5,745 research outputs found
Precoded Integer-Forcing Universally Achieves the MIMO Capacity to Within a Constant Gap
An open-loop single-user multiple-input multiple-output communication scheme
is considered where a transmitter, equipped with multiple antennas, encodes the
data into independent streams all taken from the same linear code. The coded
streams are then linearly precoded using the encoding matrix of a perfect
linear dispersion space-time code. At the receiver side, integer-forcing
equalization is applied, followed by standard single-stream decoding. It is
shown that this communication architecture achieves the capacity of any
Gaussian multiple-input multiple-output channel up to a gap that depends only
on the number of transmit antennas.Comment: to appear in the IEEE Transactions on Information Theor
Successive Integer-Forcing and its Sum-Rate Optimality
Integer-forcing receivers generalize traditional linear receivers for the
multiple-input multiple-output channel by decoding integer-linear combinations
of the transmitted streams, rather then the streams themselves. Previous works
have shown that the additional degree of freedom in choosing the integer
coefficients enables this receiver to approach the performance of
maximum-likelihood decoding in various scenarios. Nonetheless, even for the
optimal choice of integer coefficients, the additive noise at the equalizer's
output is still correlated. In this work we study a variant of integer-forcing,
termed successive integer-forcing, that exploits these noise correlations to
improve performance. This scheme is the integer-forcing counterpart of
successive interference cancellation for traditional linear receivers.
Similarly to the latter, we show that successive integer-forcing is capacity
achieving when it is possible to optimize the rate allocation to the different
streams. In comparison to standard successive interference cancellation
receivers, the successive integer-forcing receiver offers more possibilities
for capacity achieving rate tuples, and in particular, ones that are more
balanced.Comment: A shorter version was submitted to the 51st Allerton Conferenc
Computation Alignment: Capacity Approximation without Noise Accumulation
Consider several source nodes communicating across a wireless network to a
destination node with the help of several layers of relay nodes. Recent work by
Avestimehr et al. has approximated the capacity of this network up to an
additive gap. The communication scheme achieving this capacity approximation is
based on compress-and-forward, resulting in noise accumulation as the messages
traverse the network. As a consequence, the approximation gap increases
linearly with the network depth.
This paper develops a computation alignment strategy that can approach the
capacity of a class of layered, time-varying wireless relay networks up to an
approximation gap that is independent of the network depth. This strategy is
based on the compute-and-forward framework, which enables relays to decode
deterministic functions of the transmitted messages. Alone, compute-and-forward
is insufficient to approach the capacity as it incurs a penalty for
approximating the wireless channel with complex-valued coefficients by a
channel with integer coefficients. Here, this penalty is circumvented by
carefully matching channel realizations across time slots to create
integer-valued effective channels that are well-suited to compute-and-forward.
Unlike prior constant gap results, the approximation gap obtained in this paper
also depends closely on the fading statistics, which are assumed to be i.i.d.
Rayleigh.Comment: 36 pages, to appear in IEEE Transactions on Information Theor
Integer-Forcing Linear Receivers
Linear receivers are often used to reduce the implementation complexity of
multiple-antenna systems. In a traditional linear receiver architecture, the
receive antennas are used to separate out the codewords sent by each transmit
antenna, which can then be decoded individually. Although easy to implement,
this approach can be highly suboptimal when the channel matrix is near
singular. This paper develops a new linear receiver architecture that uses the
receive antennas to create an effective channel matrix with integer-valued
entries. Rather than attempting to recover transmitted codewords directly, the
decoder recovers integer combinations of the codewords according to the entries
of the effective channel matrix. The codewords are all generated using the same
linear code which guarantees that these integer combinations are themselves
codewords. Provided that the effective channel is full rank, these integer
combinations can then be digitally solved for the original codewords. This
paper focuses on the special case where there is no coding across transmit
antennas and no channel state information at the transmitter(s), which
corresponds either to a multi-user uplink scenario or to single-user V-BLAST
encoding. In this setting, the proposed integer-forcing linear receiver
significantly outperforms conventional linear architectures such as the
zero-forcing and linear MMSE receiver. In the high SNR regime, the proposed
receiver attains the optimal diversity-multiplexing tradeoff for the standard
MIMO channel with no coding across transmit antennas. It is further shown that
in an extended MIMO model with interference, the integer-forcing linear
receiver achieves the optimal generalized degrees-of-freedom.Comment: 40 pages, 16 figures, to appear in the IEEE Transactions on
Information Theor
Flexible Backhaul Design and Degrees of Freedom for Linear Interference Networks
The considered problem is that of maximizing the degrees of freedom (DoF) in
cellular downlink, under a backhaul load constraint that limits the number of
messages that can be delivered from a centralized controller to the base
station transmitters. A linear interference channel model is considered, where
each transmitter is connected to the receiver having the same index as well as
one succeeding receiver. The backhaul load is defined as the sum of all the
messages available at all the transmitters normalized by the number of users.
When the backhaul load is constrained to an integer level B, the asymptotic per
user DoF is shown to equal (4B-1)/(4B), and it is shown that the optimal
assignment of messages to transmitters is asymmetric and satisfies a local
cooperation constraint and that the optimal coding scheme relies only on
zero-forcing transmit beamforming. Finally, an extension of the presented
coding scheme is shown to apply for more general locally connected and
two-dimensional networks.Comment: Submitted to IEEE International Symposium on Information Theory (ISIT
2014
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