate for VR video uploading. To address the motion characteristic of UE (User Equipments) and small cell feature of 5G H-CRAN, in this paper we proposed a content-sensing based resource allocation scheme for delay-sensitive VR video uploading in 5G H-CRAN, in which the source coding rate of uploading VR video is determined by the centralized RA scheduling. This scheme jointly optimizes g-NB group resource allocation, RHH/g-NB association, sub-channel assignment, power allocation, and tile encoding rate assignment as formulated in a mixed-integer nonlinear problem (MINLP). To solve the problem, a three stage algorithm is proposed. Dynamic g-NB group resource allocation is first performed according to the UE density of each group. Then, joint RRH/g-NB association, sub-channel allocation and power allocation is performed by an iterative process. Finally, encoding tile rate is assigned to optimize the target objective by adopting convex optimization toolbox. The simulation results show that our proposed algorithm ensures the total utility of system under the constraint of maximum transmission delay and power, which also with low complexity and faster convergence.

Low Complexity Fair Scheduling in LTE/LTE-A Uplink Involving Multiple Traffic Classes

Abstract: The bulk of the research on long term evolution/long term evolution-advanced [(LTE)/(LTE-A)] packet scheduling is concentrated in the downlink and the uplink and is comparatively less explored. In uplink, channel aware scheduling with throughput maximization has been widely studied while considering an infinitely backlogged buffer model, which makes the investigations unrealistic. Therefore, we propose an optimal uplink packet scheduling procedure with realistic traffic sources. First, we advocate a joint channel and buffer aware algorithm, which maximizes the actual transmitted bit-count. Thereafter, we introduce delay constraints in our algorithm to support real-time traffic. We further enhance our algorithm by incorporating the varied delay and throughput requirements demanded by mixed traffic classes. Finally, we introduce priority flipping to minimize bandwidth starvation of lower priority traffic in the presence of higher percentage of high priority traffic. We observe that a delay constraint may render the optimization-based proposals infeasible. Therefore, to avoid infeasibility, we replace the delay constraint with delay outage minimization (DOM). DOM aims at minimizing the packet drop due to delay violation. Moreover, DOM also helps in reducing the problems to a well-known assignment problem, which can be solved by applying the Hungarian algorithm. Hence, our approach delivers an optimal allocation with low computational complexity.