Abstract
Emerging 5G wireless networks are expected to herald significant transformation in industrial applications, with improved coverage, high data rates, and massive device capacity. However, the introduction of 5G wireless makes the network configuration, management, and planning extremely challenging. For efficient network configuration, every cell needs to be allocated a particular Physical Cell Identifier (PCID), which is unique in its vicinity. Wireless standards (e.g., 3GPP) typically specify a limited number of PCIDs. However, the number of cells in 5G Ultradense Networks (UDN) is expected to significantly outnumber these limited PCIDs. Hence, these PCIDs need to be efficiently allocated among the myriad of cells, such that two cells which are neighbors or neighbor’s neighbor are assigned with different PCIDs. This complicated network configuration problem becomes even more complex by dynamic introduction and removal of 5G small cells (e.g., micro, femto, and pico). In this paper, we introduce BiSON, a new Bioinspired Self-Organizing Solution for automated and efficient PCID configuration in 5G UDN. Using two different extensions, namely, “always near-optimal” and “heuristic,” we explain near-optimal and dynamic auto-configuration in computationally feasible time, with negligible overhead. Our extensive network simulation experiments, based on actual 5G wireless trials, demonstrate that the proposed algorithm achieves better optimality (minimum PCIDs in use) than earlier works in a reasonable computational complexity.
Highlights
Generation 5G wireless [1] envisions revolutionizing industrial applications, like robotics and smart grids, by providing manifold improvement in latency, data rates, and device capacity
(3) The biologically inspired SON (BiSON) algorithm runs in the Self-Organizing Networks (SON) server and dynamically allocates Physical Cell Identifier (PCID) to small cells
(5) We include multistory buildings where small cells are deployed with arbitrary overlapping of one over another
Summary
Generation 5G wireless [1] envisions revolutionizing industrial applications, like robotics and smart grids, by providing manifold improvement in latency, data rates, and device capacity. An efficient, dynamic, and optimal PCID configuration among the myriad of 5G cells is of utmost important. A survey of the recent research works in self-organization and management [4] reveals that a large number of academic researches and international projects reflect the importance of PCID allocation with self-configuration, plug-and-play, self-optimization, self-healing (in case of failure), and automated network management. This motivates us to look into the dynamic self-configuration problem in generation of 5G wireless networks. (2) We design a new customized genetic algorithm (GA) to model the optimal PCID configuration problem.
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