# Multi-Connectivity for Multicast Video Streaming in Cellular Networks
### Related Literature  
Multicasting has been recognized as an effective means of catering to bandwidth-hungry video transmissions [3] in cellular mobile networks. Resource allocation algorithms designed for multicast streaming have been shown to serve significantly more users while minimizing the impact of multicast streaming on other services [4, 13]. Further improvements in the performance of multicast video streaming have been achieved by exploiting the inherent loss-tolerant nature of video streams [14]. The use of MC has been studied for mitigating radio link failures in ultra-dense intra-frequency 5G network deployments [15], demonstrating substantial reductions in failures and throughput improvements for cell-edge users. Additionally, proportional fair allocation policies have been designed [16], tailored for multi-connected ultra-dense networks, prioritizing users based on load balancing and signal characteristics. MC has also been shown to enhance network availability for ultra-reliable low latency communication (URLLC) applications in 5G [17], where network availability is crucial. MC also optimizes the system resource utilization in URLLC through load-aware cell selection [18]. Numerous architectures have been proposed for implementing MC in 5G [19]. The comparative evaluations in [20] assessed throughput performance in distributed and cloud-based heterogeneous network architectures, favoring cloud-based networks for superior throughput. In [21], a 5G architecture integrating multiple RATs was proposed, facilitating seamless inter-RAT MC with LTE and Wireless Local Area Networks (WLANs). A control-and-user-plane split architecture for MC in 5G NR was introduced in [22], bypassing macro-cells for the user plane transmissions of multi-connected users. It wasn shown in [23] that MC exhibits significant reductions in transmit power compared to single-connected systems, resulting in improved outage probability and spectral efficiency. MC has also been examined as a means of optimizing power consumption, particularly for 5G heterogeneous cloud radio access networks [24]. Furthermore, beyond cellular networks, MC has also found applications in vehicle-to-anything (V2X) services, playing a pivotal role in meeting Quality of Service (QoS) requirements [25]. MC, combined with guard bands, has also been shown to provide substantial improvement in millimeter-wave (mmWave) session continuity [26]. The methodologies in [27] were used to evaluate MC's impact on ultra-dense urban mmWave networks, showcasing enhancements in denial-of-service and session drop probabilities. The trade-offs between system complexity and performance enhancement in multi-connected mmWave systems were explored in [28]. In [29], a network throughput-optimizing algorithm approaching the global optimum solution was proposed for addressing the link scheduling problem in multi-connected mmWave networks. The uplink MC frameworks presented in [30] efficiently monitor channel dynamics and link directions in mmWave transmissions, leading to efficient scheduling and session management. By mitigating radio link failures due to mobility, MC also ensures seamless connectivity for mobile users [15]. The combination of MC and network coding was studied in [31] to enable the transmission of high-quality video streaming services over mmWave networks. Despite the wide-ranging applications of MC, its use in multicast streaming has not yet been explored in the existing literature. This work is the first to leverage MC for this crucial application and establish improvements in system performance that are achieved using MC multicasting for video streaming. We also address the problem of resource allocation in the proposed system. The rest of this paper is organized as follows. An overview of the existing 3 GPP standards for multicasting and MC is provided in Section 2. This is followed by a discussion on how these two techniques can be used together within the current and future generations of wireless mobile networks in Section 2.1.