MétaCan
Menu
Back to cohort
Record W2101667821 · doi:10.1109/wcnc.2006.1683610

Multi-antenna aspects of wireless fixed relays

2006· article· en· W2101667821 on OpenAlexaff
Abdulkareem Adinoyi, Halim Yanıkömeroğlu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsCarleton University
Fundersnot available
KeywordsComputer scienceComputer networkFadingWirelessAntenna (radio)Nakagami distributionDistributed antenna systemWireless networkElectronic engineeringChannel (broadcasting)TelecommunicationsEngineering

Abstract

fetched live from OpenAlex

Multiple antenna schemes can provide performance enhancement but the small size and cost constraints of wireless terminals preclude their use at these terminals. This paper investigates distributed fixed relays (infrastructure-based relaying) which are engaged in cooperation in a two-hop wireless network as a means of removing the burden of multiple antennas on wireless terminals. In contrast to mobile terminals, a small number of antennas can be deployed on infrastructure-based fixed relays. Hence, the paper investigates performance of the distributed cooperative multi-antenna fixed relays. Threshold maximal ratio combining and threshold selection combining of these multiple antenna signals are studied and analyzed. The following results are derived. For a given performance requirement, the multiple antennas at relays can significantly reduce the number of relays required in a network area, ultimately, reducing system deployment cost. In addition, threshold selection combining at the relays represents an excellent compromise between performance and system cost. Finally, the analysis performed in this paper uses the versatile Nakagami fading channel model

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.936
Threshold uncertainty score0.232

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.036
GPT teacher head0.267
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

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".

Quick stats

Citations10
Published2006
Admission routes1
Has abstractyes

Explore more

Same topicCooperative Communication and Network CodingFrench-language works237,207