5,684 research outputs found
Multilevel Coding Schemes for Compute-and-Forward with Flexible Decoding
We consider the design of coding schemes for the wireless two-way relaying
channel when there is no channel state information at the transmitter. In the
spirit of the compute and forward paradigm, we present a multilevel coding
scheme that permits computation (or, decoding) of a class of functions at the
relay. The function to be computed (or, decoded) is then chosen depending on
the channel realization. We define such a class of functions which can be
decoded at the relay using the proposed coding scheme and derive rates that are
universally achievable over a set of channel gains when this class of functions
is used at the relay. We develop our framework with general modulation formats
in mind, but numerical results are presented for the case where each node
transmits using the QPSK constellation. Numerical results with QPSK show that
the flexibility afforded by our proposed scheme results in substantially higher
rates than those achievable by always using a fixed function or by adapting the
function at the relay but coding over GF(4).Comment: This paper was submitted to IEEE Transactions on Information Theory
in July 2011. A shorter version also appeared in the proceedings of the
International Symposium on Information Theory in August 2011 without the
proof of the main theore
Coding for Relay Networks with Parallel Gaussian Channels
A wireless relay network consists of multiple source nodes, multiple destination nodes, and possibly many relay nodes in between to facilitate its transmission. It is clear that the performance of such networks highly depends on information for- warding strategies adopted at the relay nodes. This dissertation studies a particular information forwarding strategy called compute-and-forward. Compute-and-forward is a novel paradigm that tries to incorporate the idea of network coding within the physical layer and hence is often referred to as physical layer network coding. The main idea is to exploit the superposition nature of the wireless medium to directly compute or decode functions of transmitted signals at intermediate relays in a net- work. Thus, the coding performed at the physical layer serves the purpose of error correction as well as permits recovery of functions of transmitted signals.
For the bidirectional relaying problem with Gaussian channels, it has been shown by Wilson et al. and Nam et al. that the compute-and-forward paradigm is asymptotically optimal and achieves the capacity region to within 1 bit; however, similar results beyond the memoryless case are still lacking. This is mainly because channels with memory would destroy the lattice structure that is most crucial for the compute-and-forward paradigm. Hence, how to extend compute-and-forward to such channels has been a challenging issue. This motivates this study of the extension of compute-and-forward to channels with memory, such as inter-symbol interference.
The bidirectional relaying problem with parallel Gaussian channels is also studied, which is a relevant model for the Gaussian bidirectional channel with inter-symbol interference and that with multiple-input multiple-output channels. Motivated by the recent success of linear finite-field deterministic model, we first investigate the corresponding deterministic parallel bidirectional relay channel and fully characterize its capacity region. Two compute-and-forward schemes are then proposed for the Gaussian model and the capacity region is approximately characterized to within a constant gap.
The design of coding schemes for the compute-and-forward paradigm with low decoding complexity is then considered. Based on the separation-based framework proposed previously by Tunali et al., this study proposes a family of constellations that are suitable for the compute-and-forward paradigm. Moreover, by using Chinese remainder theorem, it is shown that the proposed constellations are isomorphic to product fields and therefore can be put into a multilevel coding framework. This study then proposes multilevel coding for the proposed constellations and uses multistage decoding to further reduce decoding complexity
Coding for Relay Networks with Parallel Gaussian Channels
A wireless relay network consists of multiple source nodes, multiple destination nodes, and possibly many relay nodes in between to facilitate its transmission. It is clear that the performance of such networks highly depends on information for- warding strategies adopted at the relay nodes. This dissertation studies a particular information forwarding strategy called compute-and-forward. Compute-and-forward is a novel paradigm that tries to incorporate the idea of network coding within the physical layer and hence is often referred to as physical layer network coding. The main idea is to exploit the superposition nature of the wireless medium to directly compute or decode functions of transmitted signals at intermediate relays in a net- work. Thus, the coding performed at the physical layer serves the purpose of error correction as well as permits recovery of functions of transmitted signals.
For the bidirectional relaying problem with Gaussian channels, it has been shown by Wilson et al. and Nam et al. that the compute-and-forward paradigm is asymptotically optimal and achieves the capacity region to within 1 bit; however, similar results beyond the memoryless case are still lacking. This is mainly because channels with memory would destroy the lattice structure that is most crucial for the compute-and-forward paradigm. Hence, how to extend compute-and-forward to such channels has been a challenging issue. This motivates this study of the extension of compute-and-forward to channels with memory, such as inter-symbol interference.
The bidirectional relaying problem with parallel Gaussian channels is also studied, which is a relevant model for the Gaussian bidirectional channel with inter-symbol interference and that with multiple-input multiple-output channels. Motivated by the recent success of linear finite-field deterministic model, we first investigate the corresponding deterministic parallel bidirectional relay channel and fully characterize its capacity region. Two compute-and-forward schemes are then proposed for the Gaussian model and the capacity region is approximately characterized to within a constant gap.
The design of coding schemes for the compute-and-forward paradigm with low decoding complexity is then considered. Based on the separation-based framework proposed previously by Tunali et al., this study proposes a family of constellations that are suitable for the compute-and-forward paradigm. Moreover, by using Chinese remainder theorem, it is shown that the proposed constellations are isomorphic to product fields and therefore can be put into a multilevel coding framework. This study then proposes multilevel coding for the proposed constellations and uses multistage decoding to further reduce decoding complexity
Lattices from Codes for Harnessing Interference: An Overview and Generalizations
In this paper, using compute-and-forward as an example, we provide an
overview of constructions of lattices from codes that possess the right
algebraic structures for harnessing interference. This includes Construction A,
Construction D, and Construction (previously called product
construction) recently proposed by the authors. We then discuss two
generalizations where the first one is a general construction of lattices named
Construction subsuming the above three constructions as special cases
and the second one is to go beyond principal ideal domains and build lattices
over algebraic integers
Space-Time Coded Spatial Modulated Physical Layer Network Coding for Two-Way Relaying
Using the spatial modulation approach, where only one transmit antenna is
active at a time, we propose two transmission schemes for two-way relay channel
using physical layer network coding with space time coding using Coordinate
Interleaved Orthogonal Designs (CIOD's). It is shown that using two
uncorrelated transmit antennas at the nodes, but using only one RF transmit
chain and space-time coding across these antennas can give a better performance
without using any extra resources and without increasing the hardware
implementation cost and complexity. In the first transmission scheme, two
antennas are used only at the relay, Adaptive Network Coding (ANC) is employed
at the relay and the relay transmits a CIOD Space Time Block Code (STBC). This
gives a better performance compared to an existing ANC scheme for two-way relay
channel which uses one antenna each at all the three nodes. It is shown that
for this scheme at high SNR the average end-to-end symbol error probability
(SEP) is upper bounded by twice the SEP of a point-to-point fading channel. In
the second transmission scheme, two transmit antennas are used at all the three
nodes, CIOD STBC's are transmitted in multiple access and broadcast phases.
This scheme provides a diversity order of two for the average end-to-end SEP
with an increased decoding complexity of for an arbitrary
signal set and for square QAM signal set.Comment: 9 pages, 7 figure
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
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