Multi-User and Interference networks
Multi-user MIMO Communications
In multiuser MIMO networks, the spatial degrees of freedom offered by multiple antennas can be
advantageously exploited to enhance the system capacity, by scheduling multiple users to simultaneously
share the spatial channel. This entails a fundamental paradigm shift from single user communications,
since multiuser systems can experience substantial benefit from channel state information at the transmitter
and, at the same time, require more complex scheduling strategies and transceiver methodologies. Our group considers in particular open problems such as the efficient design of precoders, joint design of precoders and decoders (e.g. linear), multi-user linear detectors, interaction between precoding and multi-user scheduling.
The role of feedback in multi-user communications
Although it can be shown that, unlike in the single user MIMO case, feedback of channel state information at the transmitter plays a crucial role in designing efficient precoders in multi-user MIMO channels, a considerable interest has been put on more practical limited feedback schemes that require only partial channel state information at the transmitter side. A crucial question can be formulated as follows: What is the optimal trade-off between channel representation at the transmitter and the precoding performance? What are the most meaningful attributes of the propagation channel towards which more feedback resource ought to be devoted. This research area lies at the cross-roads between source compression (rate-distorsion) and MIMO commucation theory.
Communications methods for interference limited channels
Interference limited channels form a wide class of channels with clear applications to cellular networks, heterogenous networks (Femto/Macro), wireless sensor networs, cognitive radio networks. In general terms, interference is the price to pay on the way to emerging modern unplanned wireless communications and hence consititute a major performance bottleneck. Finding ways of controling and mitigating interference are arised as one of the hottest research topics these days.
Cooperation and Coordination over the Interference Channels
Conventional approaches to interference are two-fold: i) via spatial reuse partitioning, which prevents the reuse of any spectral resource within a certain cluster of cells, or ii) by relying on enhanced physical layer design at the receiver side, such as based on advanced iterative decoding, or the use of multiple antenna-based interference rejection. This approach to dealing with interference may be characterized as passive. In contrast, the emerging view on network design advocates a more proactive treatment of interference, which can be accomplished through some form of interference-aware multi-transmitter coordination. Although the complexity associated with the coordination protocols can vary greatly, the underlying principle is the same: Base stations no longer tune separately their physical and link/MAC layer parameters (power level, time slot, subcarrier usage, beamforming coefficients etc.) or decode independently of one another, but instead coordinate their coding or decoding operations on the basis of global channel state and user data information exchanged in a preamble phase. There are several possible degrees of cooperation offering a trade-off between performance gains and the amount of overhead placed on the backhaul and over-the-air feedback channels. Some of the techniques we investigate include:
- Power control coordination
- multi-cell scheduling
- multiple antenna coordinated precoding (interference alignement)
- Joint multi-transmitter MIMO precoding ("Network MIMO" or "Joint processing CoMP"
On feedback and information exchange in interference channels
Typical multi-transmitter coordination and cooperation methods require the sharing of global channel state information and, in the case of network -MIMO, the additional sharing of user data packets (messages). Although the sharing of user data symbols can be made possible in certain situations, such as cellular networks with a pre-existing backbone infrastructure it is not always the case (cognitive radio systems). In addition the obtaining of accurate CSI at the TX is made difficult due to the finite quantizing effects over the feedback channels and the limited capability of
signaling between TXs to exchange the CSI. In addition, CSI exchange necessarily introduces further degradation due to latency effects over inter-TX links. This situation gives rise to an interesting information and communication theoretic framework whereby cooperating transmitters must act in a consistent manner, and must do so on the basis individual local information, possibly different from each other. We refer to such situations as distributed CSI (DCSI) channels. We investigate the optimal transmission techniques in such scenarios, borrowing from Team Decision theory. Another fundamental open problem is the optimal design of feedback allocation under a global information exchange overhead limit: "Who needs to know just how much about what in the channel"