Search

The Cloud Radio Access Network (C-RAN) is regarded as the possible implementation approach of the next-generation mobile networks. C-RAN splits a traditional base station into remote radio heads (RRHs) and the base band unit (BBU). Many BBUs are co-located into a centralized BBU pool. This enables the baseband resources to be managed in a centralized BBU pool and thus improves the efficiency. In this paper, a new bandwidth adaptation (BA) mechanism is designed for the C-RAN with the dual connectivity capability. The dual connectivity allows the bearer to be split so as to access more resources from RRHs simultaneously. The new BA mechanism is developed so as to dynamically allocate the resources to establish a new or a handoff bearer. The new BA mechanism is designed with a new downgrading index, which aims to fairly release the proportional resource from more RRHs and then aggregates the released resource to a new or a handoff bearer. Simulation and analysis results illustrate that the proposed BA mechanism reduces both the handoff bearer dropping and the bearer blocking probabilities. [ABSTRACT FROM AUTHOR]

The swarm robot network is the widely used wireless communication technology, and significantly, it has higher uplink and downlink throughput than the conventional communication networks. Apart from the appreciable advantages, there are various challenges like minimized data retention rate, low data transmission rate, countless handovers over a short time, and a short transmission range due to higher data transmission usage. To resolve these challenges, Scalable Network Architecture with Dual Connectivity Application (SN-DCA) in control and data plane is proposed to improve data retention rates and minimize network usage by controlling unwanted access in the distributive clouds during transmission. Here, Two-stage control data plane splitting (TSCDP) is introduced to enhance network usage by optimizing unwanted access. It further improves the data retention rate during transmission. The analytical performance of the proposed techniques has been validated computationally and examined through simulation studies. The Simulation results show that these techniques achieve a higher performance ratio in the network with a minimum transmission delay and a high data retention rate. [ABSTRACT FROM AUTHOR]

The Heterogeneous Cellular Network (HCN) paradigm holds promise for increasing the coverage probabilities and date rates of its users. The concept of downlink and uplink decoupling (DUDe) has been extensively investigated to alleviate the load imbalance problem in HCNs. Furthermore, the dual connectivity (DC) access scheme, which allows user equipment (UE) to simultaneously connect with multiple base stations (BSs), has also been investigated for its bandwidth aggregation feature that can provide increased UE data rates. This work uses stochastic geometry to analyze the uplink spectral- and energy-efficiency gains provided in a K -tier HCN with clustered users by introducing DC jointly with DUDe access. The BSs in each tier are modeled by an independent, homogeneous Poisson point process, whereas the spatially clustered UEs are modeled by a Matern cluster process. The exact analytical expressions and the upper-bound on coverage probability, spectral and energy efficiencies of the typical user are derived. The main results demonstrate the relative advantage of using DC with DUDe relative to the cases of single connectivity (SC) with DUDe and SC with the conventional downlink reference received power-based association. Further, the results also show that clustering should be modeled with an MCP to analyze the performance of clustered-HCNs. [ABSTRACT FROM AUTHOR]

The capacity and coverage needs of 5G NR (New Radio) networks are satisfied by deploying a high number of small cells in the coverage area of a macro cell. In 5G Dual Connectivity (DC), these small cells are represented as eNBs with 4G characteristics different from the macro cells which are the 5G NR gNBs. The mobile node (MN) can establish a connection with these cells in different technologies at the same time. To effectively manage this heterogeneity and density, the self-organizing networks can be used as a solution. The mobility load balancing (MLB) and mobility robustness optimization (MRO) are two different schemes in self-optimization to enable load balancing and handover management, respectively. These two functions affect the same parameters (e.g hysteresis, time-to-trigger, cell individual offset) from the opposite way. This conflict is further worsened in DC due to the heterogeneous ultra-dense architecture of 4G small cells at the 5G core. Accordingly, the frequent and ping-pong handovers with dropped and blocked calls are more observed because of this conflict. A key contribution of our work is timely detection of this MLB&MRO conflict through the alpha–beta pruning which is a game-theoretic approach to reduce these problems. This mechanism is based on the principle of pruning the unnecessary leaves on the tree. Thanks to this characteristic, we can overcome the ultra-density to reduce conflict detection time. To utilize the alpha–beta pruning, we consider the small cells as leaves on a tree with corresponding load values. To estimate these loads, we also utilize the G/G/1 queuing system. After finding the small cells which are probable for MLB&MRO conflict, we utilize the two-dimensional Markov chain to disable fluctuations causing this conflict. Results reveal that the proposed strategy reduces the call dropping and blocking probabilities 15% and 23% compared to the traditional MLB&MRO approach. [ABSTRACT FROM AUTHOR]