Massive-MIMO Hybrid Precoder Design Using Few-Bit DACs for 2D Antenna Array Structures
Bibliographic record
Abstract
This paper investigates the performance of different antenna array structures for hybrid massive-MIMO precoding schemes using few-bit DACs. Particularly, the proposed hybrid scheme includes two precoding stages: the RF-beamforming stage is designed via the slowly time-varying channel second-order correlation matrix, while the baseband multi-user (MU) precoding stage is constructed via the regularized zero-forcing (RZF) technique to mitigating the MU-interference. For the same system cost and complexity, we examine the achieved sum-rate and energy efficiency of various 2D antenna array structures, namely, uniform linear array (ULA), uniform rectangular array (URA), uniform circular array (UCA), and concentric circular array (CCA), in serving multiple users at different angular locations. The Monte Carlo simulation results indicate the higher achievable rate and energy efficiency of CCA by using low-resolution DACs as compared to various 2D array structures. We also show that only (3-5)-bit DACs are sufficient to provide comparable spectral and energy efficiencies.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".