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Multicasting is becoming more and more important in the Internet of Things (IoT) and wearable applications (e.g., high definition video streaming, virtual reality gaming, public safety, among others) that require high bandwidth efficiency and low energy consumption. In this regard, millimeter wave (mmWave) communications can play a crucial role to efficiently disseminate large volumes of data as well as to enhance the throughput gain in fifth-generation (5G) and beyond networks. There are, however, challenges to face in view of providing multicast services with high data rates under the conditions of short propagation range caused by high path loss at mmWave frequencies. Indeed, the strong directionality required at extremely high frequency bands excludes the possibility of serving all multicast users via a single transmission. Therefore, multicasting in directional systems consists of a sequence of beamformed transmissions to serve all multicast group members, subgroup by subgroup. This paper focuses on multicast data transmission optimization in terms of throughput and, hence, of the energy efficiency of resource-constrained devices such as wearables, running their resource-hungry applications. In particular, we provide a means to perform the beam switching and propose a radio resource management (RRM) policy that can determine the number and width of the beams required to deliver the multicast content to all interested users. Achieved simulation results show that the proposed RRM policy significantly improves network throughput with respect to benchmark approaches. It also achieves a high gain in energy efficiency over unicast and multicast with fixed predefined beams. [ABSTRACT FROM AUTHOR]

To date, group-oriented communications have been mainly exploited for delivering multimedia services in human-oriented communications while, in future fifth generation (5G) cellular networks, objects will be the main target. Internet of Things (IoT) will undoubtedly play a key role in 5G networks, wherein massive machine-type communications (mMTC) feature a use case as crucial as challenging since cellular IoT connections are predicted to grow heavily in the next future. To boost capacity and energy efficiency, the 5G network can leverage device-to-device (D2D) communications which are recognized as an effective offloading technique. This is achieved thanks to the fact that, in legacy D2D communications, data are directly sent from one device to another, avoiding the crossing of the network. Obviously, the distributed nature of such a communication paradigm and the inherent broadcast nature of the wireless channel make it necessary to think how to secure the so called “sidelink” transmissions. This work proposes a protocol for the efficient and reliable management of multicast services in a 5G-oriented IoT scenario, in which security is a crucial requirement to be met. The proposed protocol is tailored to Narrowband IoT (NB-IoT) and makes use of D2D communications with the aim of improving network efficiency and optimizing network resource utilization. In addition, cyber security and social trustworthiness mechanisms are exploited to secure D2D communications. [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]

Resource management in emerging dense heterogeneous network environments (DenseNets) is a challenging issue. The employment of multicast transmissions in this scenario has potential to address the problems. On one hand, the large number of smart user mobile devices and user expectations for high-quality rich media services has determined a growing demand for network resources; in DenseNets, mobile users have to make the choice in terms of the network to connect to, in order to balance energy saving and delivery performance. On the other hand, the proliferation of user accesses to the existing and future network infrastructure will bring along with it the operators need for optimizing the radio resource usage. This paper proposes a hybrid unicast-multicast utility-based network selection algorithm (HUMANS), which offers the additional option of selecting multicast transmissions in the network selection process during video delivery. By serving users with good channel conditions via unicast transmissions and users with poor channel quality conditions via multicast, HUMANS allows outperforming other solutions in terms of outage percentage and average quality of transmission, in both low- and high-density scenarios. Most importantly, at the same time it guarantees operators a more efficient resource utilization. [ABSTRACT FROM AUTHOR]

This paper proposes a novel method for device-to-device (D2D) user clustering that allows wireless users in proximity to share common resources to save both system bandwidth and energy resources. The idea at the basis of our proposed cluster formation is to incorporate both social interactions and physical relationships among D2D terminals. Towards this goal, we propose two clustering approaches. The first one is based on the Chinese restaurant process (CRP), whereas the second one enhances the traditional CRP by defining a “distance-dependent Chinese restaurant process” (namely, DCRP). Numerical simulation results demonstrate superiority of our proposed clustering schemes in terms of system throughput, energy consumption, and energy efficiency over the existing schemes that rely only on physical distance. [ABSTRACT FROM AUTHOR]

The design of effective radio resource management policies for group-oriented services in beyond-4G networks is attracting the interest of the research community. Along this line, this paper analyzes some novel approaches that take advantages of the Device to Device (D2D) communication paradigm with the aim of improving the session quality experienced by mobile users in terms of delay and energy consumption. The basic idea is to enable receivers with a bad cellular link from the evolved Node B (eNodeB) to receive the multicast service through another mobile device located in proximity over a direct link. Two schemes are proposed that exploit different radio technologies to enable nearby multicast subscribers to establish direct local links, either Long Term Evolution-Advanced (LTE-A) or Wi-Fi Direct. The effectiveness of the proposed solutions is demonstrated through a comprehensive simulative analysis and compared with traditional techniques that only exploit point-to-multipoint communication from the eNodeB to all the group members not taking advantages of the multi-user diversity or alternative network technologies to serve the multicast users. [ABSTRACT FROM AUTHOR]

The focus of this paper is on a wireless cooperative network architecture, where a group of users exploits short-range wireless links to share the costs of a cellular download. To maximize the efficiency of the communication system, an optimization of parameters such as download time, monetary cost, and energy consumption can be implemented. Following this approach different portions of data shall be assigned for download to the involved users, which will then cooperatively exchange the contents on the short-range link. However, the policy of task assignment to the user terminals has a direct influence on the payoff of the single users, raising fairness issues in real implementation scenarios. Focusing on the energy savings introduced by the wireless cooperative network, in this paper we address the fairness issue by relying on game theoretic bargaining solutions. These solutions, have intrinsic properties to nicely model the duality between fairness and efficiency in the performances. An optimal trade-off algorithm between efficiency and fairness is then introduced, allowing the service coordinator to select the most appropriate bargaining solution and energy savings allocation under different constraints on fairness. [ABSTRACT FROM AUTHOR]