On the Achievable Rate and Average Sum Capacity of Spread Spectrum Underlay CR Networks
Bibliographic record
Abstract
In this paper, we investigate the achievable rate and the average sum capacity of an underlay cognitive radio (CR) (also known as a secondary) system. We consider single user (SU) and multiple users (MU) secondary systems that deploy spread spectrum as the signaling technique which utilizes the whole available spectrum. The objective is to maximize the achievable rate and the average sum capacity of the SU and MU secondary systems, respectively, by allocating the optimum power to the secondary transmitter(s) (STs), such that the instantaneous (aggregate) interference power from STs is below a certain threshold at the primary receiver (PR), to guarantee the quality of service (QoS) of the primary system. Numerical and Monte-Carlo Simulation results show that the achievable rate of the SU system and the average sum capacity of the MU system can be enhanced significantly compared to other signaling techniques, because of the fact that in spread spectrum the signal's power is spread over a wider bandwidth, which gives the secondary system more freedom to allocate power to enhance the data rate.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".