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Record W4390753779 · doi:10.1109/tvt.2024.3350790

RIS Empowered Index Modulation-Based Receive Diversity Wireless System With Nakagami-$m$ Fading Channels

2024· article· en· W4390753779 on OpenAlexaff
Aritra Basu, Soumya P. Dash, Debasish Ghose

Bibliographic record

VenueIEEE Transactions on Vehicular Technology · 2024
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Technologies
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsFadingNakagami distributionDemodulationModulation (music)Bit error rateTransmitterWirelessKeyingMaximal-ratio combiningNotationMathematicsAntenna diversityAlgorithmComputer scienceTelecommunicationsChannel (broadcasting)PhysicsArithmetic

Abstract

fetched live from OpenAlex

Reconfigurable intelligent surfaces (RIS) and index modulation (IM) have been proven as potential technologies for improving the performance of next-generation wireless communication systems. In this paper, we consider the study of a receive diversity RIS-assisted wireless communication system employing two IM schemes, namely, space-shift keying (SSK) and spatial modulation (SM) for data transmission over Nakagami- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$m$</tex-math></inline-formula> fading channels. Considering the RIS to lie in close proximity to the transmitter, a receiver structure based on a greedy detection rule is proposed to select one of the receive diversity branches with the highest received energy for demodulation. Based on this system model, novel closed-form expressions for the probability of erroneous index detection (PED) of the considered target receive diversity branch, and the corresponding asymptotic expressions at a high signal-to-noise ratio (SNR) are obtained using a characteristic function approach. Furthermore, closed-form and asymptotic expressions at high SNR for the bit error rate (BER) for the SSK-based system and the SM-based system employing <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$M$</tex-math></inline-formula> -ary phase-shift keying and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$M$</tex-math></inline-formula> -ary quadrature amplitude modulation schemes are also derived. The dependencies of the performance of the considered system are also corroborated via numerical results. The asymptotic expressions and results of PED and BER at high and low SNR values lead to the observation of a performance saturation and the presence of an SNR value as a point of inflection attributed to the greedy detector's structure.

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 categoriesMeta-epidemiology (narrow)
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 score0.818
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.010
GPT teacher head0.213
Teacher spread0.203 · 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.

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

Citations13
Published2024
Admission routes1
Has abstractyes

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