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Record W2159500641 · doi:10.1109/wcnc.2005.1424617

A practical RAKE combining scheme for synchronous CDMA systems

2005· article· en· W2159500641 on OpenAlex
Wei Li, Hong‐Chuan Yang, T. Aaron Gulliver

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsRake receiverRakeCode division multiple accessFadingComputer scienceMaximal-ratio combiningAlgorithmSignal-to-noise ratio (imaging)Synchronization (alternating current)Diversity combiningMathematicsElectronic engineeringTelecommunicationsChannel (broadcasting)Decoding methodsEngineering

Abstract

fetched live from OpenAlex

In this paper we consider the performance of a RAKE receiver in a code division multiple access (CDMA) system employing maximal-ratio combining. A simple select and combine algorithm is introduced in which the RAKE receiver combines only the synchronization path and those resolvable paths with a signal-to-noise ratio (SNR) larger than a given threshold. We analyze its performance based on moment generating functions of the SNR of the combined signal. We study the cases with equal and unequal average SNR for different diversity paths. In particular, closed-form expressions for the average combined SNR and symbol error probability with the proposed RAKE receiver over block fading channels are derived. We also study the outage probability of the system and the number of channels estimated. Numerical results are given to illustrate the analytical results.

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.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.920
Threshold uncertainty score0.401

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 communication0.0000.001
Open science0.0010.001
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 head0.072
GPT teacher head0.367
Teacher spread0.295 · 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

Quick stats

Citations7
Published2005
Admission routes1
Has abstractyes

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