Performance Bounds for Combined Channel Coding and Space-Time Block Coding with Receive Antenna Selection
Bibliographic record
Abstract
This paper studies the performance of the concatenation of an outer channel code with an orthogonal spacetime block code (STBC), where the outer code can be a convolutional code (CC) or a trellis-coded modulation (TCM) code. In particular, we derive upper bounds on the bit error rate (BER) for this concatenation scheme with receive antenna selection. In our analysis, we assume that 1) the receiver uses only L out of the available M receive antennas, where, typically, L < M, 2) the selected antennas are those that maximize the instantaneous received signal-to-noise ratio (SNR), 3) the channel state information is perfectly known at the receiver, 4) the underlying channel is fully interleaved, and 5) the underlying orthogonal STBC is full-rate. We derive an explicit upper bound on the BER for the above concatenation scheme for any N, M and L, where N denotes the number of transmit antennas. We show that the diversity order, with antenna selection, is the same as that of the full complexity system, whereas the deterioration in SNR is upper bounded by 10 log10 (M/L) dB. We also derive a tighter upper bound on the BER for the Alamouti scheme when the receiver uses the best antenna, i.e., L = 1. These upper bounds can be extended in a straightforward manner to other types of outer codes and fading channels, including fast, block and slow fading channels. Finally, we present simulation results that validate our analysis.
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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 | 0.000 | 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".