Compact ultra-wide band two element vivaldi non-uniform slot MIMO antenna for body-centric applications
Bibliographic record
Abstract
This work presents a novel compact two-port Vivaldi Non-uniform Slot MIMO Antenna (VNSMA) to overcome the challenges of traditional ultra-wideband (UWB) antennas, such as large size, limited bandwidth (BW), high mutual coupling, and suboptimal performance in wearable devices. Designed based on Vivaldi non-uniform slot profile antenna (VNSPA) theory, this antenna offers superior performance metrics and significantly advances wearable antenna technology. The novelty of this work is investigating different positions for the two compact UWB Vivaldi nonuniform Antennas (VNSAs) to get better performance with smaller sizes, wider impedance matching BW, and lower mutual coupling (MC) where side by side at an angle of 180ᵒ is determined to be the best configuration. Detailed parametric studies were performed on this configuration for better performance, where the MC was further reduced by etching the ground plane with a vertical slot between the two antennas and L slots around the Microstrip to Slot (M/S) transition, respectively. Furthermore, BW and gain enhancements were obtained by etching exponential tapered and triangular slots at its two edges. Using the Finite Integration Technique (FIT), Computer Simulation Technology (CST) software is used for the simulations in this work. The VNSMA is tested on a CST Gustav human phantom and gives excellent results with low specific absorption rate (SAR) values at several UWB frequencies. The proposed VNSMA provides good, measured outcomes of S 11 < −11.08 dB with wide BW of 12.5 GHz (2.33–14.83 GHz) covering high isolation of −23 dB (for most of frequency band), moderate-high gain of 5.89 dBi, radiation efficiency of 66–90 %, low Envelope Correlation Coefficient (ECC) of 0.002 and high diversity gain (DG) of 9.99 dBi, stable radiation patterns, and average group delay of 1.2 ns. This innovative design, which optimizes antenna positioning and incorporates ground plane modifications, achieves remarkable improvements in BW, which covers multiple bands, including WLAN (2.4–2.485 GHz), X-band (8–12 GHz), and part of Ku band (12–18 GHz). The findings demonstrate the antenna's potential for various high-resolution microwave imaging applications, particularly in medical diagnostics like breast and brain cancer detection, showcasing its impact in wearable technology and healthcare.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".