MétaCan
Menu
Back to cohort
Record W2045220515 · doi:10.1002/dac.611

Roaming times of multi‐wireless systems for software defined radio

2003· article· en· W2045220515 on OpenAlexaff
YingRao Wei, A.K. Elhakeem

Bibliographic record

VenueInternational Journal of Communication Systems · 2003
Typearticle
Languageen
FieldEngineering
TopicPower Line Communications and Noise
Canadian institutionsConcordia University
Fundersnot available
KeywordsRoamingComputer scienceBase stationWirelessComputer networkSoftware-defined radioReconfigurabilityChannel (broadcasting)Telecommunications

Abstract

fetched live from OpenAlex

Abstract In this paper, we evaluate the roaming time performance for a reconfigurable multi‐mode mobile station (MS) that experiences possible transition from one kind of wireless system standard to another. In future software defined radio systems (SDR) (IEEE Commun Mag 2000; 138–143, IEE 1998; 1–6, IEEE 1999; 1212–1216, IEEE Commun Mag 1995; 33 ), reconfigurability of the MS is achieved by downloading the system configuration software code over the wireless channel. For evaluation of the roaming times, a generalized state diagram of the multi‐mode MS is presented. We focus on evaluating the times for sensing the universal pilot channel, classic base station pilot channel, association and connection establishment signaling are included. We investigate the effects of packet successful transmission probability over the wireless channel. We also consider the effects of the system resource blocking probability, MS resource blocking probability, and signaling bit rate over the universal base station channel for different cases and design scenarios. Such evaluations are important for prior design of SDR mobile terminal and universal base station in global roaming situations. We include some analysis results from many obtained. These show the feasibility of wireless software download, and switching between different wireless standard as the mobile station roams. Copyright © 2003 John Wiley & Sons, Ltd.

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.888
Threshold uncertainty score0.509

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.028
GPT teacher head0.279
Teacher spread0.251 · 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
GenreEmpirical

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

Citations1
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Communication SystemsSame topicPower Line Communications and NoiseFrench-language works237,207