# Multi-Connectivity-Based Adaptive Fractional Packet Duplication in Cellular Networks
## 2 Related Work  
We introduced the concept of fade duration outage probability (FDOP) and fractional packet duplication in our previous work [1] where FDOP-based handover requirements were shown in contrast to the traditional SINR-based handovers in cellular systems. A comprehensive tutorial on a newly created full-stack mmWave module incorporated into the widely used ns-3 simulator is provided by the authors in [2]. The research in [3] developed novel formulas for two-hop and three-hop relay routes and assigned a penalty cost to 10 of the three-hop paths. Then, optimization methods, such as total route and link-by-link optimization, were developed for each form of relay-selection method. Carrier aggregation and dual connectivity are presented as an implementation for the ns-3 mmWave module of the 3 GPP new radio at mmWave frequencies in [4], and their integration is discussed in order to enhance the features provided by the ns-3 mmWave module. The transient and steady-state representations of system-repair models, namely rapid and slow (i.e., crew-based) repairs for networks with a large number of repair teams, were examined in this research so that the results may be applied to real-world scenarios [5]. Often, failures are described exponentially, while ME distributions explain the more complicated recovery process. Ref. [6] presented an empirical model to investigate the effects of handover protocols and the degree of multi-connectivity on the delay and dependability of blockage-driven wireless networks. In contrast to any typical handover enhancement method, the authors in [7] established a 'deep-mobility' model by applying a deep learning neural network (DLNN) to control network mobility. This model makes use of in-network deep learning, data analysis and prediction. Ref. [8] discusses the mmWave area needed for the network to monitor each link's direction in addition to its power and timing. With highly directional beams and quickly changing channels, this directional tracking may be the primary barrier in achieving resilient mmWave networks. Regarding network intelligence, the authors in [9] represented handovers for public safety and emergency communications using Markov chain matrix exponential (ME) distributions, which helps make handover decisions more accurate while considering all the different factors involved in the decision process. The authors in [10] discuss the architectural enhancements and performance analysis of packet duplication form URLLC in 5G. The authors in [11] conducted a complete in-depth survey for the horizontal and vertical handovers in heterogeneous next generation wireless networks. The authors of [12] introduced and assessed a packet-duplication system using new radio dual connectivity (NR-DC) that maximizes throughput while assuring ultra-reliable, low-latency communication. Using queuing theory, stochastic geometry, ray-based and system-level simulations, the authors in [13] developed a novel performance evaluation methodology that considers the intricacies of mmWave radio propagation in realistic urban environments, dynamic link blockage due to human mobility and multi-connectivity network behavior to preserve session continuity. An anchor-based MC mobility model for 5G UCN environment was presented in [14] to improve user-mobility robustness. The first full end-to-end assessment of handover methods in mmWave cellular networks was presented in [15]. Multiple connectivity is investigated as a means of ensuring high dependability in industrial settings. Using actual channel data from two factories, many multi-connectivity approaches were compared [16]. Fog-RAN enabled multi-connectivity and multi-cell scheduling framework for 5G URLLC was studied in detail in [17]. Ref. [18] discusses the packet duplicating feature in 5G-NR and underlines the technical problems associated with it. A summary of several types of MC scheduling may be found in the survey in [19]. There are primarily three types of scheduling strategies: packet duplication, packet splitting and load balancing.