27 research outputs found
Achievable Rate and Optimal Physical Layer Rate Allocation in Interference-Free Wireless Networks
We analyze the achievable rate in interference-free wireless networks with
physical layer fading channels and orthogonal multiple access. As a starting
point, the point-to-point channel is considered. We find the optimal physical
and network layer rate trade-off which maximizes the achievable overall rate
for both a fixed rate transmission scheme and an improved scheme based on
multiple virtual users and superposition coding. These initial results are
extended to the network setting, where, based on a cut-set formulation, the
achievable rate at each node and its upper bound are derived. We propose a
distributed optimization algorithm which allows to jointly determine the
maximum achievable rate, the optimal physical layer rates on each network link,
and an opportunistic back-pressure-type routing strategy on the network layer.
This inherently justifies the layered architecture in existing wireless
networks. Finally, we show that the proposed layered optimization approach can
achieve almost all of the ergodic network capacity in high SNR.Comment: 5 pages, to appear in Proc. IEEE ISIT, July 200
Slepian-Wolf Coding Over Cooperative Relay Networks
This paper deals with the problem of multicasting a set of discrete
memoryless correlated sources (DMCS) over a cooperative relay network.
Necessary conditions with cut-set interpretation are presented. A \emph{Joint
source-Wyner-Ziv encoding/sliding window decoding} scheme is proposed, in which
decoding at each receiver is done with respect to an ordered partition of other
nodes. For each ordered partition a set of feasibility constraints is derived.
Then, utilizing the sub-modular property of the entropy function and a novel
geometrical approach, the results of different ordered partitions are
consolidated, which lead to sufficient conditions for our problem. The proposed
scheme achieves operational separation between source coding and channel
coding. It is shown that sufficient conditions are indeed necessary conditions
in two special cooperative networks, namely, Aref network and finite-field
deterministic network. Also, in Gaussian cooperative networks, it is shown that
reliable transmission of all DMCS whose Slepian-Wolf region intersects the
cut-set bound region within a constant number of bits, is feasible. In
particular, all results of the paper are specialized to obtain an achievable
rate region for cooperative relay networks which includes relay networks and
two-way relay networks.Comment: IEEE Transactions on Information Theory, accepte
Self-concatenated code design and its application in power-efficient cooperative communications
In this tutorial, we have focused on the design of binary self-concatenated coding schemes with the help of EXtrinsic Information Transfer (EXIT) charts and Union bound analysis. The design methodology of future iteratively decoded self-concatenated aided cooperative communication schemes is presented. In doing so, we will identify the most important milestones in the area of channel coding, concatenated coding schemes and cooperative communication systems till date and suggest future research directions
Achievable rates for relay networks using superposition coding
We investigate the superposition strategy and its usefulness in terms of achievable information theoretic rates. The achievable rate of the superposition of block Markov encoding (decode-forward) and side information encoding (compress-forward) for the three-node Gaussian relay channel is analyzed. It is generally believed that superposition can out perform decode-forward or compress-forward due to its generality. We prove that within the class of Gaussian distributions, this is not the case: the superposition scheme only achieves a rate that is equal to the maximum of the rates achieved by decode-forward or compress-forward individually.
We use the insight gathered on superposition forward scheme and devise a new coding scheme. The superposition coding scheme for communication over a network, combines partial decode-forward with noisy network coding. This hybrid scheme is termed as superposition noisy network coding. The novel coding scheme is designed and analyzed for a single relay channel, single source multicast network and multiple source multicast network. The special cases of Gaussian single relay channel and two way relay channel are analyzed for superposition noisy network coding. The achievable rate of the proposed scheme is higher than the existing schemes of noisy network coding, compress-forward and binning
Wireless Network Information Flow: A Deterministic Approach
In a wireless network with a single source and a single destination and an
arbitrary number of relay nodes, what is the maximum rate of information flow
achievable? We make progress on this long standing problem through a two-step
approach. First we propose a deterministic channel model which captures the key
wireless properties of signal strength, broadcast and superposition. We obtain
an exact characterization of the capacity of a network with nodes connected by
such deterministic channels. This result is a natural generalization of the
celebrated max-flow min-cut theorem for wired networks. Second, we use the
insights obtained from the deterministic analysis to design a new
quantize-map-and-forward scheme for Gaussian networks. In this scheme, each
relay quantizes the received signal at the noise level and maps it to a random
Gaussian codeword for forwarding, and the final destination decodes the
source's message based on the received signal. We show that, in contrast to
existing schemes, this scheme can achieve the cut-set upper bound to within a
gap which is independent of the channel parameters. In the case of the relay
channel with a single relay as well as the two-relay Gaussian diamond network,
the gap is 1 bit/s/Hz. Moreover, the scheme is universal in the sense that the
relays need no knowledge of the values of the channel parameters to
(approximately) achieve the rate supportable by the network. We also present
extensions of the results to multicast networks, half-duplex networks and
ergodic networks.Comment: To appear in IEEE transactions on Information Theory, Vol 57, No 4,
April 201