System-Level Design of a Full-Duplex Wireless Transceiver for Brain–Machine Interfaces
Bibliographic record
Abstract
We propose a new wireless communication architecture for implanted systems that simultaneously stimulates neurons and record neural responses. This architecture can support large numbers of electrodes (>500), providing 100 Mb/s for the downlink of stimulation signals, and gigabits per second for the uplink of neural recordings. We propose a full-duplex transceiver architecture that shares one antenna for both the ultrawideband (UWB) and the 2.45-GHz industrial, scientific, and medical band. A new pulse shaper is used for the gigabits per second uplink to simplify the transceiver design, while supporting several modulation formats with high data rates. To validate our system-level design for brain-machine interfaces, we present an ex-vivo experimental demonstration of the architecture. While the system design is for an integrated solution, the proof-of-concept demonstration uses discrete components. Good bit error rate performance over a biological channel at 0.5-, 1-, and 2-Gb/s data rates for uplink telemetry (UWB) and 100 Mb/s for downlink telemetry (2.45-GHz band) are achieved.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".