9 research outputs found
Dynamic Interference Mitigation for Generalized Partially Connected Quasi-static MIMO Interference Channel
Recent works on MIMO interference channels have shown that interference
alignment can significantly increase the achievable degrees of freedom (DoF) of
the network. However, most of these works have assumed a fully connected
interference graph. In this paper, we investigate how the partial connectivity
can be exploited to enhance system performance in MIMO interference networks.
We propose a novel interference mitigation scheme which introduces constraints
for the signal subspaces of the precoders and decorrelators to mitigate "many"
interference nulling constraints at a cost of "little" freedoms in precoder and
decorrelator design so as to extend the feasibility region of the interference
alignment scheme. Our analysis shows that the proposed algorithm can
significantly increase system DoF in symmetric partially connected MIMO
interference networks. We also compare the performance of the proposed scheme
with various baselines and show via simulations that the proposed algorithms
could achieve significant gain in the system performance of randomly connected
interference networks.Comment: 30 pages, 10 figures, accepted by IEEE Transaction on Signal
Processin
Interference Alignment via Message-Passing
We introduce an iterative solution to the problem of interference alignment
(IA) over MIMO channels based on a message-passing formulation. We propose a
parameterization of the messages that enables the computation of IA precoders
by a min-sum algorithm over continuous variable spaces -- under this
parameterization, suitable approximations of the messages can be computed in
closed-form. We show that the iterative leakage minimization algorithm of
Cadambe et al. is a special case of our message-passing algorithm, obtained for
a particular schedule. Finally, we show that the proposed algorithm compares
favorably to iterative leakage minimization in terms of convergence speed, and
discuss a distributed implementation.Comment: Submitted to the IEEE International Conference on Communications
(ICC) 201
Limited Feedback Design for Interference Alignment on MIMO Interference Networks with Heterogeneous Path Loss and Spatial Correlations
Interference alignment is degree of freedom optimal in K -user MIMO
interference channels and many previous works have studied the transceiver
designs. However, these works predominantly focus on networks with perfect
channel state information at the transmitters and symmetrical interference
topology. In this paper, we consider a limited feedback system with
heterogeneous path loss and spatial correlations, and investigate how the
dynamics of the interference topology can be exploited to improve the feedback
efficiency. We propose a novel spatial codebook design, and perform dynamic
quantization via bit allocations to adapt to the asymmetry of the interference
topology. We bound the system throughput under the proposed dynamic scheme in
terms of the transmit SNR, feedback bits and the interference topology
parameters. It is shown that when the number of feedback bits scales with SNR
as C_{s}\cdot\log\textrm{SNR}, the sum degrees of freedom of the network are
preserved. Moreover, the value of scaling coefficient C_{s} can be
significantly reduced in networks with asymmetric interference topology.Comment: 30 pages, 6 figures, accepted by IEEE transactions on signal
processing in Feb. 201
Interference Alignment for Partially Connected MIMO Cellular Networks
In this paper, we propose an iterative interference alignment (IA) algorithm
for MIMO cellular networks with partial connectivity, which is induced by
heterogeneous path losses and spatial correlation. Such systems impose several
key technical challenges in the IA algorithm design, namely the overlapping
between the direct and interfering links due to the MIMO cellular topology as
well as how to exploit the partial connectivity. We shall address these
challenges and propose a three stage IA algorithm. As illustration, we analyze
the achievable degree of freedom (DoF) of the proposed algorithm for a
symmetric partially connected MIMO cellular network. We show that there is
significant DoF gain compared with conventional IA algorithms due to partial
connectivity. The derived DoF bound is also backward compatible with that
achieved on fully connected K-pair MIMO interference channels.Comment: Submitted to IEEE Transactions on Signal Processing, accepte
Adaptive transmission in heterogeneous networks
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/166243/1/cmu2bf00018.pd