Robust precoder design for massive MIMO with peak total power constrained single‐RF‐chain transmitters
Bibliographic record
Abstract
Massive multiple‐input multiple‐output (MIMO) transmission/reception is a very promising enablingtechnique for future cellular systems. The performance of massive MIMO systemsrelies on the availability of channel state information (CSI) at thetransmitter. However, due to estimation errors and delay this CSI is imperfect. Additionally, the use of many radio frequency (RF) chains to drive a largenumber of antennas at the transmitter quickly becomes impractical when thatnumber increases. Thus, reducing the number of RF chains in massive MIMO systemsis essential in order to reduce the system complexity and cost. Considering amassive MIMO system with a single‐RF‐chain transmitter, in this study, theauthors design a precoding technique that is robust to the channel uncertainty. To reflect realistic restrictions in the authors' design, they consider the peaktotal transmitted power rather than the average power constraint. Also, theyconsider imperfect CSI and model the uncertainty region as a bounded one, whichis a reasonable assumption. In this transmitter structure, there is only onepower amplifier and load modulation rather than voltage modulation is used togenerate the desired signals on the antenna elements. They demonstrate that whena very simple fixed equaliser is used at all user terminals, the problem ofminimising the mean‐square error of the received signals at user terminals underthe worst‐case channel uncertainty can be transformed into a convex optimisationproblem. They provide simulation results and demonstrate that the proposedrobust precoding technique outperforms non‐robust techniques in terms of powerefficiency and signal‐to‐interference‐plus‐noise ratios.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".