5,936 research outputs found
End-to-End Joint Antenna Selection Strategy and Distributed Compress and Forward Strategy for Relay Channels
Multi-hop relay channels use multiple relay stages, each with multiple relay
nodes, to facilitate communication between a source and destination.
Previously, distributed space-time codes were proposed to maximize the
achievable diversity-multiplexing tradeoff, however, they fail to achieve all
the points of the optimal diversity-multiplexing tradeoff. In the presence of a
low-rate feedback link from the destination to each relay stage and the source,
this paper proposes an end-to-end antenna selection (EEAS) strategy as an
alternative to distributed space-time codes. The EEAS strategy uses a subset of
antennas of each relay stage for transmission of the source signal to the
destination with amplify and forwarding at each relay stage. The subsets are
chosen such that they maximize the end-to-end mutual information at the
destination. The EEAS strategy achieves the corner points of the optimal
diversity-multiplexing tradeoff (corresponding to maximum diversity gain and
maximum multiplexing gain) and achieves better diversity gain at intermediate
values of multiplexing gain, versus the best known distributed space-time
coding strategies. A distributed compress and forward (CF) strategy is also
proposed to achieve all points of the optimal diversity-multiplexing tradeoff
for a two-hop relay channel with multiple relay nodes.Comment: Accepted for publication in the special issue on cooperative
communication in the Eurasip Journal on Wireless Communication and Networkin
Cooperative Compute-and-Forward
We examine the benefits of user cooperation under compute-and-forward. Much
like in network coding, receivers in a compute-and-forward network recover
finite-field linear combinations of transmitters' messages. Recovery is enabled
by linear codes: transmitters map messages to a linear codebook, and receivers
attempt to decode the incoming superposition of signals to an integer
combination of codewords. However, the achievable computation rates are low if
channel gains do not correspond to a suitable linear combination. In response
to this challenge, we propose a cooperative approach to compute-and-forward. We
devise a lattice-coding approach to block Markov encoding with which we
construct a decode-and-forward style computation strategy. Transmitters
broadcast lattice codewords, decode each other's messages, and then
cooperatively transmit resolution information to aid receivers in decoding the
integer combinations. Using our strategy, we show that cooperation offers a
significant improvement both in the achievable computation rate and in the
diversity-multiplexing tradeoff.Comment: submitted to IEEE Transactions on Information Theor
Multi-Antenna Cooperative Wireless Systems: A Diversity-Multiplexing Tradeoff Perspective
We consider a general multiple antenna network with multiple sources,
multiple destinations and multiple relays in terms of the
diversity-multiplexing tradeoff (DMT). We examine several subcases of this most
general problem taking into account the processing capability of the relays
(half-duplex or full-duplex), and the network geometry (clustered or
non-clustered). We first study the multiple antenna relay channel with a
full-duplex relay to understand the effect of increased degrees of freedom in
the direct link. We find DMT upper bounds and investigate the achievable
performance of decode-and-forward (DF), and compress-and-forward (CF)
protocols. Our results suggest that while DF is DMT optimal when all terminals
have one antenna each, it may not maintain its good performance when the
degrees of freedom in the direct link is increased, whereas CF continues to
perform optimally. We also study the multiple antenna relay channel with a
half-duplex relay. We show that the half-duplex DMT behavior can significantly
be different from the full-duplex case. We find that CF is DMT optimal for
half-duplex relaying as well, and is the first protocol known to achieve the
half-duplex relay DMT. We next study the multiple-access relay channel (MARC)
DMT. Finally, we investigate a system with a single source-destination pair and
multiple relays, each node with a single antenna, and show that even under the
idealistic assumption of full-duplex relays and a clustered network, this
virtual multi-input multi-output (MIMO) system can never fully mimic a real
MIMO DMT. For cooperative systems with multiple sources and multiple
destinations the same limitation remains to be in effect.Comment: version 1: 58 pages, 15 figures, Submitted to IEEE Transactions on
Information Theory, version 2: Final version, to appear IEEE IT, title
changed, extra figures adde
Adaptive Randomized Distributed Space-Time Coding in Cooperative MIMO Relay Systems
An adaptive randomized distributed space-time coding (DSTC) scheme and
algorithms are proposed for two-hop cooperative MIMO networks. Linear minimum
mean square error (MMSE) receivers and an amplify-and-forward (AF) cooperation
strategy are considered. In the proposed DSTC scheme, a randomized matrix
obtained by a feedback channel is employed to transform the space-time coded
matrix at the relay node. Linear MMSE expressions are devised to compute the
parameters of the adaptive randomized matrix and the linear receive filter. A
stochastic gradient algorithm is also developed to compute the parameters of
the adaptive randomized matrix with reduced computational complexity. We also
derive the upper bound of the error probability of a cooperative MIMO system
employing the randomized space-time coding scheme first. The simulation results
show that the proposed algorithms obtain significant performance gains as
compared to existing DSTC schemes.Comment: 4 figure
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