Max-min SINR low complexity transceiver design for single cell massive MIMO

This work focuses on large scale multi-user MIMO systems in which the base station (BS) outfitted with M antennas communicates with K single antenna user equipments (UEs). In particular, we aim at designing the linear precoder and receiver that maximizes the minimum signal-to-interference-plus-noise...

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Vydáno v:2016 IEEE 17th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) s. 1 - 6
Hlavní autoři: Sifaou, Houssem, Kammoun, Abla, Sanguinetti, Luca, Debbah, Merouane, Alouini, Mohamed-Slim
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.07.2016
Témata:
Antennas
Complexity theory
Interference
linear transceivers
low complexity
Massive MIMO systems
MIMO
Precoding
random matrix theory
Receivers
Signal to noise ratio
truncated polynomial expansion
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Shrnutí:This work focuses on large scale multi-user MIMO systems in which the base station (BS) outfitted with M antennas communicates with K single antenna user equipments (UEs). In particular, we aim at designing the linear precoder and receiver that maximizes the minimum signal-to-interference-plus-noise ratio (SINR) subject to a given power constraint. To gain insights into the structure of the optimal precoder and receiver as well as to reduce the computational complexity for their implementation, we analyze the asymptotic regime where M and K grow large with a given ratio and make use of random matrix theory (RMT) tools to compute accurate approximations. Although simpler, the implementation of the asymptotic precoder and receiver requires fast inversions of large matrices in every coherence period. To overcome this issue, we apply the truncated polynomial expansion (TPE) technique to the precoding and receiving vector of each UE and make use of RMT to determine the optimal weighting coefficients that asymptotically solve the max-min SINR problem. Numerical results are used to show that the proposed TPE-based precoder and receiver almost achieve the same performance as the optimal ones while requiring a lower complexity.
DOI:10.1109/SPAWC.2016.7536729