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We investigate the effects of fading correlations on wireless communication systems employing multiple antennas at both the receiver and the transmitter side of the link, so called multiple-input multiple-output (MIMO) systems. It turns out that the amount of transmitter sided channel knowledge plays an important part when dealing with fading correlations. Furthermore, the possible availability of time diversity in a time-selective channel can have essential influence on performance. To study the influence of time-selectivity, the concept of sample-mean outage is introduced and applied to information theoretic measures, like capacity or cutoff rate. It will be shown, that in some cases correlated fading may offer better performance than uncorrelated fading permits, which is due to exploitable antenna gain, that will also be defined in a general form for MIMO systems.

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A procedure to achieve near-field multiple input multiple output (MIMO) communication with equally strong channels is demonstrated in this paper. This has applications in near-field wireless communications, such as Chip-to-Chip (C2C) communication or wireless links between printed circuit boards. Designing the architecture of these wireless C2C networks is, however, based on standard engineering design tools. To attain this goal, a network optimization procedure is proposed, which introduces decoupling and matching networks. As a demonstration, this optimization procedure is applied to a 2-by-2 MIMO with dipole antennas. The potential benefits and design tradeoffs are discussed for implementation of wireless radio-frequency interconnects in chip-to-chip or device-to-device communication such as in an Internet-of-Things scenario.

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In this letter, we introduce five different strategies of linear transmit signal processing for multi-user MIMO systems and provide performance comparisons in terms of maximum throughput in both uncorrelated and correlated channels when the number of transmit antennas is much larger than the number of receive antennas. It is shown that the multi-user MIMO schemes are preferable to TDMA based MIMO schemes, hence demonstrating the power of multi-user MIMO signal processing. Our work also indicates possibilities for future research in finding efficient sub-optimal algorithms. As an example, we show that our Multi-user MIMO Decomposition scheme can improve the maximum throughput compared to TDMA based MIMO schemes for large number of transmit antennas or high transmit power.

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