Since the development of 4G networks, Multiple-Input Multiple-Output (MIMO) and later multiple-user MIMO became a mature part to increase the spectral efficiency of mobile communication networks. An essential part of simultaneous multiple-user communication is the grouping of users with complementing channel properties. With the introduction of Base Station (BS) with large amount of antenna ports, i.e. transceiver units, the focus in spatial precoding is moved from uniform to heterogeneous cell coverage with changing traffic demands throughout the cell and 3D beamforming. In order to deal with the increasing feedback requirement for Frequency-Division Duplex (FDD) systems, concepts for user clustering on second order statistics are suggested in both the scientific and standardization literature. Former 3rd Generation Partnership Project (3GPP) Geometry-based Stochastic Channel Model (GSCM) channel models lack the required spatial correlation of small-scale fading. Since the latest release of 3GPP Geometrybased Stochastic Channel Model this issue is claimed to be solved and hence our contribution is an evaluation of this spatial consistency feature.

As the standardization of full dimension multiple-input multiple-output (MIMO) systems in the 3 rd Generation Partnership Project progresses, the research community has started to explore the potential of very large arrays as an enabler technology for meeting the requirements of 5 th generation systems. Indeed, in its final deliverable, the European 5G project Mobile and Wireless Communication Enablers for the 2020 Information Society (METIS) identifies massive MIMO as a key 5G enabler and proposes specific technology components that will allow the cost efficient deployment of cellular systems taking advantage of hundreds of antennas at cellular base stations. These technology components include handling the inherent pilot-data resource allocation trade-off in a near optimal fashion, a novel random access scheme supporting a large number of users, coded channel state information for sparse channels in frequency division duplexing systems, managing user grouping and multi-user beamforming, and a decentralized coordinated transceiver design. The aggregate effect of these components enables massive MIMO to contribute to the METIS objectives of delivering very high data rates and managing dense populations.

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CoMP transmission gains attraction for future releases of LTE-Advanced specifications. It is considered for downlink cochannel interference mitigation of OFDMA systems operated at full frequency reuse. However, channel knowledge at the transmitter side will be required, where its usability reduces over time, even under quasi-static mobility. This work studies the range of performance degradation caused by channel aging and delayed utilization for the purpose of joint zero-forcing precoding from a subset of base stations. We demonstrate that channel prediction significantly improves the CoMP performance: There is hardly any difference between ideal and delayed feedback when utilizing prediction filters in low mobility regime.

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