An Investigation of Spectral Efficiency in Linear MRC and MMSE Detectors with Perfect and Imperfect CSI for Massive MIMO Systems
Bibliographic record
Abstract
In this paper, the performance of two linear detectors in multi-user (MU) multiple-input multiple-output (MIMO) systems is investigated. The uplink sum rate and lower bound of channel capacity is derived for both maximum-ratio combination (MRC) and minimum mean square error (MMSE) schemes considering imperfect and perfect channel state information (CSI) conditions. Results show that linear detector performance improves dramatically when the number of base station (BS) users is smaller than that of BS antennas. It is being demonstrated that in the case of imperfect CSI and the number of BS antennas in the conditions of perfect CSI the transmitting power of users can be decreased by the square root of the number of BS antennas. Simulation results show that the MMSE detector outperforms the MRC detector. The results indicated that the system's uplink sum rate is increased by using significantly larger antenna arrays as opposed to just one antenna system. The findings of the Monte-Carlo simulation are very close to the analytical results.
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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 | 0.000 | 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 | 0.000 | 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".