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Design of hybrid topologies using higher order sectorisation for performance enhancement of 5G radio access network

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The fifth generation mobile network is planned not only to enhance capacity up to 20 Gbps but also able to connect a variety of devices ranging up to one million… Click to show full abstract

The fifth generation mobile network is planned not only to enhance capacity up to 20 Gbps but also able to connect a variety of devices ranging up to one million per square km and having diversified requirements and applications with the latency of less than one millisecond. Hence it becomes very important to utilize all available network resources judiciously to obtain the vision of IMT 2020. Performance gains of a 5G New Radio (NR) are evaluated in this paper after deployment of homogeneous six and nine sectors per site in terms of considered Key Performance Indicators (KPIs). Further two hybrid-network topologies are proposed with a combination of three, six, and nine sectors on the basis of performances measured in terms of selected KPIs. KPIs like SINR, Average data throughput per user, sectorisation gain, relative energy consumption, coverage and relative power efficiency obtained for proposed topologies i.e., Architecture-2 and Architecture-6 are found to be 2.3 dB, 2.05, 1.96, 1.35, 161%, 1.13 and 0 dB, 2.23, 2.1, 1.86, 191%, 1.44 respectively in comparison to standard three sector configuration. Although the relative energy consumption (ER) is found to be highest for Archicture-6, it provides the best relative power efficiency (RPE) of 1.44 which indicates that the proposed architecture is quite energy efficient. Both hybrid network topologies in general and Architecture-6 in particular is found to provide significantly high-performance gains and thus can be a suggested as a potential solution to meet high traffic demands at localized areas and hot spots.

Keywords: design hybrid; performance; hybrid topologies; radio; sectorisation; network

Journal Title: Journal of Ambient Intelligence and Humanized Computing
Year Published: 2021

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