A software-coupled 2D FDTD hardware accelerator [electromagnetic simulation]

Schneider, Ryan N.; Okoniewski, M.; Turner, L.E.

doi:10.1109/aps.2004.1330521

Cited by 5 publications

(1 citation statement)

References 6 publications

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“…Over the years, researches have been made to reduce the computational time and, in general, improve the model. More details can be found in [158]- [163].…”

Section: Finite-difference Time-domain (Fdtd) Modelmentioning

confidence: 99%

Cellular Communications Coverage Prediction Techniques: A Survey and Comparison

et al. 2020

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A lot of effort and time is utilized in the planning and building of the cellular wireless networks to use minimum infrastructural components to provide the best network coverage as well as delivery of quality of service. Generally, path loss models are used for the prediction of wireless network coverage. Therefore, detailed knowledge of the appropriate path loss model suitable for the proposed geographical area is needed to determine the coverage quality of any wireless network design. However, to the best of our knowledge, despite the importance of path loss models, as used for the prediction of wireless network coverage, there doesn't exist any comprehensive survey in this field. Therefore, the purpose of this paper is to survey the existing techniques and mechanisms which can be addressed in this domain. Briefly, the contributions of this paper are: (1) providing a comprehensive and up to date survey of the various network coverage prediction techniques, indicating the different frequency ranges the models were developed, (2) the different suitable terrains for each of the model and the best suit mobile generation were presented, and lastly, (3) providing comparative analysis to aid the planning and implementation of the cellular networks. INDEX TERMS Path loss model, prediction, wireless, propagation scenarios, mobile generations, signal. I. INTRODUCTION The remarkable changes experienced by the development of mobile communication system over the last few years has led to severe challenges to the planning of mobile wireless networks. This fruition journey of the first-Generation (1G) network started back in the year 1979 and has progressed to the presently explored Fifth Generation (5G) network. Each new generation is usually built upon the present generation's needs, which led to research and development for a better technology that will accommodate the needs, capacities, proper availability to the end-user. With this exponential increase in the use of mobile-connected devices as well as the constant expansion of mobile communication networks, the effective provision of the coverage of the mobile networks is imperative for the delivery of quality of service (QoS) [1]. Radio propagation can be defined as the behaviour of radio waves experienced while signals are transmitted from one point to another [2]. Such phenomena like absorptions, reflections, scattering, refractions, among others, affect the radio wave [3]. Therefore, mobile network coverage prediction is a vital and essential task in the planning and deployment of cellular technology.

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“…Over the years, researches have been made to reduce the computational time and, in general, improve the model. More details can be found in [158]- [163].…”

Section: Finite-difference Time-domain (Fdtd) Modelmentioning

confidence: 99%