Optical beamforming for retro-directive array antennas
Bibliographic record
Abstract
In this paper we introduce a novel algorithm for the beamforming of a single channel retro-directive phased array system. Retro-directive array antennas are the best candidate for two-way communication, however there must be a large spectral difference between the send and receive carriers to reduce the interference and increase the isolation. When the send and receiver RF frequencies are far apart, e.g. 10 GHz, optical beamforming provides the unique solution to beamforming problem. Moreover single channel array antennas are hardware efficient and cost-effective. The core of the proposed structure is a cascaded ring resonator structure with two parallel waveguides, which can perform the roles of both a tunable optical delay line and a directional coupler. Hence, there is no need to use an optical circulator to separate the reception path from the transmission path. The received RF signal from the antenna is modulated with an optical carrier, ?C, and enters the delay line. The beamforming algorithm calculates the carrier wavelength and the coupling factors between the adjacent rings to maximize the received power from the desired source. Thermo-optics (TO) phase shifters are used to adjust the coupling factors. The algorithm calculates the optimum coupling factors based on the instantaneous feedback from the receiver array, hence it is robust and can compensate for the environmental changes or even the relative motion of the source and antenna platform. The delayed signal that leaves the delay line is demodulated by a photodiode (PD). The RF signal is amplified, filtered and delivered to the base-band receiver for decoding. A sample of the demodulated RF signal is used as the input to the beamforming algorithm to calculate the received power and signal to noise ratio. Based on the time-reversal property of the retro-directive arrays, the same amount of delay is required for the transmitter antenna, so the coupling factors do not need to change.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".