Cell Coverage Area and Link Budget Calculations in LTE System

Sharma, Purnima K.; Sharma, Dinesh; Gupta, Akanksha

doi:10.17485/ijst/2016/v9is1/107935

Cited by 16 publications

(13 citation statements)

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“…where P s is the source transmit power, G s the source transmit gain, G t the target receive gain, and L is the total path loss between source and target. The path loss between a receive and transmit antenna is the product of the losses in each medium between them and the free-space path loss: (64)…”

Section: Appendix D: Computation Of the Electric Field Strength At Thmentioning

confidence: 99%

A Systems‐Based Risk Assessment Framework for Intentional Electromagnetic Interference (IEMI) on Critical Infrastructures

et al. 2018

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Modern infrastructures are becoming increasingly dependent on electronic systems, leaving them more vulnerable to electrical surges or electromagnetic interference. Electromagnetic disturbances appear in nature, e.g., lightning and solar wind; however, they may also be generated by man-made technology to maliciously damage or disturb electronic equipment. This article presents a systematic risk assessment framework for identifying possible, consequential, and plausible intentional electromagnetic interference (IEMI) attacks on an arbitrary distribution network infrastructure. In the absence of available data on IEMI occurrences, we find that a systems-based risk assessment is more useful than a probabilistic approach. We therefore modify the often applied definition of risk, i.e., a set of triplets containing scenario, probability, and consequence, to a set of quadruplets: scenario, resource requirements, plausibility, and consequence. Probability is "replaced" by resource requirements and plausibility, where the former is the minimum amount and type of equipment necessary to successfully carry out an attack scenario and the latter is a subjective assessment of the extent of the existence of attackers who possess the motivation, knowledge, and resources necessary to carry out the scenario. We apply the concept of intrusion areas and classify electromagnetic source technology according to key attributes. Worst-case scenarios are identified for different quantities of attacker resources. The most plausible and consequential of these are deemed the most important scenarios and should provide useful decision support in a countermeasures effort. Finally, an example of the proposed risk assessment framework, based on notional data, is provided on a hypothetical water distribution network.

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Section: Appendix D: Computation Of the Electric Field Strength At Thmentioning

confidence: 99%

A Systems‐Based Risk Assessment Framework for Intentional Electromagnetic Interference (IEMI) on Critical Infrastructures

et al. 2018

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“…It is necessary to determine link budget in the whole design of radio communication system. Link budget calculations are used for calculating the power levels wanted for cellular communications systems and for obtaining the BTS coverage [14].…”

Section: Path-lossmentioning

confidence: 99%

Mobility Load Balancing in Cellular System with Multicriteria Handoff Algorithm

Girma¹,

Abebe²

2017

Advances in Fuzzy Systems

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Efficient traffic load balancing algorithm is very important to serve more mobile users in the cellular networks. This paper is based on mobility load balancing handoff algorithm using fuzzy logic. The rank of the serving and the neighboring Base Transceiver Stations (BTSs) are calculated every half second with the help of measurement report from the two-ray propagation model. This algorithm is able to balance load of the BTS by handing off some ongoing calls on BTS's edge of highly loaded BTS to move to overlapping underloaded BTS, such that the coverage area of loaded BTS virtually shrunk towards BTS center of a loaded sector. In case of low load scenarios, the coverage area of a BTS is presumed to be virtually widened to cover up to the partial serving area of neighboring BTS. This helps a highly loaded neighboring BTS or failed BTS due to power or transmission. Simulation shows that new call blocking and handoff blocking using the proposed algorithm are enhanced notably.

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“…The range of cell coverage is based on natural factors, for example, human factors, such as the landscape (urban, suburban, rural), subscriber behavior, and propagation conditions, etc. [10].…”

Section: Cell Coverage Areamentioning

confidence: 99%