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Record W1857970051 · doi:10.1109/icupc.1995.496879

Performance issues in successive interference cancellation with reference symbol assisted channel estimation

2002· article· en· W1857970051 on OpenAlexafffund
A.C.K. Soong, Witold A. Krzymień

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSingle antenna interference cancellationCode division multiple accessComputer scienceInterference (communication)Channel (broadcasting)Phase-shift keyingElectronic engineeringBit error rateChannel capacityAlgorithmAdjacent-channel interferenceTopology (electrical circuits)TelecommunicationsEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

Direct sequence code division multiple access (DS-CDMA) is a leading candidate scheme to be used in the second generation cellular and personal communication systems. A novel multi-stage successive interference cancellation scheme is proposed which operates on the reverse CDMA link using BPSK modulation, coherent detection and reference symbols to obtain channel estimates. The results of a single cell multi-user investigation show that the traffic capacity can be increased. However, the total traffic capacity is somewhat disappointing because the channel estimates are corrupted significantly by interference from symbols not yet demodulated and cancelled by the receiver. The transmitted signal structure is, therefore, modified to decrease that interference. The results of a single cell analysis of the modified cancellation scheme demonstrate that the system's traffic capacity reaches approximately 80% of that of a multistage successive interference cancelling receiver operating on perfect channel parameters. The multi-cell results show that for hexagonal cell geometry with path loss exponent of 4 and without any forward error correction coding the capacity of the system is between 1.5 and 2.5 times that using the conventional matched filter receiver.

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: Empirical · Consensus signal: none
Teacher disagreement score0.782
Threshold uncertainty score0.460

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.059
GPT teacher head0.296
Teacher spread0.237 · 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

Citations5
Published2002
Admission routes2
Has abstractyes

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