Sum Rate Analysis of Generalized Space Shift Keying-Aided MIMO-NOMA Systems
Bibliographic record
Abstract
We investigate the sum rate performance of a generalized space shift keying (GSSK)-aided, non-orthogonal multiple access (NOMA) network. In particular, we consider a multiple-input multiple-output (MIMO) NOMA downlink channel, where the base station employs GSSK modulation to transmit additional information to the NOMA users. We present a novel energy-based maximum likelihood (ML) detection strategy at the NOMA users to decode the active antenna indices. We derive a closed-form expression for the average pairwise error probability of the energy-based ML strategy to find a union bound on the bit error probability. Further, we derive the expression for the overall sum rate of the proposed GSSK-aided MIMO-NOMA system. Through numerical evaluations, we show that the proposed system outperforms the conventional MIMO-NOMA system, in terms of spectral efficiency.
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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 | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".