Dynamic capacity allocation for multimedia services in TDMA/CDMA cellular networks
Bibliographic record
Abstract
This paper addresses the radio resource management (RRIM) structure and efficient dynamic capacity allocation techniques for hybrid TDMA/CDMA mobile cellular networks to support multimedia services with different quality-of-service (QoS) requirements in an interference-limited environment. Based on the received interference information, the minimum instantaneous power (MIP) algorithm aims to assign timeslot-codes that minimize the required transmitted power to maintain a target SINR. However, the MIP, being distributed, does not make any attempt to avoid generation of interference elsewhere across the network. Aiming to reduce both potentially received and generated interference in timeslot-code assignment, the proposed minimum sum of path-loss ratio (MS-PLR) algorithm incorporates the mutual large-scale path-loss ratios between different active mobiles in the cost function of a given timeslot during assignment. Simulation results for various traffic scenarios are used for performance evaluation and comparison. It is shown that MS-PLR can offer an additional capacity increase of 24% over MIP. The impacts of bursty WWW traffic on speech performance are also examined.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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".