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Spectral Efficiency of Multipair Massive MIMO Two-Way Relaying With Imperfect CSI
Zhejiang Univ, Peoples R China; Xidian Univ, Peoples R China.
Zhejiang Univ, Peoples R China; Xidian Univ, Peoples R China.
Queens Univ Belfast, North Ireland.
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-5954-434X
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2019 (English)In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 68, no 7, p. 6593-6607Article in journal (Refereed) Published
Abstract [en]

We consider a two-way half-duplex relaying system where multiple pairs of single-antenna users exchange information assisted by a multiple-antenna relay. Taking into account the practical constraint of imperfect channel knowledge, we study the achievable sum spectral efficiency (SE) of the amplify-and-forward protocol, assuming that the relay employs maximum ratio processing. We derive a closed-form expression for the sum SE for arbitrary system parameters and a large-scale approximation for the sum SE when the number of relay antennas M becomes sufficiently large. In addition, we study how the transmit power reduces with M to maintain a desired SE. Our results show that by using a large number of relay antennas, the transmit powers of the user, relay, and pilot symbol can be scaled down proportionally to 1/M-alpha, 1/M beta, and 1/M-gamma for certain combinations of a, beta, and gamma, respectively. This elegant power scaling law reveals a fundamental tradeoff between the transmit powers of the user/relay and pilot symbol. Finally, capitalizing on the new expressions for the sum SE, novel power allocation schemes are designed to further improve the sum SE.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC , 2019. Vol. 68, no 7, p. 6593-6607
Keywords [en]
Amplify-and-forward; geometric programming; massive MIMO; power scaling law; two-way relaying
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:liu:diva-159593DOI: 10.1109/TVT.2019.2915005ISI: 000476775000031OAI: oai:DiVA.org:liu-159593DiVA, id: diva2:1342284
Note

Funding Agencies|National Natural Science Foundation of China (NSFC) [61671406, 61725104]; NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization [U1709219]; State Key Laboratory of Integrated Services Networks [ISN19-05]; RAEng/The Leverhulme Trust Senior Research Fellowship [LTSRF1718\14\2]; ELLIIT; CENIIT

Available from: 2019-08-13 Created: 2019-08-13 Last updated: 2019-08-13

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