{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T15:17:19Z","timestamp":1781623039370,"version":"3.54.5"},"reference-count":136,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2025,7,21]],"date-time":"2025-07-21T00:00:00Z","timestamp":1753056000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,7,21]],"date-time":"2025-07-21T00:00:00Z","timestamp":1753056000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100001795","name":"University of Southern Queensland","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100001795","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Artif Intell Rev"],"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:p>Communication systems continue to embrace the potential of Artificial Intelligence (AI) in error correction codes (ECC) with coded modulation schemes (CMS). Despite this, there remains a substantial performance gap in AI methods in terrestrial and satellite communication systems. Additionally, AI and power efficiency for Low Earth Orbit (LEO) satellites have shown a critical gap. To the best of the author\u2019s knowledge, this is the first Systematic literature review attempting to bridge this vital gap to boost efficiency and add fault tolerance. From 389 articles published between 1993 and 2023, the construction and performance of 33 AI algorithms have been comprehensively reviewed for 16 ECC, seven higher-order CMS, and LEO satellites. Based on four key parameters: error correction, modulation, power, and energy efficiency, the PRISMA strategy with a 27-item checklist was adopted and 63 studies were selected to investigate the AI-based performance of terrestrial (40-studies) and LEO satellites (23-studies). Analysing nine performance metrics, Convolutional Neural Network was the most popular choice (20.6%) with an accuracy of 99% and SNR from 6-20dB, followed by Deep Neural Network (19.04%). The least used algorithm was Reinforcement learning (9.52%). Modified Reed Solomon codes showed the best measurement of power consumption and error rate. Adaptive LDPC codes provided a 45% increase in energy efficiency with an 11% computation decrease. Considering appropriate merits and challenges, the review identifies, discusses, and synthesises AI results to create a summary of current evidence for terrestrial and LEO satellites contributing to evidence-based practice for future researchers.<\/jats:p>","DOI":"10.1007\/s10462-025-11317-4","type":"journal-article","created":{"date-parts":[[2025,7,21]],"date-time":"2025-07-21T06:36:52Z","timestamp":1753079812000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["A comprehensive systematic literature review on artificial intelligence for error correction and modulation schemes in next-generation satellite communications"],"prefix":"10.1007","volume":"58","author":[{"given":"Ekta","family":"Sharma","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christopher P.","family":"Davey","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ravinesh C.","family":"Deo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Brad D.","family":"Carter","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sancho","family":"Salcedo-Sanz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,7,21]]},"reference":[{"key":"11317_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1687-1499-2014-204","volume":"2014","author":"N Abughalieh","year":"2014","unstructured":"Abughalieh N, Steenhaut K, Now\u00e9 A, Anpalagan A (2014) Turbo codes for multi-hop wireless sensor networks with decode-and-forward mechanism. EURASIP J Wirel Commun Netw 2014:1\u201313. https:\/\/doi.org\/10.1186\/1687-1499-2014-204","journal-title":"EURASIP J Wirel Commun Netw"},{"issue":"6","key":"11317_CR2","doi-asserted-by":"publisher","first-page":"447","DOI":"10.1109\/LCOMM.2008.080017","volume":"12","author":"E Arikan","year":"2008","unstructured":"Arikan E (2008) A performance comparison of polar codes and reed-muller codes. IEEE Commun Lett 12(6):447\u2013449. https:\/\/doi.org\/10.1109\/LCOMM.2008.080017","journal-title":"IEEE Commun Lett"},{"issue":"6","key":"11317_CR3","doi-asserted-by":"publisher","first-page":"3440","DOI":"10.1109\/TCOMM.2020.2977280","volume":"68","author":"E Balevi","year":"2020","unstructured":"Balevi E, Andrews JG (2020) Autoencoder-based error correction coding for one-bit quantization. IEEE Trans Commun 68(6):3440\u20133451. https:\/\/doi.org\/10.1109\/TCOMM.2020.2977280","journal-title":"IEEE Trans Commun"},{"key":"11317_CR4","unstructured":"Barto AG, Sutton RS (1995) Reinforcement learning. Handbook of brain theory and neural networks, 804-809"},{"issue":"7","key":"11317_CR5","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1145\/3448250","volume":"64","author":"Y Bengio","year":"2021","unstructured":"Bengio Y, Lecun Y, Hinton G (2021) Deep learning for ai. Commun ACM 64(7):58\u201365. https:\/\/doi.org\/10.1145\/3448250","journal-title":"Commun ACM"},{"key":"11317_CR6","doi-asserted-by":"crossref","unstructured":"Berrou C, Glavieux A, Thitimajshima P (1993) Near shannon limit errorcorrecting coding and decoding: Turbo-codes. 1. Proceedings of icc\u201993-ieee international conference on communications (Vol. 2, p. 1064-1070). IEEE","DOI":"10.1109\/ICC.1993.397441"},{"issue":"2","key":"11317_CR7","doi-asserted-by":"publisher","first-page":"401","DOI":"10.1109\/TMTT.2016.2515586","volume":"64","author":"J Besnoff","year":"2016","unstructured":"Besnoff J, Abbasi M, Ricketts DS (2016) High data-rate communication in near-field rfid and wireless power using higher order modulation. IEEE Trans Microw Theory Tech 64(2):401\u2013413. https:\/\/doi.org\/10.1109\/TMTT.2016.2515586","journal-title":"IEEE Trans Microw Theory Tech"},{"key":"11317_CR8","doi-asserted-by":"crossref","unstructured":"Bhise A, Vyavahare PD (2012) Modified turbo codes for next generation wireless networks. 2012 ninth international conference on wireless and optical communications networks (wocn) (p. 1\u20136). IEEE","DOI":"10.1109\/WOCN.2012.6331884"},{"issue":"5","key":"11317_CR9","doi-asserted-by":"publisher","first-page":"1269","DOI":"10.1109\/18.133245","volume":"37","author":"RE Blahut","year":"1991","unstructured":"Blahut RE (1991) The gleason-prange theorem. IEEE Trans Inf Theory 37(5):1269\u20131273. https:\/\/doi.org\/10.1109\/18.133245","journal-title":"IEEE Trans Inf Theory"},{"key":"11317_CR10","first-page":"181","volume":"18","author":"A Bonisoli","year":"1984","unstructured":"Bonisoli A (1984) Every equidistant linear code is a sequence of dual hamming codes. Ars Combin 18:181\u2013186","journal-title":"Ars Combin"},{"issue":"3","key":"11317_CR11","doi-asserted-by":"publisher","first-page":"567","DOI":"10.1109\/TCCN.2019.2919300","volume":"5","author":"E Bourtsoulatze","year":"2019","unstructured":"Bourtsoulatze E, Kurka DB, G\u00fcnd\u00fcz D (2019) Deep joint source-channel coding for wireless image transmission. IEEE Trans Cogn Commun Netw 5(3):567\u2013579. https:\/\/doi.org\/10.1109\/TCCN.2019.2919300","journal-title":"IEEE Trans Cogn Commun Netw"},{"key":"11317_CR12","doi-asserted-by":"crossref","unstructured":"Brokalakis A, Papaefstathiou I (2012a) Using hardware-based forward error correction to reduce the overall energy consumption of wsns. 2012 ieee wireless communications and networking conference (wcnc) (pp. 2191\u20132196)","DOI":"10.1109\/WCNC.2012.6214156"},{"key":"11317_CR13","doi-asserted-by":"crossref","unstructured":"Brokalakis A, Papaefstathiou I (2012b) Using hardware-based forward error correction to reduce the overall energy consumption of wsns. 2012 ieee wireless communications and networking conference (wcnc) (pp. 2191\u20132196)","DOI":"10.1109\/WCNC.2012.6214156"},{"issue":"2","key":"11317_CR14","doi-asserted-by":"publisher","first-page":"1098","DOI":"10.1103\/PhysRevA.54.1098","volume":"54","author":"AR Calderbank","year":"1996","unstructured":"Calderbank AR, Shor PW (1996) Good quantum error-correcting codes exist. Phys Rev A 54(2):1098. https:\/\/doi.org\/10.1103\/PhysRevA.54.1098","journal-title":"Phys Rev A"},{"issue":"9","key":"11317_CR15","doi-asserted-by":"publisher","first-page":"5489","DOI":"10.1109\/TCOMM.2020.3002915","volume":"68","author":"S Cammerer","year":"2020","unstructured":"Cammerer S, Aoudia FA, D\u00f6rner S, Stark M, Hoydis J, Brink ST (2020) Trainable communication systems: concepts and prototype. IEEE Trans Commun 68(9):5489\u20135503. https:\/\/doi.org\/10.1109\/TCOMM.2020.3002915","journal-title":"IEEE Trans Commun"},{"key":"11317_CR16","doi-asserted-by":"crossref","unstructured":"Cammerer S, Hoydis J, Aoudia FA, Keller A (2022) Graph neural networks for channel decoding. 2022 ieee globecom workshops (gc wkshps) (p. 486-491). IEEE","DOI":"10.1109\/GCWkshps56602.2022.10008601"},{"issue":"6","key":"11317_CR17","doi-asserted-by":"publisher","first-page":"955","DOI":"10.4218\/etrij.2022-0192","volume":"44","author":"S Chan","year":"2022","unstructured":"Chan S, Jo G, Kim S, Oh D, Ku B (2022) Dynamic power and bandwidth allocation for dvb-based leo satellite systems. ETRI J 44(6):955\u2013965. https:\/\/doi.org\/10.4218\/etrij.2022-0192","journal-title":"ETRI J"},{"issue":"5","key":"11317_CR18","doi-asserted-by":"publisher","first-page":"1087","DOI":"10.1109\/LWC.2022.3157062","volume":"11","author":"S Chan","year":"2022","unstructured":"Chan S, Lee H, Kim S, Oh D (2022) Intelligent low complexity resource allocation method for integrated satellite-terrestrial systems. IEEE Wirel Commun Lett 11(5):1087\u20131091. https:\/\/doi.org\/10.1109\/LWC.2022.3157062","journal-title":"IEEE Wirel Commun Lett"},{"key":"11317_CR19","doi-asserted-by":"publisher","unstructured":"Chan SC, Fishman S, Canny J, Korattikara A, Guadarrama S (2019) Measuring the reliability of reinforcement learning algorithms. arXiv preprint arXiv:1912.05663, https:\/\/doi.org\/10.48550\/arXiv.1912.05663","DOI":"10.48550\/arXiv.1912.05663"},{"issue":"7","key":"11317_CR20","doi-asserted-by":"publisher","first-page":"eadf8437","DOI":"10.1126\/sciadv.adf8437","volume":"9","author":"Y Chen","year":"2023","unstructured":"Chen Y, Zhou T, Wu J, Qiao H, Lin X, Fang L, Dai Q (2023) Photonic unsupervised learning variational autoencoder for high-throughput and lowlatency image transmission. Sci Adv 9(7):eadf8437. https:\/\/doi.org\/10.1126\/sciadv.adf8437","journal-title":"Sci Adv"},{"key":"11317_CR21","doi-asserted-by":"crossref","unstructured":"Cogen F, Aydin E (2019) Hexagonal quadrature amplitude modulation aided spatial modulation. 2019 11th international conference on electrical and electronics engineering (eleco) (p. 730-733)","DOI":"10.23919\/ELECO47770.2019.8990645"},{"key":"11317_CR22","doi-asserted-by":"crossref","unstructured":"Cogen F, \u00d6zden BA, Ayd\u0131n E (2024) Energy-efficient and low-complexity spatial modulation system with deep neural network-based capacity-optimized antenna selection. 2024 15th national conference on electrical and electronics engineering (eleco) (pp. 1\u20135)","DOI":"10.1109\/ELECO64362.2024.10847098"},{"issue":"4","key":"11317_CR23","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1109\/MWC.001.1900491","volume":"27","author":"L Dai","year":"2020","unstructured":"Dai L, Jiao R, Adachi F, Poor HV, Hanzo L (2020) Deep learning for wireless communications: An emerging interdisciplinary paradigm. IEEE Wirel Commun 27(4):133\u2013139. https:\/\/doi.org\/10.1109\/MWC.001.1900491","journal-title":"IEEE Wirel Commun"},{"issue":"5","key":"11317_CR24","doi-asserted-by":"publisher","first-page":"879","DOI":"10.1002\/edn3.194","volume":"3","author":"JA Darling","year":"2021","unstructured":"Darling JA, Jerde CL, Sepulveda AJ (2021) What do you mean by false positive? Environmental DNA 3(5):879\u2013883. https:\/\/doi.org\/10.1002\/edn3.194","journal-title":"Environmental DNA"},{"key":"11317_CR25","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2024.111672","volume":"159","author":"CP Davey","year":"2024","unstructured":"Davey CP, Shakeel I, Deo RC, Sharma E, Salcedo-Sanz S, Soar J (2024) End-to-end learning of adaptive coded modulation schemes for resilient wireless communications. Appl Soft Comput 159:111672. https:\/\/doi.org\/10.1016\/j.asoc.2024.111672","journal-title":"Appl Soft Comput"},{"key":"11317_CR26","unstructured":"Davey MC, MacKay DJ (1998) Low density parity check codes over gf (q). 1998 information theory workshop (cat. no. 98ex131) (p. 70-71). IEEE"},{"key":"11317_CR27","unstructured":"Dayan P, Sahani M, Deback G (1999) Unsupervised learning [Journal Article]. The MIT encyclopedia of the cognitive sciences, 857- 859 https:\/\/doi.org\/https:\/\/web.math.princeton.edu\/~sswang\/developmental-diaschisis-references\/dun99b.pdf"},{"key":"11317_CR28","doi-asserted-by":"crossref","unstructured":"DelVecchio M, Flowers B, Headley WC (2020) Effects of forward error correction on communications aware evasion attacks [Conference Proceedings]. 2020 ieee 31st annual international symposium on personal, indoor and mobile radio communications (p. 1-7). IEEE","DOI":"10.1109\/PIMRC48278.2020.9217343"},{"issue":"2","key":"11317_CR29","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1109\/MWC.001.1900178","volume":"27","author":"B Deng","year":"2019","unstructured":"Deng B, Jiang C, Yao H, Guo S, Zhao S (2019) The next generation heterogeneous satellite communication networks: Integration of resource management and deep reinforcement learning. IEEE Wirel Commun 27(2):105\u2013111. https:\/\/doi.org\/10.1109\/MWC.001.1900178","journal-title":"IEEE Wirel Commun"},{"key":"11317_CR30","doi-asserted-by":"crossref","unstructured":"Doan N, Hashemi SA, Gross WJ (2020) Decoding polar codes with reinforcement learning. Globecom 2020-2020 ieee global communications conference (p. 1-6). IEEE","DOI":"10.1109\/GLOBECOM42002.2020.9348007"},{"key":"11317_CR31","doi-asserted-by":"crossref","unstructured":"Ejaz MZ, Khurshid K, Abbas Z, Aizaz MA, Nawaz A (2018) A novel image encoding and communication technique of b\/w images for iot, robotics and drones using (15, 11) reed solomon scheme. 2018 advances in science and engineering technology international conferences (aset) (p. 1-6). IEEE","DOI":"10.1109\/ICASET.2018.8376846"},{"key":"11317_CR32","unstructured":"Elbert BR (2008) Introduction to satellite communication. Artech house"},{"issue":"7","key":"11317_CR33","doi-asserted-by":"publisher","first-page":"4521","DOI":"10.1109\/TCOMM.2019.2908870","volume":"67","author":"A Elkelesh","year":"2019","unstructured":"Elkelesh A, Ebada M, Cammerer S, Ten Brink S (2019) Decoder-tailored polar code design using the genetic algorithm. IEEE Trans Commun 67(7):4521\u20134534. https:\/\/doi.org\/10.1109\/TCOMM.2019.2908870","journal-title":"IEEE Trans Commun"},{"key":"11317_CR34","doi-asserted-by":"crossref","unstructured":"Ez-Zazi I, Arioua M, El Oualkadi A, El Assari Y (2015) Performance analysis of efficient coding schemes for wireless sensor networks. 2015 third international workshop on rfid and adaptive wireless sensor networks (rawsn) (p. 42-47). IEEE","DOI":"10.1109\/RAWSN.2015.7173277"},{"key":"11317_CR35","doi-asserted-by":"publisher","first-page":"3017","DOI":"10.1007\/s11277-016-3763-1","volume":"94","author":"I Ez-Zazi","year":"2017","unstructured":"Ez-Zazi I, Arioua M, El Oualkadi A, Lorenz P (2017) A hybrid adaptive coding and decoding scheme for multi-hop wireless sensor networks. Wireless Pers Commun 94:3017\u20133033. https:\/\/doi.org\/10.1007\/s11277-016-3763-1","journal-title":"Wireless Pers Commun"},{"issue":"5","key":"11317_CR36","doi-asserted-by":"publisher","first-page":"1030","DOI":"10.1109\/JSAC.2018.2832820","volume":"36","author":"P Ferreira","year":"2018","unstructured":"Ferreira P, Paffenroth R, Wyglinski AM, Hackett TM, Bil\u00e9n SG, Reinhart RC, Mortensen DJ (2018) Multiobjective reinforcement learning for cognitive satellite communications using deep neural network ensembles. IEEE J Sel Areas Commun 36(5):1030\u20131041","journal-title":"IEEE J Sel Areas Commun"},{"key":"11317_CR37","doi-asserted-by":"publisher","first-page":"385","DOI":"10.1007\/s13042-020-01178-4","volume":"12","author":"H Fourati","year":"2021","unstructured":"Fourati H, Maaloul R, Chaari L (2021) A survey of 5g network systems: challenges and machine learning approaches. Int J Mach Learn Cybern 12:385\u2013431. https:\/\/doi.org\/10.1007\/s13042-020-01178-4","journal-title":"Int J Mach Learn Cybern"},{"issue":"1","key":"11317_CR38","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1109\/TIT.1962.1057683","volume":"8","author":"R Gallager","year":"1962","unstructured":"Gallager R (1962) Low-density parity-check codes. IRE Trans Inform Theory 8(1):21\u201328. https:\/\/doi.org\/10.1109\/TIT.1962.1057683","journal-title":"IRE Trans Inform Theory"},{"key":"11317_CR39","unstructured":"Guiotto A, Martelli A, Paccagnini C (2003) Smart-fdir: Use of artificial intelligence in the implementation of a satellite fdir. Dasia 2003-data systems in aerospace (Vol. 532)"},{"issue":"9","key":"11317_CR40","doi-asserted-by":"publisher","first-page":"4157","DOI":"10.1109\/TMTT.2021.3075678","volume":"69","author":"G G\u00fcltepe","year":"2021","unstructured":"G\u00fcltepe G, Kanar T, Zihir S, Rebeiz GM (2021) A 1024-element ku-band satcom phased-array transmitter with 45-dbw single-polarization eirp. IEEE Trans Microw Theory Tech 69(9):4157\u20134168. https:\/\/doi.org\/10.1109\/TMTT.2021.3075678","journal-title":"IEEE Trans Microw Theory Tech"},{"key":"11317_CR41","doi-asserted-by":"crossref","unstructured":"Ha T, Oh J, Lee D, Lee J, Jeon Y, Cho S (2018) Reinforcement learningbased resource allocation for streaming in a multi-modal deep space network. 2021 international conference on information and communication technology convergence (ictc) (p. 201-206). IEEE","DOI":"10.1109\/ICTC52510.2021.9621165"},{"key":"11317_CR42","unstructured":"Happonen A (2012) Low power design for wireless sensor networks. Citeseer"},{"issue":"5","key":"11317_CR43","doi-asserted-by":"publisher","first-page":"96","DOI":"10.1109\/MWC.001.1900394","volume":"27","author":"NU Hassan","year":"2020","unstructured":"Hassan NU, Huang C, Yuen C, Ahmad A, Zhang Y (2020) Dense small satellite networks for modern terrestrial communication systems: Benefits, infrastructure, and technologies. IEEE Wirel Commun 27(5):96\u2013103. https:\/\/doi.org\/10.1109\/MWC.001.1900394","journal-title":"IEEE Wirel Commun"},{"key":"11317_CR44","doi-asserted-by":"publisher","DOI":"10.1002\/9781119536604","volume-title":"Cochrane handbook for systematic reviews of interventions","author":"JP Higgins","year":"2019","unstructured":"Higgins JP, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA (2019) Cochrane handbook for systematic reviews of interventions. John Wiley, Hoboken"},{"key":"11317_CR45","doi-asserted-by":"crossref","unstructured":"Hill R, Lizak P (1995) Extensions of linear codes. Proceedings of 1995 ieee international symposium on information theory (p. 345)","DOI":"10.1109\/ISIT.1995.550332"},{"key":"11317_CR46","unstructured":"Hocquenghem A (1959) Codes correcteurs d\u2019erreurs Chiffers, 2:147\u2013156"},{"key":"11317_CR47","unstructured":"Hong L, Ho K (2003) Classification of bpsk and qpsk signals with unknown signal level using the bayes technique. 2003 ieee international symposium on circuits and systems (iscas) (Vol. 4, pp. IV\u2013IV)"},{"key":"11317_CR48","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/WCN\/2006\/74812","volume":"2006","author":"SL Howard","year":"2006","unstructured":"Howard SL, Schlegel C, Iniewski K, Iniewski K (2006) Error control coding in low-power wireless sensor networks: When is ecc energy-efficient? EURASIP J Wirel Commun Netw 2006:1\u201314. https:\/\/doi.org\/10.1155\/WCN\/2006\/74812","journal-title":"EURASIP J Wirel Commun Netw"},{"issue":"1","key":"11317_CR49","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1109\/tcomm.2019.2951403","volume":"68","author":"L Huang","year":"2020","unstructured":"Huang L, Zhang H, Li R, Ge Y, Wang J (2020) Ai coding: learning to construct error correction codes. IEEE Trans Commun 68(1):26\u201339. https:\/\/doi.org\/10.1109\/tcomm.2019.2951403","journal-title":"IEEE Trans Commun"},{"key":"11317_CR50","doi-asserted-by":"crossref","unstructured":"Islam MR (2010) Selection of error control\/correction codes in wireless sensor network. International conference on electrical & computer engineering (icece 2010) (p. 674-677). IEEE","DOI":"10.1109\/ICELCE.2010.5700783"},{"key":"11317_CR51","doi-asserted-by":"crossref","unstructured":"Islam MR, Kim J (2009) Capacity and ber analysis for nakagami-n channel in ldpc coded wireless sensor network. 2008 international conference on intelligent sensors, sensor networks and information processing (p. 167-172). IEEE","DOI":"10.1109\/ISSNIP.2008.4761981"},{"key":"11317_CR52","doi-asserted-by":"publisher","first-page":"325","DOI":"10.1007\/s12243-009-0151-9","volume":"65","author":"MR Islam","year":"2010","unstructured":"Islam MR, Kim J (2010) On the cooperative mimo communication for energy-efficient cluster-to-cluster transmission at wireless sensor network. Annals Telecommun Annales des T\u00e9l\u00e9commun 65:325\u2013340. https:\/\/doi.org\/10.1007\/s12243-009-0151-9","journal-title":"Annals Telecommun Annales des T\u00e9l\u00e9commun"},{"issue":"6","key":"11317_CR53","doi-asserted-by":"publisher","first-page":"528","DOI":"10.1109\/tai.2021.3108129","volume":"2","author":"A Jagannath","year":"2021","unstructured":"Jagannath A, Jagannath J, Melodia T (2021) Redefining wireless communication for 6g: Signal processing meets deep learning with deep unfolding. IEEE Trans Artif Intell 2(6):528\u2013536. https:\/\/doi.org\/10.1109\/tai.2021.3108129","journal-title":"IEEE Trans Artif Intell"},{"issue":"2","key":"11317_CR54","doi-asserted-by":"publisher","first-page":"419","DOI":"10.1109\/TMC.2017.2709309","volume":"17","author":"S Jang","year":"2017","unstructured":"Jang S, Shin KG, Bahk S (2017) Post-cca and reinforcement learning based bandwidth adaptation in 802.11 ac networks. IEEE Trans Mob Comput 17(2):419\u2013432. https:\/\/doi.org\/10.1109\/TMC.2017.2709309","journal-title":"IEEE Trans Mob Comput"},{"key":"11317_CR55","doi-asserted-by":"crossref","unstructured":"Jiang Y, Kannan S, Kim H, Oh S, Asnani H, Viswanath P (2019) Deepturbo: Deep turbo decoder. 2019 ieee 20th international workshop on signal processing advances in wireless communications (spawc) (p. 1-5). IEEE","DOI":"10.1109\/SPAWC.2019.8815400"},{"key":"11317_CR56","doi-asserted-by":"crossref","unstructured":"Jiang Y, Kim H, Asnani H, Kannan S, Oh S, Viswanath P (2020a) Joint channel coding and modulation via deep learning. 2020 ieee 21st international workshop on signal processing advances in wireless communications (spawc) (p. 1-5). IEEE","DOI":"10.1109\/SPAWC48557.2020.9153885"},{"issue":"1","key":"11317_CR57","doi-asserted-by":"publisher","first-page":"207","DOI":"10.1109\/JSAIT.2020.2988577","volume":"1","author":"Y Jiang","year":"2020","unstructured":"Jiang Y, Kim H, Asnani H, Kannan S, Oh S, Viswanath P (2020) Learn codes: inventing low-latency codes via recurrent neural networks. IEEE J Selected Areas Inform Theory 1(1):207\u2013216. https:\/\/doi.org\/10.1109\/JSAIT.2020.2988577","journal-title":"IEEE J Selected Areas Inform Theory"},{"key":"11317_CR58","doi-asserted-by":"crossref","unstructured":"Jo G, Chan S, Kim S, Oh D (2023) Analysis on the neural network-aided satellite resource allocation schemes. 2023 international conference on electronics, information, and communication (iceic) (p. 1-4). IEEE","DOI":"10.1109\/ICEIC57457.2023.10049977"},{"key":"11317_CR59","doi-asserted-by":"crossref","unstructured":"Kashani ZH, Shiva M (2006) Bch coding and multi-hop communication in wireless sensor networks. 2006 ifip international conference on wireless and optical communications networks (p. 5 pp.-5). IEEE","DOI":"10.1109\/WOCN.2006.1666619"},{"key":"11317_CR60","unstructured":"Kathy Haan RW (2023) 24 top ai statistics and trends in 2023 [Online Database]"},{"key":"11317_CR61","doi-asserted-by":"crossref","unstructured":"Klaimi R, Weithoffer S, Nour CA (2022) Improved non-uniform constellations for non-binary codes through deep reinforcement learning. 2022 ieee 23rd international workshop on signal processing advances in wireless communication (spawc) (p. 1-5). IEEE","DOI":"10.1109\/SPAWC51304.2022.9834022"},{"issue":"11","key":"11317_CR62","first-page":"3059","volume":"38","author":"T Koike-Akino","year":"2020","unstructured":"Koike-Akino T, Wang Y, Millar DS, Kojima K, Parsons K (2020) Neural turbo equalization: deep learning for fiber-optic nonlinearity compensation. J Lightwave Technol 38(11):3059\u20133066","journal-title":"J Lightwave Technol"},{"key":"11317_CR63","doi-asserted-by":"crossref","unstructured":"Kothari V, Liberis E, Lane ND (2020) The final frontier: Deep learning in space. Proceedings of the 21st international workshop on mobile computing systems and applications (p. 45-49)","DOI":"10.1145\/3376897.3377864"},{"issue":"1","key":"11317_CR64","doi-asserted-by":"publisher","first-page":"1","DOI":"10.32604\/iasc.2022.022536","volume":"33","author":"S Lakshmi Durga","year":"2022","unstructured":"Lakshmi Durga S, Rajeshwari C, Hamed Allehaibi K, Gupta N, Nammas Albaqami N, Bharti I, Hoirul Basori A (2022) Deep reinforcement learning-based long short-term memory for satellite iot channel allocation. Intel Autom Soft Comput 33(1):1\u201319. https:\/\/doi.org\/10.32604\/iasc.2022.022536","journal-title":"Intel Autom Soft Comput"},{"key":"11317_CR65","doi-asserted-by":"crossref","unstructured":"Leite JP, de Carvalho PHP, Vieira RD (2012) A flexible framework based on reinforcement learning for adaptive modulation and coding in ofdm wireless systems. 2012 ieee wireless communications and networking conference (wcnc) (p. 809-814). IEEE","DOI":"10.1109\/WCNC.2012.6214482"},{"key":"11317_CR66","doi-asserted-by":"crossref","unstructured":"Li N, Su T, Deng Z-l, Hu L (2018) Research on the channel information forecast and adaptive coding and modulation with reinforcement learning","DOI":"10.12783\/dtcse\/wicom2018\/26284"},{"key":"11317_CR67","doi-asserted-by":"publisher","DOI":"10.1109\/TCCN.2023.3234268","author":"S Li","year":"2023","unstructured":"Li S, Zhang Y, Huang Z, Zhou J, Zhao Y (2023) Modeling and classifying error-correcting codes with soft decision-based hmms for intelligent wireless communication. IEEE Trans Cogn Commun Netw. https:\/\/doi.org\/10.1109\/TCCN.2023.3234268","journal-title":"IEEE Trans Cogn Commun Netw"},{"issue":"1","key":"11317_CR68","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1016\/j.icte.2022.01.018","volume":"8","author":"SH Lim","year":"2022","unstructured":"Lim SH, Han J, Noh W, Song Y, Jeon S-W (2022) Hybrid neural coded modulation: design and training methods. ICT Exp 8(1):25\u201330. https:\/\/doi.org\/10.1016\/j.icte.2022.01.018","journal-title":"ICT Exp"},{"key":"11317_CR69","doi-asserted-by":"crossref","unstructured":"Liu P, Shi Y, Jiao Y, Wu T (2020) A new method for small satellite tt & c using internet of things communication technology. 2020 ieee 9th joint international information technology and artificial intelligence conference (itaic) (Vol. 9, p. 1468-1473). IEEE","DOI":"10.1109\/ITAIC49862.2020.9338800"},{"issue":"2","key":"11317_CR70","doi-asserted-by":"publisher","first-page":"817","DOI":"10.1109\/TCCN.2019.2946358","volume":"6","author":"X Liu","year":"2019","unstructured":"Liu X, Wu S, Wang Y, Zhang N, Jiao J, Zhang Q (2019) Exploiting error-correction-crc for polar scl decoding: A deep learning-based approach. IEEE Trans Cogn Commun Netw 6(2):817\u2013828. https:\/\/doi.org\/10.1109\/TCCN.2019.2946358","journal-title":"IEEE Trans Cogn Commun Netw"},{"issue":"3","key":"11317_CR71","doi-asserted-by":"publisher","first-page":"441","DOI":"10.3390\/app8030441","volume":"8","author":"Y Liu","year":"2018","unstructured":"Liu Y, Shen Y, Li L, Wang H (2018) Fpga implementation of a bpsk 1d-cnn demodulator. Appl Sci 8(3):441. https:\/\/doi.org\/10.3390\/app8030441","journal-title":"Appl Sci"},{"issue":"22","key":"11317_CR72","doi-asserted-by":"publisher","first-page":"8678","DOI":"10.3390\/s22228678","volume":"22","author":"Z Liu","year":"2022","unstructured":"Liu Z, Li W, Feng J, Zhang J (2022) Research on satellite network traffic prediction based on improved gru neural network. Sensors 22(22):8678. https:\/\/doi.org\/10.3390\/s22228678","journal-title":"Sensors"},{"issue":"1","key":"11317_CR73","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s11227-024-06795-2","volume":"81","author":"D Lloria","year":"2025","unstructured":"Lloria D, Roger S, Leon G, Badia JM, Botella-Mascarell C, Belloch JA (2025) Optimizing millimeter wave mimo channel estimation through gpu-based edge artificial intelligence. J Supercomput 81(1):1. https:\/\/doi.org\/10.1007\/s11227-024-06795-2","journal-title":"J Supercomput"},{"key":"11317_CR74","unstructured":"Lu Z, Pu H, Wang F, Hu Z, Wang L (2017) The expressive power of neural networks: A view from the width. Advances in neural information processing systems, 30"},{"issue":"2","key":"11317_CR75","doi-asserted-by":"publisher","first-page":"104","DOI":"10.1109\/TCOM.1986.1096498","volume":"34","author":"H Ma","year":"1986","unstructured":"Ma H, Wolf J (1986) On tail biting convolutional codes. IEEE Trans Commun 34(2):104\u2013111. https:\/\/doi.org\/10.1109\/TCOM.1986.1096498","journal-title":"IEEE Trans Commun"},{"key":"11317_CR76","unstructured":"Makkuva AV, Liu X, Jamali MV, Mahdavifar H, Oh S, Viswanath P (2021) Ko codes: inventing nonlinear encoding and decoding for reliable wireless communication via deep-learning. International conference on machine learning (p. 7368-7378). PMLR"},{"key":"11317_CR77","doi-asserted-by":"publisher","first-page":"35643","DOI":"10.1109\/ACCESS.2022.3161618","volume":"10","author":"M Marey","year":"2022","unstructured":"Marey M, Mostafa H (2022) Power of error correcting codes for sfbc-ofdm classification over unknown channels. IEEE Access 10:35643\u201335652. https:\/\/doi.org\/10.1109\/ACCESS.2022.3161618","journal-title":"IEEE Access"},{"issue":"1","key":"11317_CR78","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1002\/jrsm.1277","volume":"9","author":"E Mayo-Wilson","year":"2018","unstructured":"Mayo-Wilson E, Li T, Fusco N, Dickersin K, Investigators M (2018) Practical guidance for using multiple data sources in systematic reviews and meta-analyses (with examples from the muds study). Res Synthesis Methods 9(1):2\u201312. https:\/\/doi.org\/10.1002\/jrsm.1277","journal-title":"Res Synthesis Methods"},{"issue":"11","key":"11317_CR79","doi-asserted-by":"publisher","first-page":"3884","DOI":"10.3390\/s21113884","volume":"21","author":"F Mei","year":"2021","unstructured":"Mei F, Chen H, Lei Y (2021) Blind recognition of forward error correction codes based on recurrent neural network. Sensors 21(11):3884. https:\/\/doi.org\/10.3390\/s21113884","journal-title":"Sensors"},{"key":"11317_CR80","doi-asserted-by":"publisher","unstructured":"Michelucci U (2022) An introduction to autoencoders. arXiv preprint arXiv:2201.03898, https:\/\/doi.org\/10.48550\/arXiv.2201.03898","DOI":"10.48550\/arXiv.2201.03898"},{"issue":"6","key":"11317_CR81","doi-asserted-by":"publisher","first-page":"4491","DOI":"10.1007\/s11276-020-02355-7","volume":"26","author":"MA Morsy","year":"2020","unstructured":"Morsy MA, Alsayyari AS (2020) Performance analysis of coherent bpsk-ocdma wireless communication system. Wireless Netw 26(6):4491\u20134505. https:\/\/doi.org\/10.1007\/s11276-020-02355-7","journal-title":"Wireless Netw"},{"key":"11317_CR82","doi-asserted-by":"crossref","unstructured":"Mota MP, Araujo DC, Neto FHC, de Almeida AL, Cavalcanti FR (2019) Adaptive modulation and coding based on reinforcement learning for 5g networks. 2019 ieee globecom workshops (gc wkshps) (p. 1-6). IEEE","DOI":"10.1109\/GCWkshps45667.2019.9024384"},{"key":"11317_CR83","doi-asserted-by":"crossref","unstructured":"Mulgund A, Shekhar R, Devroye N, Tur\u00e1n G, \u017defran M (2022) Evaluating interpretations of deep-learned error-correcting codes. 2022 58th annual allerton conference on communication, control, and computing (allerton) (p. 1-8). IEEE","DOI":"10.1109\/Allerton49937.2022.9929417"},{"key":"11317_CR84","doi-asserted-by":"publisher","first-page":"6","DOI":"10.1109\/IREPGELC.1954.6499441","volume":"3","author":"DE Muller","year":"1954","unstructured":"Muller DE (1954) Application of boolean algebra to switching circuit design and to error detection. Trans IRE Professional Group on Electronic Comput 3:6\u201312. https:\/\/doi.org\/10.1109\/IREPGELC.1954.6499441","journal-title":"Trans IRE Professional Group on Electronic Comput"},{"key":"11317_CR85","doi-asserted-by":"crossref","unstructured":"Murphy CD (2000) High-order optimum hexagonal constellations. 11th ieee international symposium on personal indoor and mobile radio communications. pimrc 2000. proceedings (cat. no.00th8525) (Vol. 1, p. 143-146 vol.1)","DOI":"10.1109\/PIMRC.2000.881407"},{"key":"11317_CR86","unstructured":"NASA (2018) Nasa. state of the art small spacecraft technology [Online Database]. National Aeronautics and Space Administration"},{"key":"11317_CR87","doi-asserted-by":"publisher","first-page":"46317","DOI":"10.1109\/ACCESS.2019.2909490","volume":"7","author":"SJ Nawaz","year":"2019","unstructured":"Nawaz SJ, Sharma SK, Wyne S, Patwary MN, Asaduzzaman M (2019) Quantum machine learning for 6g communication networks: state-of-the-art and vision for the future. IEEE Access 7:46317\u201346350. https:\/\/doi.org\/10.1109\/ACCESS.2019.2909490","journal-title":"IEEE Access"},{"issue":"2","key":"11317_CR88","doi-asserted-by":"publisher","first-page":"101","DOI":"10.3390\/aerospace10020101","volume":"10","author":"F Ortiz","year":"2023","unstructured":"Ortiz F, Monzon Baeza V, Garces-Socarras LM, V\u00e1squez-Peralvo JA, Gonzalez JL, Fontanesi G, Lagunas E, Querol J, Chatzinotas S (2023) Onboard processing in satellite communications using ai accelerators [Journal Article]. Aerospace 10(2):101. https:\/\/doi.org\/10.3390\/aerospace10020101","journal-title":"Aerospace"},{"key":"11317_CR89","doi-asserted-by":"crossref","unstructured":"O\u2019Shea TJ, Roy T, West N, Hilburn BC (2018) Physical layer communications system design over-the-air using adversarial networks. 2018 26th european signal processing conference (eusipco) (p. 529-532)","DOI":"10.23919\/EUSIPCO.2018.8553233"},{"issue":"7","key":"11317_CR90","doi-asserted-by":"publisher","DOI":"10.1002\/ett.4795","volume":"34","author":"BA Ozden","year":"2023","unstructured":"Ozden BA, Cogen F, Aydin E (2023) Mirror activation pattern selection for energy efficient hexagonal qam aided media-based modulation. Trans Emerg Telecommun Tech 34(7):e4795","journal-title":"Trans Emerg Telecommun Tech"},{"key":"11317_CR91","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijsu.2021.105906","volume":"88","author":"MJ Page","year":"2021","unstructured":"Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, Shamseer L, Tetzlaff JM, Akl EA, Brennan SE (2021) The prisma 2020 statement: an updated guideline for reporting systematic reviews. Int J Surg 88:105906. https:\/\/doi.org\/10.1016\/j.ijsu.2021.105906","journal-title":"Int J Surg"},{"key":"11317_CR92","doi-asserted-by":"crossref","unstructured":"Paluszek M, Thomas S (2020) Practical matlab deep learning. A Project-Based Approach, Michael Paluszek and Stephanie Thomas","DOI":"10.1007\/978-1-4842-5124-9"},{"key":"11317_CR93","doi-asserted-by":"crossref","unstructured":"Qaisar SB, Radha H (2007) Optimal progressive error recovery for wireless sensor networks using irregular ldpc codes. 2007 41st annual conference on information sciences and systems (p. 232-237). IEEE","DOI":"10.1109\/CISS.2007.4298305"},{"key":"11317_CR94","doi-asserted-by":"crossref","unstructured":"Qassim Y, Magana ME (2014) Error-tolerant non-binary error correction code for low power wireless sensor networks. The international conference on information networking 2014 (icoin2014) (p. 23-27). IEEE","DOI":"10.1109\/ICOIN.2014.6799477"},{"key":"11317_CR95","doi-asserted-by":"crossref","unstructured":"Rajapaksha N, Rajatheva N, Latva-aho M (2020a) Low complexity autoencoder based end-to-end learning of coded communications systems. 2020 ieee 91st vehicular technology conference (vtc2020-spring) (p. 1-7). IEEE","DOI":"10.1109\/VTC2020-Spring48590.2020.9128456"},{"key":"11317_CR96","doi-asserted-by":"crossref","unstructured":"Rajapaksha N, Rajatheva N, Latva-aho M (2020b) Low complexity autoencoder based end-to-end learning of coded communications systems. 2020 ieee 91st vehicular technology conference (vtc2020-spring) (pp. 1\u20137)","DOI":"10.1109\/VTC2020-Spring48590.2020.9128456"},{"issue":"3","key":"11317_CR97","doi-asserted-by":"publisher","first-page":"366","DOI":"10.1109\/JPROC.2014.2299397","volume":"102","author":"S Rangan","year":"2014","unstructured":"Rangan S, Rappaport TS, Erkip E (2014) Millimeter-wave cellular wireless networks: Potentials and challenges. Proc IEEE 102(3):366\u2013385. https:\/\/doi.org\/10.1109\/JPROC.2014.2299397","journal-title":"Proc IEEE"},{"issue":"2","key":"11317_CR98","doi-asserted-by":"publisher","first-page":"300","DOI":"10.1137\/0108018","volume":"8","author":"IS Reed","year":"1960","unstructured":"Reed IS, Solomon G (1960) Polynomial codes over certain finite fields. J Soc Ind Appl Math 8(2):300\u2013304. https:\/\/doi.org\/10.1137\/0108018","journal-title":"J Soc Ind Appl Math"},{"issue":"3","key":"11317_CR99","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s11082-022-04512-y","volume":"55","author":"A Refaai","year":"2023","unstructured":"Refaai A, Newagy F, Fathy Abo Sree M, Aly MH, Elhennawy H, Abaza M (2023) Uplink serial relay laser satellite communication over turbulent channel: performance analysis. Opt Quant Electron 55(3):1\u201311","journal-title":"Opt Quant Electron"},{"issue":"3","key":"11317_CR100","doi-asserted-by":"publisher","first-page":"1839","DOI":"10.1109\/COMST.2020.2990499","volume":"22","author":"N Saeed","year":"2020","unstructured":"Saeed N, Elzanaty A, Almorad H, Dahrouj H, Al-Naffouri TY, Alouini M-S (2020) Cubesat communications: recent advances and future challenges. IEEE Commun Surv Tutor 22(3):1839\u20131862. https:\/\/doi.org\/10.1109\/COMST.2020.2990499","journal-title":"IEEE Commun Surv Tutor"},{"key":"11317_CR101","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13638-021-01929-z","volume":"2021","author":"H Safi","year":"2021","unstructured":"Safi H, Akbari M, Vaezpour E, Parsaeefard S, Shubair RM (2021) Autoencoder-bank based design for adaptive channel-blind robust transmission. EURASIP J Wirel Commun Netw 2021:1\u201315. https:\/\/doi.org\/10.1186\/s13638-021-01929-z","journal-title":"EURASIP J Wirel Commun Netw"},{"key":"11317_CR102","doi-asserted-by":"crossref","unstructured":"Sartipi M, Fekri F (2004) Source and channel coding in wireless sensor networks using ldpc codes. 2004 first annual ieee communications society conference on sensor and ad hoc communications and networks, 2004. ieee secon 2004. (pp. 309\u2013316)","DOI":"10.1109\/SAHCN.2004.1381931"},{"issue":"8","key":"11317_CR103","doi-asserted-by":"publisher","first-page":"1627","DOI":"10.1021\/ac60214a047","volume":"36","author":"A Savitzky","year":"1964","unstructured":"Savitzky A, Golay MJ (1964) Smoothing and differentiation of data by simplified least squares procedures. Anal Chem 36(8):1627\u20131639. https:\/\/doi.org\/10.1021\/ac60214a047","journal-title":"Anal Chem"},{"key":"11317_CR104","doi-asserted-by":"crossref","unstructured":"Schibisch, S., Cammerer S, D\u00f6rner S, Hoydis J, ten Brink S (2018) Online label recovery for deep learning-based communication through error correcting codes. 2018 15th international symposium on wireless communication systems (iswcs) (p. 1-5). IEEE","DOI":"10.1109\/ISWCS.2018.8491189"},{"key":"11317_CR105","doi-asserted-by":"publisher","unstructured":"Schreiber U (2004) Pulse-amplitude-modulation (pam) fluorometry and saturation pulse method: an overview. Chlorophyll a Fluorescence a Signature of Photosynthesis 279\u2013319. https:\/\/doi.org\/10.1007\/978-1-4020-3218-9_11","DOI":"10.1007\/978-1-4020-3218-9_11"},{"issue":"5","key":"11317_CR106","doi-asserted-by":"publisher","first-page":"612","DOI":"10.1109\/LCOMM.2012.031912.112323","volume":"16","author":"Y Seyedi","year":"2012","unstructured":"Seyedi Y, Safavi SM (2012) On the analysis of random coverage time in mobile leo satellite communications. IEEE Commun Lett 16(5):612\u2013615. https:\/\/doi.org\/10.1109\/LCOMM.2012.031912.112323","journal-title":"IEEE Commun Lett"},{"issue":"3","key":"11317_CR107","doi-asserted-by":"publisher","first-page":"379","DOI":"10.1002\/j.1538-7305.1948.tb01338.x","volume":"27","author":"CE Shannon","year":"1948","unstructured":"Shannon CE (1948) A mathematical theory of communication. Bell Syst Tech J 27(3):379\u2013423. https:\/\/doi.org\/10.1002\/j.1538-7305.1948.tb01338.x","journal-title":"Bell Syst Tech J"},{"issue":"16","key":"11317_CR108","doi-asserted-by":"publisher","first-page":"5271","DOI":"10.3390\/s24165271","volume":"24","author":"E Sharma","year":"2024","unstructured":"Sharma E, Deo RC, Davey CP, Carter BD (2024) Artificial intelligenceempowered doppler weather profile for low-earth-orbit satellites. Sensors (Basel Switzerland) 24(16):5271","journal-title":"Sensors (Basel Switzerland)"},{"key":"11317_CR109","doi-asserted-by":"crossref","unstructured":"Sharma E, Deo RC, Davey CP, Carter BD, Salcedo-Sanz S (2024a) Poster: Cloud computing with ai-empowered trends in software-defined radios: Challenges and opportunities. 2024 ieee 25th international symposium on a world of wireless, mobile and multimedia networks (wowmom) (pp. 298\u2013300)","DOI":"10.1109\/WoWMoM60985.2024.00054"},{"key":"11317_CR110","doi-asserted-by":"crossref","unstructured":"Sharma E, Deo RC, Davey CP, Carter BD, Salcedo-Sanz S (2024b) Towards next-generation federated learning: A case study on privacy attacks in artificial intelligence systems. 2024 ieee conference on artificial intelligence (cai) (pp. 1446\u20131453)","DOI":"10.1109\/CAI59869.2024.00259"},{"key":"11317_CR111","doi-asserted-by":"crossref","unstructured":"Sharma E, Shakeel I, Deo RC, Davey CP, Salcedo-Sanz S (2023) A comparative study of artificial intelligence-based algorithms for bitwise decoding of error correction codes. 2023 22nd international symposium on communications and information technologies (iscit) (pp. 37\u201342)","DOI":"10.1109\/ISCIT57293.2023.10376079"},{"key":"11317_CR112","doi-asserted-by":"publisher","DOI":"10.1109\/JLT.2023.3236400","author":"J Shi","year":"2023","unstructured":"Shi J, Li Z, Jia J, Li Z, Shen C, Zhang J, Chi N (2023) Waveform-towaveform end-to-end learning framework in a seamless fiber-terahertz integrated communication system. J Lightwave Technol. https:\/\/doi.org\/10.1109\/JLT.2023.3236400","journal-title":"J Lightwave Technol"},{"key":"11317_CR113","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/2046-4053-3-54","volume":"3","author":"E Stovold","year":"2014","unstructured":"Stovold E, Beecher D, Foxlee R, Noel-Storr A (2014) Study flow diagrams in cochrane systematic review updates: an adapted prisma flow diagram. Syst Rev 3:1\u20135. https:\/\/doi.org\/10.1186\/2046-4053-3-54","journal-title":"Syst Rev"},{"key":"11317_CR114","doi-asserted-by":"crossref","unstructured":"Toledo RN, Akamine C, Jerji F, Silva LA (2020) M-qam demodulation based on machine learning. 2020 ieee international symposium on broadband multimedia systems and broadcasting (bmsb) (p. 1-6). IEEE","DOI":"10.1109\/BMSB49480.2020.9379442"},{"key":"11317_CR115","doi-asserted-by":"crossref","unstructured":"Tonnellier T, Hashemipour M, Doan N, Gross WJ, Balatsoukas-Stimming A (2021) Towards practical near-maximum-likelihood decoding of errorcorrecting codes: An overview. Icassp 2021-2021 ieee international conference on acoustics, speech and signal processing (icassp) (p. 8283-8287). IEEE","DOI":"10.1109\/ICASSP39728.2021.9414311"},{"key":"11317_CR116","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511807213","volume-title":"Fundamentals of wireless communication","author":"D Tse","year":"2005","unstructured":"Tse D, Viswanath P (2005) Fundamentals of wireless communication. Cambridge University Press"},{"issue":"8","key":"11317_CR117","doi-asserted-by":"publisher","first-page":"2590","DOI":"10.1109\/JSAC.2021.3087248","volume":"39","author":"T-Y Tung","year":"2021","unstructured":"Tung T-Y, Kobus S, Roig JP, G\u00fcnd\u00fcz D (2021) Effective communications: a joint learning and communication framework for multi-agent reinforcement learning over noisy channels. IEEE J Sel Areas Commun 39(8):2590\u20132603. https:\/\/doi.org\/10.1109\/JSAC.2021.3087248","journal-title":"IEEE J Sel Areas Commun"},{"issue":"11","key":"11317_CR118","doi-asserted-by":"publisher","first-page":"6822","DOI":"10.1109\/TCOMM.2020.3017020","volume":"68","author":"M Varasteh","year":"2020","unstructured":"Varasteh M, Hoydis J, Clerckx B (2020) Learning to communicate and energize: modulation, coding, and multiple access designs for wireless information-power transmission. IEEE Trans Commun 68(11):6822\u20136839. https:\/\/doi.org\/10.1109\/TCOMM.2020.3017020","journal-title":"IEEE Trans Commun"},{"issue":"2","key":"11317_CR119","doi-asserted-by":"publisher","first-page":"291","DOI":"10.1109\/49.345873","volume":"13","author":"F Vatalaro","year":"1995","unstructured":"Vatalaro F, Corazza GE, Caini C, Ferrarelli C (1995) Analysis of leo, meo, and geo global mobile satellite systems in the presence of interference and fading. IEEE J Sel Areas Commun 13(2):291\u2013300. https:\/\/doi.org\/10.1109\/49.345873","journal-title":"IEEE J Sel Areas Commun"},{"issue":"2","key":"11317_CR120","doi-asserted-by":"publisher","first-page":"291","DOI":"10.1109\/49.345873","volume":"13","author":"F Vatalaro","year":"1995","unstructured":"Vatalaro F, Corazza GE, Caini C, Ferrarelli C (1995) Analysis of leo, meo, and geo global mobile satellite systems in the presence of interference and fading. IEEE J Sel Areas Commun 13(2):291\u2013300. https:\/\/doi.org\/10.1109\/49.345873","journal-title":"IEEE J Sel Areas Commun"},{"issue":"5","key":"11317_CR121","doi-asserted-by":"publisher","first-page":"751","DOI":"10.1109\/TCOM.1971.1090700","volume":"19","author":"A Viterbi","year":"1971","unstructured":"Viterbi A (1971) Convolutional codes and their performance in communication systems. IEEE Trans Commun Technol 19(5):751\u2013772. https:\/\/doi.org\/10.1109\/TCOM.1971.1090700","journal-title":"IEEE Trans Commun Technol"},{"key":"11317_CR122","doi-asserted-by":"publisher","first-page":"104844","DOI":"10.1109\/ACCESS.2022.3201354","volume":"10","author":"J Wang","year":"2022","unstructured":"Wang J, Huang H, Liu J, Li J (2022) Joint demodulation and error correcting codes recognition using convolutional neural network. IEEE Access 10:104844\u2013104851. https:\/\/doi.org\/10.1109\/ACCESS.2022.3201354","journal-title":"IEEE Access"},{"key":"11317_CR123","doi-asserted-by":"publisher","DOI":"10.1016\/j.dsp.2020.102668","author":"J Wang","year":"2020","unstructured":"Wang J, Li J, Huang H, Wang H (2020) Fine-grained recognition of error correcting codes based on 1-d convolutional neural network. Digital Signal Proc. https:\/\/doi.org\/10.1016\/j.dsp.2020.102668","journal-title":"Digital Signal Proc"},{"issue":"17","key":"11317_CR124","doi-asserted-by":"publisher","first-page":"2717","DOI":"10.3390\/electronics11172717","volume":"11","author":"M Wang","year":"2022","unstructured":"Wang M, Li Y, Liu R, Wu H, Hu Y, Lau FC (2022) Decoding quadratic residue codes using deep neural networks. Electronics 11(17):2717. https:\/\/doi.org\/10.3390\/electronics11172717","journal-title":"Electronics"},{"key":"11317_CR125","doi-asserted-by":"crossref","unstructured":"Wong LJ, Altland E, Detwiler J, Fermin P, Kuzin JM, Moeliono N, Abdalla AS, Headley WC, Michaels AJ (2020) Resilience improvements for space-based radio frequency machine learning. 2020 international symposium on networks, computers and communications (isncc) (p. 1-5). IEEE","DOI":"10.1109\/ISNCC49221.2020.9297212"},{"key":"11317_CR126","doi-asserted-by":"crossref","unstructured":"Wu G-J, Chau P (1996) Artificial intelligent adaptive control for ds-cdma with open-loop power control operating over a low earth orbiting satellite line. Proceedings of milcom\u201996 ieee military communications conference (Vol. 1, p. 1-5). IEEE","DOI":"10.1109\/MILCOM.1996.568573"},{"key":"11317_CR127","doi-asserted-by":"publisher","first-page":"50179","DOI":"10.1109\/access.2018.2869374","volume":"6","author":"X Wu","year":"2018","unstructured":"Wu X, Jiang M, Zhao C (2018) Decoding optimization for 5g ldpc codes by machine learning. IEEE Access 6:50179\u201350186. https:\/\/doi.org\/10.1109\/access.2018.2869374","journal-title":"IEEE Access"},{"key":"11317_CR128","doi-asserted-by":"publisher","DOI":"10.1109\/MWC.011.2200310","author":"Z Xiao","year":"2022","unstructured":"Xiao Z, Yang J, Mao T, Xu C, Zhang R, Han Z, Xia X-G (2022) Leo satellite access network (leo-san) towards 6g: Challenges and approaches. IEEE Wirel Commun. https:\/\/doi.org\/10.1109\/MWC.011.2200310","journal-title":"IEEE Wirel Commun"},{"issue":"3","key":"11317_CR129","doi-asserted-by":"publisher","first-page":"173","DOI":"10.1109\/JCN.2020.100015","volume":"22","author":"HB Yilmaz","year":"2020","unstructured":"Yilmaz HB, Chae C-B, Deng Y, O\u2019Shea T, Dai L, Lee N, Hoydis J (2020) Special issue on advances and applications of artificial intelligence and machine learning for wireless communications. J Commun Netw 22(3):173\u2013176. https:\/\/doi.org\/10.1109\/JCN.2020.100015","journal-title":"J Commun Netw"},{"key":"11317_CR130","doi-asserted-by":"crossref","unstructured":"Yitbarek YH, Yu K, \u00c5kerberg J, Gidlund M, Bj\u00f6rkman M (2014) Implementation and evaluation of error control schemes in industrial wireless sensor networks. 2014 ieee international conference on industrial technology (p. 730- 735)","DOI":"10.1109\/ICIT.2014.6895022"},{"key":"11317_CR131","doi-asserted-by":"publisher","DOI":"10.23919\/JCN.2022.000055","author":"Y Yu","year":"2023","unstructured":"Yu Y, Ying J, Wang P, Guo L (2023) A data-driven deep learning network for massive mimo detection with high-order qam. J Commun Netw. https:\/\/doi.org\/10.23919\/JCN.2022.000055","journal-title":"J Commun Netw"},{"issue":"9","key":"11317_CR132","doi-asserted-by":"publisher","first-page":"1297","DOI":"10.3390\/electronics11091297","volume":"11","author":"S Zhang","year":"2022","unstructured":"Zhang S, Yu G, Yu S, Zhang Y, Zhang Y (2022) Weather-conscious adaptive modulation and coding scheme for satellite-related ubiquitous networking and computing. Electronics 11(9):1297. https:\/\/doi.org\/10.3390\/electronics11091297","journal-title":"Electronics"},{"key":"11317_CR133","doi-asserted-by":"publisher","first-page":"222109","DOI":"10.1109\/ACCESS.2020.3044321","volume":"8","author":"Y Zhang","year":"2020","unstructured":"Zhang Y, Wang Z, Huang Y, Ren J, Yin Y, Liu Y, Pedersen GF, Shen M (2020) Deep neural network-based receiver for next-generation leo satellite communications. IEEE Access 8:222109\u2013222116. https:\/\/doi.org\/10.1109\/ACCESS.2020.3044321","journal-title":"IEEE Access"},{"issue":"7","key":"11317_CR134","doi-asserted-by":"publisher","first-page":"6141","DOI":"10.1109\/TIE.2020.2994873","volume":"68","author":"Y Zhang","year":"2020","unstructured":"Zhang Y, Wang Z, Huang Y, Wei W, Pedersen GF, Shen M (2020) A digital signal recovery technique using dnns for leo satellite communication systems. IEEE Trans Industr Electron 68(7):6141\u20136151. https:\/\/doi.org\/10.1109\/TIE.2020.2994873","journal-title":"IEEE Trans Industr Electron"},{"key":"11317_CR135","doi-asserted-by":"publisher","first-page":"62197","DOI":"10.1109\/ACCESS.2020.2983437","volume":"8","author":"B Zhao","year":"2020","unstructured":"Zhao B, Liu J, Wei Z, You I (2020) A deep reinforcement learning based approach for energy-efficient channel allocation in satellite internet of things. IEEE Access 8:62197\u201362206. https:\/\/doi.org\/10.1109\/ACCESS.2020.2983437","journal-title":"IEEE Access"},{"key":"11317_CR136","unstructured":"Zhu XJ (2005) Semi-supervised learning literature survey. https:\/\/doi.org\/http:\/\/digital.library.wisc.edu\/1793\/60444"}],"container-title":["Artificial Intelligence Review"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10462-025-11317-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10462-025-11317-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10462-025-11317-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,12]],"date-time":"2025-09-12T18:10:29Z","timestamp":1757700629000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10462-025-11317-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,21]]},"references-count":136,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2025,10]]}},"alternative-id":["11317"],"URL":"https:\/\/doi.org\/10.1007\/s10462-025-11317-4","relation":{},"ISSN":["1573-7462"],"issn-type":[{"value":"1573-7462","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7,21]]},"assertion":[{"value":"2 July 2025","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 July 2025","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no known Conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"321"}}