67 research outputs found
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
Full Diversity Unitary Precoded Integer-Forcing
We consider a point-to-point flat-fading MIMO channel with channel state
information known both at transmitter and receiver. At the transmitter side, a
lattice coding scheme is employed at each antenna to map information symbols to
independent lattice codewords drawn from the same codebook. Each lattice
codeword is then multiplied by a unitary precoding matrix and sent
through the channel. At the receiver side, an integer-forcing (IF) linear
receiver is employed. We denote this scheme as unitary precoded integer-forcing
(UPIF). We show that UPIF can achieve full-diversity under a constraint based
on the shortest vector of a lattice generated by the precoding matrix . This constraint and a simpler version of that provide design criteria for
two types of full-diversity UPIF. Type I uses a unitary precoder that adapts at
each channel realization. Type II uses a unitary precoder, which remains fixed
for all channel realizations. We then verify our results by computer
simulations in , and MIMO using different QAM
constellations. We finally show that the proposed Type II UPIF outperform the
MIMO precoding X-codes at high data rates.Comment: 12 pages, 8 figures, to appear in IEEE-TW
Asymmetric Compute-and-Forward with CSIT
We present a modified compute-and-forward scheme which utilizes Channel State
Information at the Transmitters (CSIT) in a natural way. The modified scheme
allows different users to have different coding rates, and use CSIT to achieve
larger rate region. This idea is applicable to all systems which use the
compute-and-forward technique and can be arbitrarily better than the regular
scheme in some settings.Comment: in International Zurich Seminar on Communications, 2014; minor update
on example
Robust Successive Compute-and-Forward over Multi-User Multi-Relay Networks
This paper develops efficient Compute-and-forward (CMF) schemes in multi-user
multi-relay networks. To solve the rank failure problem in CMF setups and to
achieve full diversity of the network, we introduce two novel CMF methods,
namely, extended CMF and successive CMF. The former, having low complexity, is
based on recovering multiple equations at relays. The latter utilizes
successive interference cancellation (SIC) to enhance the system performance
compared to the state-of-the-art schemes. Both methods can be utilized in a
network with different number of users, relays, and relay antennas, with
negligible feedback channels or signaling overhead. We derive new concise
formulations and explicit framework for the successive CMF method as well as an
approach to reduce its computational complexity. Our theoretical analysis and
computer simulations demonstrate the superior performance of our proposed CMF
methods over the conventional schemes. Furthermore, based on our simulation
results, the successive CMF method yields additional signal-to-noise ratio
gains and shows considerable robustness against channel estimation error,
compared to the extended CMF method.Comment: 44 pages, 10 figures, 1 table, accepted to be published in IEEE
Trans. on Vehicular Tec
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