QoS based Joint Radio Resource Allocation for Multi-Homing Calls in Heterogeneous Wireless Access Network
Bibliographic record
Abstract
In this paper, we propose QoS based radio resource allocation, where multi modal users are capable to connect to multi-RATs in heterogeneous wireless access network (HWAN). Our optimization problem is based on system sum-rate maximization under the QoS constraint. We propose a joint radio resource allocation scheme where we use Lagrange duality and dual update method to find a solution for the optimal allocation of subcarrier and power in OFDMA system and optimal time share in WLAN system. Numerical results show that the overall sum-throughput of our proposed optimal resource allocation algorithm in HWAN for multi-RAT approach outperforms the single RAT approach that uses WLAN or OFDMA based system. Furthermore, we analyze the impact of minimum data rate requirement of mobile users on the convergence rate of our proposed algorithm. Matlab based simulation results show that convergence rate of our propose algorithm is independent of the minimum data rate requirement of users.
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 | 0.001 | 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".