In this work, we analyze the diversity-multiplexing performance of a MIMO multiple access wireless system with non-cooperating transmitters. Each of the transmitters and receiver use noisy and mismatched versions of the channel estimate to implement decentralized power control. While accounting for the resources consumed in training, we show that with relatively simple power control, regardless of the number of transmitters, we can achieve double the maximum diversity order of a system with no instantaneous channel state information at the transmitters. Intuitively, the gain can be attributed to using temporal degrees of freedom enabled by power control without coding over multiple coherence intervals.
Abstract-Two distinct models of feedback, suited for FDD (Frequency Division Duplex) and TDD (Frequency Division Duplex) systems respectively, have been widely studied in the literature. In this paper, we compare these two models of feedback in terms of the diversity multiplexing tradeoff for varying amount of channel state information at the terminals. We find that, when all imperfections are accounted for, the maximum achievable diversity order in FDD systems matches the diversity order in TDD systems. TDD systems achieve better diversity order at higher multiplexing gains. In FDD systems, the maximum diversity order can be achieved with just a single bit of feedback. Additional bits of feedback (perfect or imperfect) do not affect the diversity order if the receiver does not know the channel state information.
Abstract-When channel state information is available at the transmitter, we can diagonalize a MIMO channel with SVD transceivers. However, outage of the weaker eigenchannels limits the performance of such a transceiver. In the current work, we propose and analytically characterize co-ordinate interleaving of multi-dimensional symbols over sets of eigenchannels. We show that in our method, the diversity multiplexing trade-off (DMT) is determined by the strongest eigenchannel in each set. We also calculate the optimal (DMT) for different possible sets and constellation dimensions with rate allocation among the sets.
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