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Massive multiple-input multiple-output technology has been considered a breakthrough in wireless communication systems. It consists of equipping a base station with a large number of antennas to serve many active users in the same time-frequency block. Among its underlying advantages is the possibility to focus transmitted signal energy into very short-range areas, which will provide huge improvements in terms of system capacity. However, while this new concept renders many interesting benefits, it brings up new challenges that have called the attention of both industry and academia: channel state information acquisition, channel feedback, instantaneous reciprocity, statistical reciprocity, architectures, and hardware impairments, just to mention a few. This paper presents an overview of the basic concepts of massive multiple-input multiple-output, with a focus on the challenges and opportunities, based on contemporary research.

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International audienceIn this paper, we present new space-time multiplexing codes (STMC) for multiple-antenna transmissions, which rely on a three-dimensional tensor modeling of the transmitted/received signals. The proposed codes combine spatial multiplexing and space-time coding by spreading a linear combination of different sub-streams of data over the space and time dimensions. We show the STMC induces a tensor structure on the transmitted/received signal that can be modeled using a trilinear tensor decomposition. Tensor modeling is exploited at the receiver for a blind decoding of the transmitted sub-streams based on linear processing and without any ambiguity. The proposed approach also provides full diversity while benefiting from the maximum multiplexing gain offered by the multiple antennas. Simulation results show that the tensor-based STMC offer remarkable performance with good diversity-multiplexing trade-of