In future Radio Access Network (RAN), many small cells will be densely deployed to meet the capacity demand of mobile users. Centralized Radio Access Network (CRAN) is a potential solution to increase the capacity demand of RAN. CRAN breaks the functionality of RAN between Remote Radio Head (RRH) and Base Band Unit (BBU) where RRH and BBU are preferably connected by an optical link called fronthaul link. However, the deployment of fiber for fronthaul connectivity, at each Small Cell (SC) location, is impossible or impractical due to cost or other constraints. As such, Passive Optical Network (PON) and Free Space Optic (FSO) technologies have emerged as potential candidates for fronthaul transmission when the complete optical fiber-based infrastructure for fronthaul network cannot be deployed alone. In this paper, we propose a hybrid PON and FSO based method for SC fronthaul connections that considers three different network constraints i.e. bandwidth, data rate, and latency. Based on this, we formulate the problem and propose a novel method to perform cell association, namely Minimum Sum Selection (MSS). The performance is evaluated in terms of the number of SCs connected and the proposed method is compared with two other baselines, namely: Minimum Rate Selection (MRS) and Random Selection Method (RSM). The results show that despite MSS requiring knowledge of all network constraints, it has a better performance at the cost of more computation resources, achieving gains of 7% and 6.5% in cell connections when compared to the other two baseline methods.
The quality of power supply and reliability play a vital role in the smooth operation and maintenance of commercial use. These requirements have significant applications when dealing with residential areas, hospitals, industries, educational sectors, banks and airports, etc. In this regard, backup diesel generators are considered the most important source for an uninterrupted supply of electricity. However, there is an emergent need to avoid sudden shutdown of generators in the events of overload, shortage of fuel flow, service interval and lagging of power factor. These common problems can be addressed through monitoring of power generator parameters, for instance, real time remote monitoring to measure the health of the generator, the problem of load management due to high demand of power during peak hours and power factor improvement due to exceeding inductive load. In this paper, our proposed architecture—based on an IOT solution—consists of different sensors, namely a current transformer for measuring load, fuel gauge for fuel level monitoring, and temperature measurement with the energy module to determine the power factor of the system. Our proposed system is operated and tested on a real trolley-mounted 25 KVA generator.
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