133 research outputs found
Automatic and Flexible Transmission of Semantic Map Images using Polar Codes for End-to-End Semantic-based Communication Systems
Semantic communication represents a promising roadmap toward achieving
end-to-end communication with reduced communication overhead and an enhanced
user experience. The integration of semantic concepts with wireless
communications presents novel challenges. This paper proposes a flexible
simulation software that automatically transmits semantic segmentation map
images over a communication channel. An additive white Gaussian noise (AWGN)
channel using binary phase-shift keying (BPSK) modulation is considered as the
channel setup. The well-known polar codes are chosen as the channel coding
scheme. The popular COCO-Stuff dataset is used as an example to generate
semantic map images corresponding to different signal-to-noise ratios (SNRs).
To evaluate the proposed software, we have generated four small datasets, each
containing a thousand semantic map samples, accompanied by comprehensive
information corresponding to each image, including the polar code
specifications, detailed image attributes, bit error rate (BER), and frame
error rate (FER). The capacity to generate an unlimited number of semantic maps
utilizing desired channel coding parameters and preferred SNR, in conjunction
with the flexibility of using alternative datasets, renders our simulation
software highly adaptable and transferable to a broad range of use cases
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