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The growing demand for mobile multicast services, such as Internet Protocol television (IPTV) and video streaming, requires effective radio resource management (RRM) to handle traffic with strict quality-of-service constraints over Long-Term Evolution (LTE) and beyond systems. Special care is needed to limit system performance degradation when multiple multicast streams are simultaneously transmitted. To this aim, this paper proposes an RRM policy based on a subgrouping technique for the delivery of scalable multicast video flows in a cell. Our proposal enhances the legacy multicast transmission over LTE systems by exploiting multiuser diversity and the users' channel quality feedbacks. Moreover, it is designed to take advantage of the frequency selectivity in the subgroup formation. Simulation results demonstrate the effectiveness of the proposed scheme, which outperforms existing approaches from the literature. It succeeds in achieving higher spectral efficiency and guaranteeing adequate video quality to all multicast receivers and improved quality to those with good channel conditions. [ABSTRACT FROM AUTHOR]

Multimedia content delivery over satellite systems is considered as a promising service in emerging 5G networks. The aim of this paper is to design a novel radio resource management algorithm for efficiently managing multicast multimedia content transmission over satellite network. The proposed approach performs the spectrum management on a per-group basis, by splitting multicast terminals into different subgroups according to the experienced channel qualities. We demonstrate that subgrouping policy defined by the authors as multicast subgrouping-maximum satisfaction index (MS-MSI), based on a new metric (i.e., MSI), overcomes the weakness of the previous techniques proposed in the literature and provides the best tradeoff between user throughput and fairness. As a further result, we demonstrate that MS-MSI is robust to the long propagation delay of satellite links. An extensive simulation campaign has been conducted by considering several satellite environments. [ABSTRACT FROM PUBLISHER]

Allocating and managing radio resources to multicast transmissions in orthogonal frequency-division multiple access (OFDMA) systems is the challenging research issue addressed by this paper. A subgrouping technique, which divides the subscribers into subgroups according to the experienced channel quality, is considered to overcome the throughput limitations of conventional multicast data delivery schemes. A low complexity algorithm, designed to work with different resource allocation strategies, is also proposed to reduce the computational complexity of the subgroup formation problem. Simulation results, carried out by considering the Long Term Evolution system based on OFDMA, testify the effectiveness of the proposed solution, which achieves a near-optimal performance with a limited computational load for the system. [ABSTRACT FROM PUBLISHER]

The era of the fifth-generation (5G) New Radio (NR) technology has just begun, and its promises to substantially improve the system performance have turned into reality. The 5G NR enabled Non-Terrestrial Network (NTN) is almost upon us and will represent an effective solution to provide services anytime, anywhere, and over wider coverage areas. In this context, high throughput satellite systems with advanced multi-beam transmissions have gained significant attention owing to their ability to boost the system capacity through beam frequency re-use, increased user data rates, and system spectral efficiency. In this paper, we propose a novel radio resource management scheme, named Single-Frequency Multi-Beam Transmission (SF-MBT), for efficient delivery of the enhanced Mobile Broadband (eMBB) services over the 5G NR multi-beam NTN systems. The main thinking is to group beams into the dedicated Beam Areas, wherein a certain content flow is delivered via simultaneous multi-beam transmissions over the same radio resources without causing inter-beam interference. A simulation campaign is conducted under different scenarios to assess the effectiveness of the proposed SF-MBT algorithm as compared to the current schemes based on frequency reuse. System-wide performance is evaluated in terms of the aggregate data rate, mean throughput, and system spectral efficiency. [ABSTRACT FROM AUTHOR]

There is an important trend in terms of user expectations of ubiquity in relation to rich media services and increase in number and range of devices with high specifications which enable access to such services, with very ambitious technical requirements. Providing this support is a very challenging issue, especially in urban dense network environments (DenseNet). Diverse solutions have been proposed, including deployment of femtocells in conjunction with the existing infrastructure, but there is still need for new approaches to balance resources and quality in current competitive market. This paper proposes an innovative three-phase adaptive scheduling solution [energy-quality utility-based adaptive scheduling solution (EQUAS)], which performs trade off between service quality and energy efficiency when allocating network resources to mobile users in a DenseNet. Resource allocation is performed according to a utility function that takes into account throughput, device energy consumption, and user mobility. Furthermore, adaptive reallocation is applied to increase network coverage and avoid dropping service. Testing results show how EQUAS outperforms two competitive approaches in terms of energy consumption and efficiency, data throughput, and estimated user satisfaction. [ABSTRACT FROM AUTHOR]

The objective of this paper is to design radio resource management policies for supporting the effective delivery of multicast service in Long-Term Evolution Advanced (LTE-A) systems. Specifically, we propose multicast subgrouping-based solutions to maximize the system efficiency in terms of throughput under the constraints that 1) all user equipment devices are served and that 2) fairness among the activated multicast subgroups is guaranteed to avoid users' dissatisfaction. These results are obtained by modeling the multicast subgroup formation problem through a bargaining game. Moreover, an algorithm, which achieves the optimal fairness–efficiency tradeoff, is proposed to support the system in selecting the most appropriate solution in terms of 1) subgroups activated over each system carrier and 2) resource allocated to them. [ABSTRACT FROM PUBLISHER]