Millimeter-Wave CMOS Sourceless Receiver Architecture for 5G-Served Ultra-Low-Power Sensing and Communication Systems
Bibliographic record
Abstract
In this paper, an extremely low-power and low-complexity CMOS sourceless millimeter-wave (mmW) receiver for the next-generation wireless communication and sensing systems including fifth-generation (5G) is proposed and demonstrated. It makes the use of injection-locked self-oscillating mixers (SOMs) in order to enable a direct conversion to baseband without resorting to any external local oscillator (LO) nor an IF processing block, therefore, greatly reducing power consumption, as well as the receiver's complexity. This architecture is created through multi-input and multi-output (MIMO) arrays in connection with slicing frequency spectrum or frequency band of interest. In this way, the proposed receiver supports a high data transmission throughput based on the frequency-diversified MIMO, which presents a unique feature in the architectural implementation of a low-power and high bit-rate communication and sensing systems. Transmission and demodulation of a digital modulated signal M-quadratic-amplitude modulation (M-QAM) at 40 GHz, is successfully demonstrated with simulated and measured results.
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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) | 0.002 | 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".