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Adaptive Pilot Clustering in Heterogeneous Massive MIMO Networks
KTH, School of Electrical Engineering (EES), Signal Processing.
KTH, School of Electrical Engineering (EES), Signal Processing.
2016 (English)In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 15, no 8, 5555-5568 p.Article in journal (Refereed) Published
Abstract [en]

We consider the uplink of a cellular massive multiple-input multiple-output network. Acquiring channel state information at the base stations (BSs) requires uplink pilot signaling. Since the number of orthogonal pilot sequences is limited by the channel coherence, pilot reuse across cells is necessary to achieve high spectral efficiency. However, finding efficient pilot reuse patterns is non-trivial, especially in practical asymmetric BS deployments. We approach this problem using the coalitional game theory. Each BS has a few unique pilots and can form coalitions with other BSs to gain access to more pilots. The BSs in a coalition, thus, benefit from serving more users in their cells at the expense of higher pilot contamination and interference. Given that a cell's average spectral efficiency depends on the overall pilot reuse pattern, the suitable coalitional game model is in the partition form. We develop a low-complexity distributed coalition formation based on individual stability. By incorporating a BS intercommunication budget constraint, we are able to control the overhead in message exchange between the BSs and ensure the algorithm's convergence to a solution of the game called individually stable coalition structure. Simulation results reveal fast algorithmic convergence and substantial performance gains over the baseline schemes with no pilot reuse, full pilot reuse, or random pilot reuse pattern.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2016. Vol. 15, no 8, 5555-5568 p.
Keyword [en]
Massive MIMO networks, spectral efficiency, pilot contamination, coalitional game theory
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
URN: urn:nbn:se:kth:diva-193224DOI: 10.1109/TWC.2016.2561289ISI: 000381509900031ScopusID: 2-s2.0-84982272577OAI: diva2:1034147
16th IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), JUN 28-JUL 01, 2015, Stockholm, SWEDEN

QC 20161011

Available from: 2016-10-11 Created: 2016-09-30 Last updated: 2016-10-11Bibliographically approved

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