3 research outputs found
Diversity Order Gain with Noisy Feedback in Multiple Access Channels
In this paper, we study the effect of feedback channel noise on the
diversity-multiplexing tradeoff in multiuser MIMO systems using quantized
feedback, where each user has m transmit antennas and the base-station receiver
has n antennas. We derive an achievable tradeoff and use it to show that in
SNR-symmetric channels, a single bit of imperfect feedback is sufficient to
double the maximum diversity order to 2mn compared to when there is no feedback
(maximum is mn at multiplexing gain of zero). Further, additional feedback bits
do not increase this maximum diversity order beyond 2mn. Finally, the above
diversity order gain of mn over non-feedback systems can also be achieved for
higher multiplexing gains, albeit requiring more than one bit of feedback.Comment: Proceedings of the 2008 IEEE International Symposium on Information
Theory, Toronto, ON, Canada, July 6 - 11, 200
Bits About the Channel: Multi-round Protocols for Two-way Fading Channels
Most communication systems use some form of feedback, often related to
channel state information. In this paper, we study diversity multiplexing
tradeoff for both FDD and TDD systems, when both receiver and transmitter
knowledge about the channel is noisy and potentially mismatched. For FDD
systems, we first extend the achievable tradeoff region for 1.5 rounds of
message passing to get higher diversity compared to the best known scheme, in
the regime of higher multiplexing gains. We then break the mold of all current
channel state based protocols by using multiple rounds of conferencing to
extract more bits about the actual channel. This iterative refinement of the
channel increases the diversity order with every round of communication. The
protocols are on-demand in nature, using high powers for training and feedback
only when the channel is in poor states. The key result is that the diversity
multiplexing tradeoff with perfect training and K levels of perfect feedback
can be achieved, even when there are errors in training the receiver and errors
in the feedback link, with a multi-round protocol which has K rounds of
training and K-1 rounds of binary feedback. The above result can be viewed as a
generalization of Zheng and Tse, and Aggarwal and Sabharwal, where the result
was shown to hold for K=1 and K=2 respectively. For TDD systems, we also
develop new achievable strategies with multiple rounds of communication between
the transmitter and the receiver, which use the reciprocity of the forward and
the feedback channel. The multi-round TDD protocol achieves a
diversity-multiplexing tradeoff which uniformly dominates its FDD counterparts,
where no channel reciprocity is available.Comment: Submitted to IEEE Transactions on Information Theor
Power-Controlled Feedback and Training for Two-way MIMO Channels
Most communication systems use some form of feedback, often related to
channel state information. The common models used in analyses either assume
perfect channel state information at the receiver and/or noiseless state
feedback links. However, in practical systems, neither is the channel estimate
known perfectly at the receiver and nor is the feedback link perfect. In this
paper, we study the achievable diversity multiplexing tradeoff using i.i.d.
Gaussian codebooks, considering the errors in training the receiver and the
errors in the feedback link for FDD systems, where the forward and the feedback
are independent MIMO channels.
Our key result is that the maximum diversity order with one-bit of feedback
information is identical to systems with more feedback bits. Thus,
asymptotically in , more than one bit of feedback does not
improve the system performance at constant rates. Furthermore, the one-bit
diversity-multiplexing performance is identical to the system which has perfect
channel state information at the receiver along with noiseless feedback link.
This achievability uses novel concepts of power controlled feedback and
training, which naturally surface when we consider imperfect channel estimation
and noisy feedback links. In the process of evaluating the proposed training
and feedback protocols, we find an asymptotic expression for the joint
probability of the exponents of eigenvalues of the actual
channel and the estimated channel which may be of independent interest.Comment: in IEEE Transactions on Information Theory, 201