Bibliographic record
Abstract
In the last three decades, the explosive growth of mobile and wireless communications has radically changed the life of people. Wireless services have migrated from the conventional voice-centric services to data-centric services. The circuit-switched communication network is now being replaced by the all-IP packet-switched network. Mobile communications have also evolved from the first-generation (1G) analog systems to the third-generation (3G) systems now being deployed, and the fourth-generation (4G) systems are now under development and are expected to be available by 2010. The evolution of wireless networking has also taken place rapidly during this period, from low-speed wireless local-area networks (LANs) to broadband wireless LANs, wireless metropolitan area networks (MANs), wireless wide-area networks (WANs), and wireless personal-area networks (PANs). Also, broadband wireless data service has been expanded into broadcasting service, leading to satellite TV broadcasting and wireless regional-area networks (RANs) for digital TV. The data rate has also evolved from the 10 kbits/s voice communications to approximately 1 Gbit/s in the 4G wireless network. In addition, the 4G wireless network will provide ubiquitous communications. Scope and Purpose A complete wireless system involves many different areas. However, most existing textbooks on wireless communications focus only on the fundamental principles of wireless communications, while many other areas associated with a whole wireless system, such as digital signal processing, antenna design, microwave and radio frequency (RF) subsystem design, speech coding, video coding, and channel coding, are left to other books.
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 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.413 | 0.281 |
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".