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Institutional Repository [SANDBOX]
Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/E0297DB1-EF0C-49A5-9EE8-BFE73C98A52D | ||
| Year | 2017 | ||
| Type of Item | Diploma Work | ||
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| Bibliographic Citation | Triantafyllos Papakonstantinou, "Massive MIMO wireless communication", Diploma Work, School of Electrical and Computer Engineering, Technical University of Crete, Chania, Greece, 2017 https://doi.org/10.26233/heallink.tuc.67681 | ||
| Appears in Collections |
In this thesis, we study a novel cellular network architecture, called “Massive MIMO”. The characteristic of massive MIMO architecture is to equip Base Stations with a number of antennas much larger than the number of active users. This promising idea offers enormous enhancements in spectral and energy efficiency, simple signal processing, and more. To understand how massive MIMO works in a wireless cellular system, we focus our study on the pioneering and award-winning paper "Noncooperative cellular wireless with unlimited numbers of base station antennas" of Thomas L. Marzetta, who introduced and popularized the concept of massive MIMO. By simulating a scenario of multicellular wireless system, we see the beneficial contribution of the use of multiple antennas (more than 100) and learn about the problem of pilot contamination, which is generated during the channel estimation phase. This phenomenon limits the capacity of the system and its elimination is of primary importance. To mitigate pilot contamination, we may use a less aggressive frequency reuse strategy in the cellular network but, as we will see, this improves the system behavior in terms of interference but it does not lead to high communication rates. After having realized the restrictive role of pilot contamination, we study a very interesting novel idea, which has been presented in the paper entitled “A coordinated approach to channel estimation in large-scale multiple-antenna systems,” and seems to address the problem (at least at a theoretical level). This paper develops an algorithm which, in conjunction with an improved channel estimator, tackles the pilot contamination problem by taking advantage of the multiple antenna dimensions and exploiting the side information lying in the second-order statistics of the channel vectors.
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