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Record W2131869931 · doi:10.1109/isit.2011.6033800

On the maximum achievable rates in the decode-forward diamond channel

2011· article· en· W2131869931 on OpenAlexaff
Mahdi Zamani, Amir K. Khandani

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsRelayComputer scienceRayleigh fadingDecoding methodsFadingChannel (broadcasting)ThroughputChannel state informationTopology (electrical circuits)Computer networkWirelessAlgorithmTelecommunicationsMathematicsPhysics

Abstract

fetched live from OpenAlex

This paper studies the problem of two-hop transmission from a single-antenna source to a single-antenna destination via two single-antenna relays. The relays operate in a full-duplex mode and they are not capable of buffering data. The links from the source to the relays and from the relays to the destination are considered to be Rayleigh block fading and there is no direct link between the source and the destination. There is also no link between the relays. Consequently, the half-duplex mode is a direct result of the full-duplex mode with frequency or time division. All nodes are assumed to be oblivious to their forward-channel gains, however, they have perfect information about their backward-channel gains. We also assume a stringent decoding delay constraint of one fading block that makes the definition of ergodic (Shannon) capacity meaningless. Hence, we adopt the broadcast approach (multi-layer coding) to maximize the expected-rate received at the destination. For this purpose, the decode-forward (DF) relaying adopting the broadcast approach is proposed. The main feature of the proposed scheme is that the layers being decoded at both relays are added coherently at the destination although each relay has no information about the number of layers being successfully decoded by the other relay. It is proved that the optimum strategy maximizing the throughput and expected-rate is to send uncorrelated signals over the relays. The maximum throughput is analytically formulated. An achievable rate as well as upper-bounds are presented for the maximum expected-rate of the channel.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.005
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.024
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0010.003
Scholarly communication0.0030.004
Open science0.0020.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.082
GPT teacher head0.275
Teacher spread0.194 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations3
Published2011
Admission routes1
Has abstractyes

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