ADAPTIVE RESOURCE ALLOCATION FOR WIRELESS MULTICAST MIMO-OFDM SYSTEMS

Multiple antenna orthogonal frequency division multiple access (OFDMA) is a promissing technique for the high downlink capacity in the next generation wireless systems, in which adaptive resource allocation would be an important research issue that can significantly improve the performance with guaranteed QoS for users. Moreover, most of the current source allocation algorithms are limited to the unicast system. In this paper, dynamic resource allocation is studied for multiple antenna OFDMA based systems which provide multicast service. The performance of multicast system is simulated and compared with that of the unicast system. Numerical results also show that the propossed algorithms improve the system capacity significantly compared with the conventional scheme

Optimal 4G OFDMA Dynamic Subcarrier and Power Auction-based Allocation towards H.264 Scalable Video Transmission

In this paper, authors presented a price maximization scheme for optimal orthogonal frequency division for multiple access (OFDMA) subcarrier allocation for wireless video unicast/multicast scenarios. They formulate a pricing based video utility function for H.264 based wireless scalable video streaming, thereby achieving a trade-off between price and QoS fairness. These parametric models for scalable video rate and quality characterization arederived from the standard JSVM reference codec for the SVC extension of the H.264/AVC, and hence are directly applicable in practical wireless scenarios. With the aid of these models, they proposed auction based framework for revenue maximization of the transmitted video streams in the unicast and multicast 4G scenario. A closedform expression is derived for the optimal scalable video quantization step-size subject to the constraints of theunicast/multicast users in 4G wireless systems. This yields the optimal OFDMA subcarrier allocation for multi-userscalable video multiplexing. The proposed scheme is cognizant of the user modulation and code rate, and is henceamenable to adaptive modulation and coding (AMC) feature of 4G wireless networks. Further, they also consider aframework for optimal power allocation based on a novel revenue maximization scheme in OFDMA based wireless broadband 4G systems employing auction bidding models. This is formulated as a constrained convex optimization problem towards sum video utility maximization. We observe that as the demand for a video stream increases inbroadcast/multicast scenarios, higher power is allocated to the corresponding video stream leading to a gain in the overall revenue/utility. We simulate a standard WiMAX based 4G video transmission scenario to validate the performance of the proposed optimal 4G scalable video resource allocation schemes. Simulations illustrate that the proposed optimal band width and power allocation schemes result in a significant performance improvement over the suboptimal equal resource allocation schemes for scalable video transmission.Defence Science Journal, 2013, 63(1), pp.15-24, DOI:http://dx.doi.org/10.14429/dsj.63.375

Multiuser Diversity Management for Multicast/Broadcast Services in 5G and Beyond Networks

The envisaged fifth-generation (5G) and beyond networks represent a paradigm shift for global communications, offering unprecedented breakthroughs in media service delivery with novel capabilities and use cases. Addressing the critical research verticals and challenges that characterize the International Mobile Telecommunications (IMT)-2030 framework requires a compelling mix of enabling radio access technologies (RAT) and native softwarized, disaggregated, and intelligent radio access network (RAN) conceptions. In such a context, the multicast/broadcast ser vice (MBS) capability is an appealing feature to address the ever-growing traffic demands, disruptive multimedia services, massive connectivity, and low-latency applications. Embracing the MBS capability as a primary component of the envisaged 5G and beyond networks comes with multiple open challenges. In this research, we contextualize and address the necessity of ensuring stringent quality of service (QoS)/quality of experience (QoE) requirements, multicasting over millimeter-wave (mmWave) and sub-Terahertz (THz) frequencies, and handling complex mobility behaviors. In the broad problem space around these three significant challenges, we focus on the specific research problems of effectively handling the trade-off between multicasting gain and multiuser diversity, along with the trade-off between optimal network performance and computational complexity. In this research, we cover essential aspects at the intersection of MBS, radio resource management (RRM), machine learning (ML), and the Open RAN (O-RAN) framework. We characterize and address the dynamic multicast multiuser diversity through low-complexity RRM solutions aided by ML, orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA) techniques in 5G MBS and beyond networks. We characterize the performance of the multicast access techniques conventional multicast scheme (CMS), subgrouping based on OMA (S-OMA), and subgrouping based on NOMA (S-NOMA). We provide conditions for their adequate selection regarding the specific network conditions (Chapter 4). Consequently, we propose heuristic methods for the dynamic multicast access technique selection and resource allocation, taking advantage of the multiuser diversity (Chapter 5.1). Moreover, we proposed a multicasting strategy based on fixed pre-computed multiple-input multiple-output (MIMO) multi-beams and S-NOMA (Chapter 5.2). Our approach tackles specific throughput requirements for enabling extended reality (XR) applications attending multiple users and handling their spatial and channel quality diversity. We address the computational complexity (CC) associated with the dynamic multicast RRM strategies and highlight the implications of fast variations in the reception conditions of the multicast group (MG) members. We propose a low complexity ML-based solution structured by a multicast-oriented trigger to avoid overrunning the algorithm, a K-Means clustering for group-oriented detection and splitting, and a classifier for selecting the most suitable multicast access technique (Chapter 6.1). Our proposed approaches allow addressing the trade-off between optimal network performance and CC by maximizing specific QoS parameters through non-optimal solutions, considerably reducing the CC of conventional exhaustive mechanisms. Moreover, we discuss the insertion of ML-based multicasting RRM solutions into the envisioned disaggregated O-RAN framework (Chapter 6.2.5). We analyze specific MBS tasks and the importance of a native decentralized, softwarized, and intelligent conception. We assess the effectiveness of our proposal under multiple numerical and link level simulations of recreated 5G MBS use cases operating in μWave and mmWave. We evaluate various network conditions, service constraints, and users’ mobility behaviors

Coordinated Multicast/Unicast Transmission on 5G: A Novel Approach for Linear Broadcasting

Linear broadcasting services, with a scheduled programming, constitute a paramount tel-ecommunication service for today’s society. Although the existing technology is mature, current linear broadcast systems have serious limitations when providing service to moving users or users placed in areas with complex orography and poor signal quality. To over-come these limitations, 3GPP 5G standard has included a work item to support 5G mul-ticast/broadcast services for future Release 17. This paper investigates the integration of point-to-point (unicast) communication with cellular multicast/broadcast on 5G technology to extend the current support of linear broadcasting services. This integration relies on the use mobile edge computing (MEC) at the 5G base station (gNB) to host a dynamic adap-tive streaming over HTTP (DASH) server that is coordinated with the multicast transmis-sion to complement the broadcast service. This approach join the reliability of point-to-point communications, with dedicated resources for each user, with the spectrum efficiency of multi-cast communications, where a set of users share common resources. The coopera-tion between those unicast and multicast schemes allows those users whose coverage is not good enough, to complete the linear broadcast flow through the point-to-point transmission via MEC. The benefits of such approach have been assessed with simulations in a realistic scenario that considers a vehicle moving across a sparsely populated region in southern Spain. Results reveals that throughput and bitrate playback (reproduction rate) are greatly improved when unicast/multicast integration is enabled since the number of stalling events is reduced significantly.This work has been partially supported by Radio Televisión Española through Impulsa Visión RTVE grant and by the Universidad de Málaga. We are grateful to Pere Vila, Esteban Mayoral Campos, Adolfo Muñoz Berrón and Miguel Ángel Bona San Vicente for their support and collaboration during the development of the project. Funding for open access charge: Universidad de Málaga / CBU

Joint Strategy for LTE Resource Allocation: Multicast Subgrouping & Unicast Transmissions

La ponencia presentada en: XII Jornadas de Ingeniería Telemática (JITEL 2015), celebrada los días 14 al 16 de octubre de 2015, en Palma de Mallorca.Mobile broadband services are growing rapidly in the last few years due to the deployment of Long Term Evolution (LTE) cellular networks. Among them, multicast services can be provided using Evolved Multimedia Broadcast and Multicast Service (eMBMS), available with 3rd Generation Partnership Project (3GPP) release 9, which can deliver broadcast/multicast content using a single-frequency network mode. This means sending the same multimedia content to a mass audience within a specific area. The utilization of the Conventional Multicast Scheme (CMS) approach for multicast resource allocation presents intrinsic inefficiencies, because of the different channel conditions of the users which demand the service. This paper proposes a Joint Multicast Subgrouping and Unicast Transmissions (JMSUT) strategy for resource allocation, which consists of the use of the multicast and the unicast transmissions, by means of the subframes reserved by the LTE standard for each purpose, to deliver a multicast service. The goal of the JMSUT algorithm is to maximize the service throughput whereas it guarantees the fulfillment of the Quality of Service (QoS) requirements of every user. This paper solves the former maximization problem of the joint resource allocation; on the one hand, splitting the multicast resources into different subgroups that transmit the same content with different Modulation and Coding Scheme (MCS), and on the other hand, the users with worst channel conditions are served by means of the unicast transmissions.This work was supported in part by the Spanish Ministry of Economy and Competitiveness, National Plan for Scientific Research, Development and Technological Innovation (IN-NPACTO subprogram), LTExtreme project (IPT-2012-0525- 430000), and the project TEC2014-59255-C3-3-R (ELISA).Publicad

Multicast broadcast services support in OFDMA-based WiMAX systems [Advances in mobile multimedia]

Multimedia stream service provided by broadband wireless networks has emerged as an important technology and has attracted much attention. An all-IP network architecture with reliable high-throughput air interface makes orthogonal frequency division multiplexing access (OFDMA)-based mobile worldwide interoperability for microwave access (mobile WiMAX) a viable technology for wireless multimedia services, such as voice over IP (VoIP), mobile TV, and so on. One of the main features in a WiMAX MAC layer is that it can provide'differentiated services among different traffic categories with individual QoS requirements. In this article, we first give an overview of the key aspects of WiMAX and describe multimedia broadcast multicast service (MBMS) architecture of the 3GPP. Then, we propose a multicast and broadcast service (MBS) architecture for WiMAX that is based on MBMS. Moreover, we enhance the MBS architecture for mobile WiMAX to overcome the shortcoming of limited video broadcast performance over the baseline MBS model. We also give examples to demonstrate that the proposed architecture can support better mobility and offer higher power efficiency