Tensor Decompositions for Integrated Sensing and Communications

Integrated sensing and communications (ISAC) is one of the potential key technologies of the sixth-generation (6G) that could enhance the information interaction ability among network nodes. Since tensor technology can excellently store, process, and analyze a large amount of multi-dimensional data generated by modern wireless systems, it has aroused great research interest in both academia and industry. In this article, we present a general review on tensor decompositions for ISAC. We first describe the commonly used tensors and their extended models. Next, we introduce the recent development and appealing advantages of tensor decompositions for communication, sensing, and ISAC, respectively. Moreover, the superiority of tensor decompositions to facilitate ISAC is demonstrated through a case study, and some promising research directions of tensor decompositions in ISAC are discussed to promote future works. We envision that the tensor technology will play an indispensable role in ISAC systems by virtue of its excellence in handling abundant multi-dimensional data.