Joint CSI Estimation, Beamforming and Scheduling Design for Wideband Massive MIMO System
Bibliographic record
Abstract
This paper proposes a novel approach for designing channel estimation, beamforming and scheduling jointly for wideband massive multiple input multiple output (MIMO) systems. With the proposed approach, we first quantify the maximum number of user equipments (UEs) that can send pilots which may or may not be orthogonal. Specifically, when the channel has a maximum of ℒ multipath taps, and we allocate $\tilde{M}$ sub-carriers for the channel state information (CSI) estimation, a maximum of $\tilde{M}$ UEs' CSI can be estimated (ℒ times compared to the conventional CSI estimation approach) in a massive MIMO regime. Then, we propose to schedule a subset of these UEs using greedy based scheduling to transmit their data on each sub-carrier with the proposed joint beamforming and scheduling design. We employ the well known maximum ratio combiner (MRC) beamforming approach for the uplink channel data transmission. All the analytical expressions are validated via numerical results, and the superiority of the proposed design over the conventional orthogonal frequency division multiplexing (OFDM) transmission approach is demonstrated using extensive numerical simulations in the long term evolution (LTE) channel environment. The proposed channel estimation and beamforming design is linear and simple to implement.
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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) | 0.001 | 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".