Massive MIMO for Internet of Things (IoT) connectivity

Abstract

Massive MIMO is considered to be one of the key technologies in the emerging 5G systems, but also a concept applicable to other wireless systems. Exploiting the large number of degrees of freedom (DoFs) of massive MIMO is essential for achieving high spectral efficiency, high data rates and extreme spatial multiplexing of densely distributed users. On the one hand, the benefits of applying massive MIMO for broadband communication are well known and there has been a large body of research on designing communication schemes to support high rates. On the other hand, using massive MIMO for Internet-of-Things (IoT) is still a developing topic, as IoT connectivity has requirements and constraints that are significantly different from the broadband connections. In this paper we investigate the applicability of massive MIMO to IoT connectivity. Specifically, we treat the two generic types of IoT connections envisioned in 5G: massive machine-type communication (mMTC) and ultra-reliable low-latency communication (URLLC). This paper fills this important gap by identifying the opportunities and challenges in exploiting massive MIMO for IoT connectivity. We provide insights into the trade-offs that emerge when massive MIMO is applied to mMTC or URLLC and present a number of suitable communication schemes. The discussion continues to the questions of network slicing of the wireless resources and the use of massive MIMO to simultaneously support IoT connections with very heterogeneous requirements. The main conclusion is that massive MIMO can bring benefits to the scenarios with IoT connectivity, but it requires tight integration of the physical-layer techniques with the protocol design. (C) 2019 Elsevier B.V. All rights reserved.Funding Agencies|European Research Council (ERC) under the European UnionEuropean Research Council (ERC) [648382 WILLOW]; Danish Council for Independent Research, Denmark [8022-00284B SEMIOTIC]; National Council for Scientific and Technological Development (CNPq) of BrazilNational Council for Scientific and Technological Development (CNPq) [304066/2015-0]; Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior Brazil (CAPES)CAPES [001]; Swedish Research Council (VR)Swedish Research Council; Excellence Center at Linkoping - Lund in Information Technology (ELLIIT), Denmark; CONFAP-ERC Agreement H2020 (Brazilian National Council of State Funding Agencies); CONFAP-ERC Agreement H2020 (European Research Council)</p