BER analysis of space–time diversity in CDMA systems over frequency-selective fading channels
Bibliographic record
Abstract
The performance of direct-sequence code division multiple access (DS-CDMA) using space–time spreading system, over frequency-selective fading channels, is investigated. The underlying transmit diversity scheme, previously introduced in the literature, is based on two transmit and one receive antenna. It was shown that when employed in flat fast-fading channels, the received signal quality can be improved by utilising the spatial and temporal diversities at the receiver side. We study the problem of multiuser interference in asynchronous CDMA systems that employ transmit/receive diversity using space–time spreading. To overcome the effects of interference, a decorrelator detector is used at the base station. Considering binary phase-shift keying transmission, we analyse the system performance in terms of its probability of bit error. In particular, we derive the probability of error over frequency-selective Rayleigh fading channels for both fast and slow-fading channels. For the fast-fading channel, both simulations and analytical results show that the full system diversity is achieved. On the other hand, when considering a slow-fading channel, we show that the scheme reduces to conventional space–time spreading schemes where the diversity order is half of that of fast-fading.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".