Performance Bounds for Space–Time Block Codes With Receive Antenna Selection
Bibliographic record
Abstract
In this correspondence, we present a comprehensive performance analysis of orthogonal space-time block codes (STBCs) with receive antenna selection. For a given number of receive antennas M, we assume that the receiver uses the best L of the available M antennas, where, typically, L/spl les/M. The selected antennas are those that maximize the instantaneous received signal-to-noise ratio (SNR). We derive explicit upper bounds on the bit-error rate (BER) performance of the above system for any M and L, and for any number of transmit antennas. We show that the diversity order, with antenna selection, is maintained as that of the full complexity system, whereas the deterioration in SNR is upper-bounded by 10log/sub 10/(M/L) decibels. Furthermore, we derive a tighter upper bound for the BER performance for any N and M when L=1, and derive an expression for the exact BER performance for the Alamouti scheme when L=1. We also present simulation results that validate our analysis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".