Path Loss Measurements of User Equipment to Access Point Communications at 60 GHz

Characterization of Wearable and Implanted Antennas: Test Procedure and Range Design

10.36227/techrxiv.15132279 ◽

2021 ◽

Author(s):

Lukas Berkelmann ◽

Dirk Manteuffel

Keyword(s):

Test Procedure ◽

Wireless Body Area Network ◽

Path Loss ◽

Area Network ◽

Test Range ◽

General Ability ◽

Test Zone ◽

Path Loss Measurements

A method for measuring de-embedded antenna parameters of wearable and implanted antennas for on-body communications is presented. It consists of a tapered flat phantom in order to characterize an antenna’s general ability to excite surface waves travelling along the boundary between body tissue and free space expressed by an angular on-body antenna gain. The design offers a test zone large enough for most typical Wireless Body Area Network devices up to smartphone-size while minimizing the required amount of tissue-simulating material. The designed antenna test range is validated in the 2.4 GHz ISM-band. In order to showcase the applicability to a realistic application, different designs of antennas integrated into an implanted pacemaker are characterized by their on-body gain patterns. A comparison of their performance in in-situ path-loss measurements reveals a clear relation to the on-body gain patterns and indicates that this parameter is a suitable measure for enabling educated antenna design for on-body applications.<br>

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Measurement and Prediction of Short-Range Path Loss between 27 and 40 GHz in University Campus Scenarios

10.21203/rs.3.rs-70739/v1 ◽

2020 ◽

Author(s):

Glaucio Ramos ◽

Carlos Vargas ◽

Luiz Mello ◽

Paulo Pereira ◽

Sandro Gonçalves ◽

...

Keyword(s):

Short Range ◽

Prediction Models ◽

Path Loss ◽

Prediction Method ◽

University Campus ◽

Millimetre Wave ◽

Empirical Prediction ◽

Loss Prediction ◽

Path Loss Prediction ◽

Path Loss Measurements

Abstract In this paper, we present the results of short-range path loss measurements in the microwave and millimetre wave bands, at frequencies between 27 and 40 GHz, obtained in a campaign inside a university campus in Rio de Janeiro, Brazil. Existing empirical path loss prediction models, including the alpha-beta-gamma (ABG) model and the close-in free space reference distance with frequency dependent path loss exponent (CIF) model are tested against the measured data, and an improved prediction method that includes the path loss dependence on the height di erence between transmitter and receiver is proposed. A fuzzy technique is also applied to predict the path loss and the results are compared with those obtained with the empirical prediction models.

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Propagation Path Loss Modeling and Outdoor Coverage Measurements Review in Millimeter Wave Bands for 5G Cellular Communications

International Journal of Electrical and Computer Engineering (IJECE) ◽

10.11591/ijece.v8i4.pp2254-2260 ◽

2018 ◽

Vol 8 (4) ◽

pp. 2254 ◽

Cited By ~ 1

Author(s):

Mohammed B. Majed ◽

Tharek A. Rahman ◽

Omar Abdul Aziz

Keyword(s):

Communication Networks ◽

Millimeter Wave ◽

Wide Spectrum ◽

Path Loss ◽

Separation Distance ◽

Propagation Path ◽

Delay Spread ◽

Propagation Time ◽

60 Ghz ◽

Rms Delay Spread

The global bandwidth inadequacy facing wireless carriers has motivated the exploration of the underutilized millimeter wave (mm-wave) frequency spectrum for future broadband cellular communication networks, and mmWave band is one of the promising candidates due to wide spectrum. This paper presents propagation path loss and outdoor coverage and link budget measurements for frequencies above 6 GHz (mm-wave bands) using directional horn antennas at the transmitter and omnidirectional antennas at the receiver. This work presents measurements showing the propagation time delay spread and path loss as a function of separation distance for different frequencies and antenna pointing angles for many types of real-world environments. The data presented here show that at 28 GHz, 38 GHz and 60 GHz, unobstructed Line of Site (LOS) channels obey free space propagation path loss while non-LOS (NLOS) channels have large multipath delay spreads and can utilize many different pointing angles to provide propagation links. At 60 GHz, there is more path loss and smaller delay spreads. Power delay profiles PDPs were measured at every individual pointing angle for each TX and RX location, and integrating each of the PDPs to obtain received power as a function of pointing angle. The result shows that the mean RMS delay spread varies between 7.2 ns and 74.4 ns for 60 GHz and 28 GHz respectively in NLOS scenario.

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Path Loss Measurements of Indoor LTE System for the Internet of Things

Applied Sciences ◽

10.3390/app7060537 ◽

2017 ◽

Vol 7 (6) ◽

pp. 537 ◽

Cited By ~ 3

Author(s):

Guan-Yi Liu ◽

Tsung-Yu Chang ◽

Yung-Chun Chiang ◽

Po-Chiang Lin ◽

Jeich Mar

Keyword(s):

Internet Of Things ◽

Path Loss ◽

The Internet ◽

Path Loss Measurements ◽

The Internet Of Things

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Rural Macrocell Path Loss Measurements for 5G Fixed Wireless Access at 26 GHz

10.1109/5gwf52925.2021.00064 ◽

2021 ◽

Author(s):

Norshahida Saba ◽

Lauri Mela ◽

Muhammad Usman Sheikh ◽

Jari Salo ◽

Kalle Ruttik ◽

...

Keyword(s):

Path Loss ◽

Wireless Access ◽

Path Loss Measurements ◽

Fixed Wireless Access ◽

Fixed Wireless

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Minimizing The Number of Channel Switches of Mobile Users in Cognitive Radio Ad-Hoc Networks

Journal of Sensor and Actuator Networks ◽

10.3390/jsan9020023 ◽

2020 ◽

Vol 9 (2) ◽

pp. 23 ◽

Cited By ~ 1

Author(s):

Rajorshi Biswas ◽

Jie Wu

Keyword(s):

Cognitive Radio ◽

Ad Hoc Networks ◽

Ad Hoc ◽

Path Loss ◽

Access Point ◽

Primary User ◽

Mobile Users ◽

Mobility Patterns ◽

Current Channel ◽

Hoc Networks

Cognitive radio (CR) technology is envisioned to use wireless spectrum opportunistically when the primary user (PU) is not using it. In cognitive radio ad-hoc networks (CRAHNs), the mobile users form a distributed multi-hop network using the unused spectrum. The qualities of the channels are different in different locations. When a user moves from one place to another, it needs to switch the channel to maintain the quality-of-service (QoS) required by different applications. The QoS of a channel depends on the amount of usage. A user can select the channels that meet the QoS requirement during its movement. In this paper, we study the mobility patterns of users, predict their next locations and probabilities to move there based on its history. We extract the mobility patterns from each user’s location history and match the recent trajectory with the patterns to find future locations. We construct a spectrum database using Wi-Fi access point location data and the free space path loss formula. We propose a machine learning-based mechanism to predict spectrum status of some missing locations in the spectrum database. We formulate a problem to select the current channel in order to minimize the total number of channel switches during a certain number of next moves of a user. We conduct an extensive simulation combining real and synthetic datasets to support our model.

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