A cooperative massive MIMO system for future In vivo nanonetworks

Belaoura, W., Ghanem, K., Imran, M. A. , Alomainy, A. and Abbasi, Q. H. (2021) A cooperative massive MIMO system for future In vivo nanonetworks. IEEE Systems Journal, 15(1), pp. 331-337. (doi: 10.1109/JSYST.2020.2995671)

Abstract

Terahertz propagation inside human body tissues suffers from a low achievable capacity, which drastically limits the usefulness of in vivo nanoscale networks. In this article, a virtual massive multiple-input multiple-output (m-MIMO) array architecture constructed by the cooperative and opportunistic action of distributed nano nodes to form a cluster is introduced for the first time for in vivo nano communications. Moreover, a joint carefully designed scheme merging an antenna-selection-based maximum magnitude (MM) criterion and a spatial modulation (SM) transmission concept is incorporated within this virtual m-MIMO architecture, as a way to achieve the best compromise between performance and complexity. Capacity maximization achieved by the proposed MM antenna selection is also derived for the proposed system. Simulation results consolidate the effectiveness of the proposed MM antenna-selection-assisted SM for the virtual m-MIMO system inside human bodies. It is shown that the MM antenna selection can greatly improve the performance of the proposed architecture in terms of the bit error rate and reduce the complexity.

• Item Type: Articles
• Additional Information: This publication was made possible by NPRP grant number NPRP 10-1231-160071 from the Qatar National Research Fund (a member of Qatar Foundation).
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Abbasi, Professor Qammer and Imran, Professor Muhammad and belaoura, widad
• Authors: Belaoura, W., Ghanem, K., Imran, M. A., Alomainy, A., and Abbasi, Q. H.
• College/School: College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering; College of Science and Engineering > School of Engineering > Systems Power and Energy
• Journal Name: IEEE Systems Journal
• Publisher: IEEE
• ISSN: 1932-8184
• ISSN (Online): 1937-9234
• Published Online: 15 June 2020
• Copyright Holders: Copyright © 2020 IEEE
• First Published: First published in IEEE Systems Journal 15(1):331-337
• Publisher Policy: Reproduced in accordance with the publisher copyright policy