Radio-Propagation-Measurement-Based Simulations of the Capacity of Multi-User D-MIMO Indirect Path Communication Systems in a Small Cluttered Room at 2, 18, and 28 GHz
Bibliographic record
Abstract
This paper reports multi-user D-MIMO system capacity calculations for 4x4 D-MIMO channels, simulated using transmission loss and indirect path loss variation models derived from channel sounding measurements made with a vector-network-analyser (VNA) based channel sounding system. The channel sounding measurements were made with a bandwidth of 500 MHz at centre frequencies of 2.4 GHz, 18 GHz, and 28 GHz, in a small cluttered study room. Transmission was from an emulated sector antenna mounted with a downtilt of 62.5 degrees above the suspended ceiling in the room at a height of 4 m above floor level. Reception was at 45 desk-top-height locations scattered throughout the room using an omni directional antenna at 2.4 GHz, and step-wise azimuth and elevation scanning horn antennas with 10 deg. beamwidths in both planes, which scanned for maximum received power at 18 GHz and 28 GHz. Reported results show that, given the same average SNR, D-MIMO system capacities are approximately the same with no beam steering at UEs at 2 GHz and with beam steering at UEs at 18 and 28 GHz. In the scenario considered, between 20 dB and 25 dB and between 30 dB and 35 dB more system gain is required at 18 GHz and at 28 GHz, respectively, to achieve the same SNR as at 2 GHz. However, it is considered that when beams are steered at a UE to receive maximum power from specular reflections, it might be possible to avoid the deleterious effects of correlations in spatial transmission loss variations and interference. In this case, significant increases in outage capacity (e.g. 3 bits/s/Hz, compared with 1 bit/s/Hz, at SNR=6 dB) can be achieved at the same SNR, with respect to that in conventional 2 GHz systems, when the steering of narrow beams to the direction of maximum received power is employed.
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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 | 0.001 | 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".