389 research outputs found
Asymptotically optimal cooperative wireless networks with reduced signaling complexity
This paper considers an orthogonal amplify-and-forward (OAF) protocol for cooperative relay communication over Rayleigh-fading channels in which the intermediate relays are permitted to linearly transform the received signal and where the source and relays transmit for equal time durations. The diversity-multiplexing gain (D-MG) tradeoff of the equivalent space-time channel associated to this protocol is determined and a cyclic-division-algebra-based D-MG optimal code constructed. The transmission or signaling alphabet of this code is the union of the QAM constellation and a rotated version of QAM. The size of this signaling alphabet is small in comparison with prior D-MG optimal constructions in the literature and is independent of the number of participating nodes in the network
Distributed Beamforming in Wireless Multiuser Relay-Interference Networks with Quantized Feedback
We study quantized beamforming in wireless amplify-and-forward
relay-interference networks with any number of transmitters, relays, and
receivers. We design the quantizer of the channel state information to minimize
the probability that at least one receiver incorrectly decodes its desired
symbol(s). Correspondingly, we introduce a generalized diversity measure that
encapsulates the conventional one as the first-order diversity. Additionally,
it incorporates the second-order diversity, which is concerned with the
transmitter power dependent logarithmic terms that appear in the error rate
expression. First, we show that, regardless of the quantizer and the amount of
feedback that is used, the relay-interference network suffers a second-order
diversity loss compared to interference-free networks. Then, two different
quantization schemes are studied: First, using a global quantizer, we show that
a simple relay selection scheme can achieve maximal diversity. Then, using the
localization method, we construct both fixed-length and variable-length local
(distributed) quantizers (fLQs and vLQs). Our fLQs achieve maximal first-order
diversity, whereas our vLQs achieve maximal diversity. Moreover, we show that
all the promised diversity and array gains can be obtained with arbitrarily low
feedback rates when the transmitter powers are sufficiently large. Finally, we
confirm our analytical findings through simulations.Comment: 41 pages, 14 figures, submitted to IEEE Transactions on Information
Theory, July 2010. This work was presented in part at IEEE Global
Communications Conference (GLOBECOM), Nov. 200
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
Reliable Physical Layer Network Coding
When two or more users in a wireless network transmit simultaneously, their
electromagnetic signals are linearly superimposed on the channel. As a result,
a receiver that is interested in one of these signals sees the others as
unwanted interference. This property of the wireless medium is typically viewed
as a hindrance to reliable communication over a network. However, using a
recently developed coding strategy, interference can in fact be harnessed for
network coding. In a wired network, (linear) network coding refers to each
intermediate node taking its received packets, computing a linear combination
over a finite field, and forwarding the outcome towards the destinations. Then,
given an appropriate set of linear combinations, a destination can solve for
its desired packets. For certain topologies, this strategy can attain
significantly higher throughputs over routing-based strategies. Reliable
physical layer network coding takes this idea one step further: using
judiciously chosen linear error-correcting codes, intermediate nodes in a
wireless network can directly recover linear combinations of the packets from
the observed noisy superpositions of transmitted signals. Starting with some
simple examples, this survey explores the core ideas behind this new technique
and the possibilities it offers for communication over interference-limited
wireless networks.Comment: 19 pages, 14 figures, survey paper to appear in Proceedings of the
IEE
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