Symbiotic Radio: Cognitive Backscattering Communications for Future Wireless Networks
2020 (English)In: IEEE Transactions on Cognitive Communications and Networking, E-ISSN 2332-7731, Vol. 6, no 4, p. 1242-1255Article in journal (Refereed) Published
Abstract [en]
The heterogenous wireless services and exponentially growing traffic call for novel spectrum- and energy-efficient wireless communication technologies. Recently, a new technique, called symbiotic radio (SR), is proposed to exploit the benefits and address the drawbacks of cognitive radio (CR) and ambient backscattering communications (AmBC), leading to mutualism spectrum sharing and highly reliable backscattering communications. In particular, the secondary transmitter (STx) in SR transmits messages to the secondary receiver (SRx) over the RF signals originating from the primary transmitter (PTx) based on cognitive backscattering communications, thus the secondary system shares not only the radio spectrum, but also the power, and infrastructure with the primary system. In return, the secondary transmission provides beneficial multipath diversity to the primary system, therefore the two systems form mutualism spectrum sharing. More importantly, joint decoding is exploited at SRx to achieve highly reliable backscattering communications. In this article, to exploit the full potential of SR, we provide a systematic view for SR and address three fundamental tasks in SR: (1) enhancing the backscattering link via active load; (2) achieving highly reliable communications through joint decoding; and (3) capturing PTxs RF signals using reconfigurable intelligent surfaces. Emerging applications, design challenges and open research problems will also be discussed.
Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC , 2020. Vol. 6, no 4, p. 1242-1255
Keywords [en]
Symbiotic radio; cognitive radio; ambient backscattering communications; spectrum management; spectrum efficiency; energy efficiency; joint decoding; reconfigurable intelligent surfaces; large intelligent antennas
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:liu:diva-172201DOI: 10.1109/TCCN.2020.3023139ISI: 000597145100011OAI: oai:DiVA.org:liu-172201DiVA, id: diva2:1512934
Note
Funding Agencies|Key Areas of Research and Development Program of Guangdong Province, China [2018B010114001]; National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [61631005, U1801261]; National Key Research and Development Program of China [2018YFB1801105]; Programme of Introducing Talents of Discipline to UniversitiesMinistry of Education, China - 111 Project [B20064]; [ZYGX2019Z022]
2020-12-282020-12-282023-01-25