Image Transmission Analysis using CSS Modulation Scheme
Vítor Fialho
Vitor Fialho, DEETC, Instituto Superior de Engenharia de Lisboa and Centre of Technology and Systems, Lisbon, Portugal.
Manuscript received on 30 October 2023 | Revised Manuscript received on 03 November 2023 | Manuscript Accepted on 15 November 2023 | Manuscript published on 30 November 2023 | PP: 32-35 | Volume-12 Issue-12, November 2023 | Retrieval Number: 100.1/ijitee.L975311121223 | DOI: 10.35940/ijitee.L9753.11121223
Open Access | Editorial and Publishing Policies | Cite | Zenodo | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Image transmission through low-speed communication systems has been a challenge to overcome in the last few years. Actual IoT technologies are supported by LPWAN, where power consumption is a primary consideration. The image transmission study presented in this paper is based on the Chirp Spread Spectrum (CSS) modulation scheme used by LoRa. A simulation model for image transmission is presented, where the communication channel is based on additive white Gaussian noise (AWGN), with a configurable signal-to-noise ratio (SNR). This model enables the modification of several LoRa CSS parameters, including spreading factor (SF), bandwidth (BW), and code rate (CR). The adopted metrics for evaluating the proposed methodology are symbol error rate (SER), bit error rate (BER), and peak signal-to-noise ratio (PSNR). The first two figures of merit enable the study of transmission quality, and the last one allows for the inference of the received image quality. For SF=8 and SNR=-10 dB, the obtained values of SER and BER are 0.001 and 1 × 10^ (-4), respectively. These values will result in a PSNR of 21 dB.
Keywords: CSS, LoRaWAN, Image transmission, SER, SNR and PSNR
Scope of the Article: Image Analysis and Processing