Download PDF

2017 51st Asilomar Conference on Signals, Systems, and Computers, Date: 2017/10/29 - 2017/11/01, Location: Pacific Grove, CA, USA

Publication date: 2017-11
Volume: 489 Pages: 271 - 276
ISBN: 978-1-5386-1823-3 ISSN: 2576-2303
DOI: 10.1109/ACSSC.2017.8335182
Publisher: IEEE

2017 51st Asilomar Conference on Signals, Systems, and Computers


Chen, Cheng-Ming
Guevara Toledo, Andrea ; Pollin, Sofie


Distributed antenna array, large-scale antenna systems, massive MIMO, software defined radio, spatial separation, Science & Technology, Technology, Computer Science, Information Systems, Engineering, Electrical & Electronic, Telecommunications, Computer Science, Engineering


Massive MIMO (MaMIMO) is a technology of primary interest for sub-6 GHz operation in the next generation cellular systems. While MaMIMO is most often linked to macrocell scenarios, where a single cell serves many users distributed over a large area, network densification will also result in scenarios where many users are served by a MaMIMO base station (BS) that is nearby. A key question is how to scale up MaMIMO: should we add more antennas to a given cell, or create multiple smaller and distributed cells that can cooperate? This paper documents the measured performance of a very dense MaMIMO system for an indoor-to-outdoor propagation environment. The impact of the number of antennas, and the distribution of the antenna elements is experimentally verified for a simplified linear deployment of the BSs. Concretely, we serve 12 closely located users with 16, 32 or 64 antennas. We compare a centrally positioned collocated array and two distributed arrays with their uplink throughput in a licensed 2.6 GHz band. The experimental results show that 12 users can be served with only 32 antennas for the distributed topology, which is effectively only 16 antennas per MaMIMO BS. For the specific case analyzed in our measurement campaign, with the centralized deployment, 64 antennas are needed to obtain good performance, while distributing the antenna elements in two sub-arrays improves total performance and fairness between the users.