Wireless Channel Models for Indoor Environments

Anusuya, K. V.; Bharadhwaj, S.; Rani, Shweta

doi:10.14429/dsj.58.1706

Cited by 9 publications

(4 citation statements)

References 27 publications

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“…Measurements of channel parameters and analysis of indoor radio channels have been undertaken in [6][7][8][9][10] . Though these measurements have been undertaken for MIMO channels in 5.2 GHz, Ultra-Wideband using Software Defined Radios (SDR) and related hardware, but the measurements and channel models are for small distances and purely for indoor setup.…”

Section: Related Workmentioning

confidence: 99%

Channel Sounding and Measurements for Pico Cells for LTE and Future Wireless Networks

2021

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Wireless networks are the preferred future access networks for both defense and civilian deployments as part of telecommunication networks. The successful implementation of long term evolution (LTE) networks and applications such as the Internet of Things (IoT) in the telecommunication infrastructure has guaranteed rates of up to 100 Mbps while supporting ultra-dense wireless access network. With the incorporation of LTE-Advanced and fifth-generation wireless protocols, the data rates are expected to reach upto 1 Gbps. Hence, there is a pertinent requirement to carry out channel measurements at sub 1 GHz, 2 GHz, and 3 GHz bands to enable the design and implementation of optimum transceivers for pico-cells of LTE and future wireless networks. For the first time measurements and comparison with standard models of channel impulse response models have also been carried out in five different terrains namely Urban, Semi-Urban, Forest, Rural, and Desert terrains in the Indian sub-continent to effectively cover a variety of deployments of future wireless access networks for defense wireless networks

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Section: Related Workmentioning

confidence: 99%

Channel Sounding and Measurements for Pico Cells for LTE and Future Wireless Networks

2021

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“…Later, in 2008, Anusuya et al [7] surveyed different channel models used to characterize indoor wireless systems, and they concluded that the efficiency of a model is measured by computational complexity whereas its accuracy can be measured by estimating its prediction error. In contrast, Neskovic et al [8] mentioned that in order to increase system efficiency, mutual interference should be avoided, thus favoring coexistence as a result of suitable techniques for the prediction of indoor electromagnetic propagation.…”

Section: A Related Literature Reviews Publishedmentioning

confidence: 99%

Bringing It Indoors: A Review of Narrowband Radio Propagation Modeling for Enclosed Spaces

2020

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Small cells are now widely deployed indoors to address hot-spot areas where capacity uplift is needed. This deployment leads to the increase of wireless networks as a challenge to service demands of personal communication systems, which has inspired the scientific community to work towards understanding and predicting in-building radio wave propagation performance. Despite this, only a few reviews have attempted to overview channel modeling for specific indoor environments and even fewer outline remarks that include a methodology for designing and planning indoor radio systems. Consequently, a comprehensive survey of indoor narrowband channel models is presented, spanning more than 30 years of continuous research to overview and contrast significant developments including their disadvantages, and proposing a new taxonomy to analyze them. Finally, remarks on indoor radio propagation modeling with a vision for future research opportunities are presented. ⋮ INDEX TERMS Indoor channel models, indoor radio wave propagation, wireless propagation.

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“…[50,51]); hence, we do not focus on the control strategies for the UAV. Furthermore, we define a bounded coverage domain D t ⊂ M at time t around the UAV in the azimuth plane which specifies a neighborhood around the L-UAV based on signal strength from its wireless transmitter [52]. A simple model for this region is a circular disk with fixed radius r at a specific height (see Figure 3(b)).…”

Section: Problem Descriptionmentioning

confidence: 99%

A framework for mapping with biobotic insect networks: From local to global maps

Dirafzoon

Bozkurt

Lobatón

2017

Robotics and Autonomous Systems

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We present an approach for global exploration and mapping of unknown environments using a swarm of cyborg insects, known as biobots, for emergency response scenarios under minimal sensing and localization constraints. We exploit natural stochastic motion models and controlled locomotion of biobots in conjunction with an aerial leader to explore and map a domain of interest. A sliding window strategy is adopted to construct local maps from coordinate free encounter information of the agents by means of local metric estimation. Robust topological features from these local representations are extracted using topological data analysis and a classification scheme. These maps are then merged into a global map which can be visualized using a graphical representation, that integrates geometric as well as topological features of the environment. Simulation and experimental results with biologically inspired robotic platform are presented to illustrate and verify the correctness of our approach, which provides building blocks for SLAM with biobotic insects.

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Wireless Channel Models for Indoor Environments

Cited by 9 publications

References 27 publications

Channel Sounding and Measurements for Pico Cells for LTE and Future Wireless Networks

Channel Sounding and Measurements for Pico Cells for LTE and Future Wireless Networks

Bringing It Indoors: A Review of Narrowband Radio Propagation Modeling for Enclosed Spaces

A framework for mapping with biobotic insect networks: From local to global maps

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