{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:10:12Z","timestamp":1760235012321,"version":"build-2065373602"},"reference-count":50,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2021,7,7]],"date-time":"2021-07-07T00:00:00Z","timestamp":1625616000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Natural Sciences and Engineering Research Council of Canada (NSERC).","award":["RGPIN-2016-03647"],"award-info":[{"award-number":["RGPIN-2016-03647"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Network"],"abstract":"<jats:p>Most modern communication systems, such as those intended for deployment in IoT applications or 5G and beyond networks, utilize multiple domains for transmission and reception at the physical layer. Depending on the application, these domains can include space, time, frequency, users, code sequences, and transmission media, to name a few. As such, the design criteria of future communication systems must be cognizant of the opportunities and the challenges that exist in exploiting the multi-domain nature of the signals and systems involved for information transmission. Focussing on the Physical Layer, this paper presents a novel mathematical framework using tensors, to represent, design, and analyze multi-domain systems. Various domains can be integrated into the transceiver design scheme using tensors. Tools from multi-linear algebra can be used to develop simultaneous signal processing techniques across all the domains. In particular, we present tensor partial response signaling (TPRS) which allows the introduction of controlled interference within elements of a domain and also across domains. We develop the TPRS system using the tensor contracted convolution to generate a multi-domain signal with desired spectral and cross-spectral properties across domains. In addition, by studying the information theoretic properties of the multi-domain tensor channel, we present the trade-off between different domains that can be harnessed using this framework. Numerical examples for capacity and mean square error are presented to highlight the domain trade-off revealed by the tensor formulation. Furthermore, an application of the tensor framework to MIMO Generalized Frequency Division Multiplexing (GFDM) is also presented.<\/jats:p>","DOI":"10.3390\/network1020005","type":"journal-article","created":{"date-parts":[[2021,7,8]],"date-time":"2021-07-08T04:32:49Z","timestamp":1625718769000},"page":"50-74","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Multi-Domain Communication Systems and Networks: A Tensor-Based Approach"],"prefix":"10.3390","volume":"1","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7556-2946","authenticated-orcid":false,"given":"Divyanshu","family":"Pandey","sequence":"first","affiliation":[{"name":"Department of Electrical and Computer Engineering, McGill University, Montreal, QC H3A 0E9, Canada"}]},{"given":"Adithya","family":"Venugopal","sequence":"additional","affiliation":[{"name":"Fortinet Inc., Burnaby, BC V5C 2G4, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1299-3073","authenticated-orcid":false,"given":"Harry","family":"Leib","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, McGill University, Montreal, QC H3A 0E9, Canada"}]}],"member":"1968","published-online":{"date-parts":[[2021,7,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Chataut, R., and Akl, R. 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