2,563 research outputs found
Compute-and-Forward: Harnessing Interference through Structured Codes
Interference is usually viewed as an obstacle to communication in wireless
networks. This paper proposes a new strategy, compute-and-forward, that
exploits interference to obtain significantly higher rates between users in a
network. The key idea is that relays should decode linear functions of
transmitted messages according to their observed channel coefficients rather
than ignoring the interference as noise. After decoding these linear equations,
the relays simply send them towards the destinations, which given enough
equations, can recover their desired messages. The underlying codes are based
on nested lattices whose algebraic structure ensures that integer combinations
of codewords can be decoded reliably. Encoders map messages from a finite field
to a lattice and decoders recover equations of lattice points which are then
mapped back to equations over the finite field. This scheme is applicable even
if the transmitters lack channel state information.Comment: IEEE Trans. Info Theory, to appear. 23 pages, 13 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
IEE
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
Nomographic Functions: Efficient Computation in Clustered Gaussian Sensor Networks
In this paper, a clustered wireless sensor network is considered that is
modeled as a set of coupled Gaussian multiple-access channels. The objective of
the network is not to reconstruct individual sensor readings at designated
fusion centers but rather to reliably compute some functions thereof. Our
particular attention is on real-valued functions that can be represented as a
post-processed sum of pre-processed sensor readings. Such functions are called
nomographic functions and their special structure permits the utilization of
the interference property of the Gaussian multiple-access channel to reliably
compute many linear and nonlinear functions at significantly higher rates than
those achievable with standard schemes that combat interference. Motivated by
this observation, a computation scheme is proposed that combines a suitable
data pre- and post-processing strategy with a nested lattice code designed to
protect the sum of pre-processed sensor readings against the channel noise.
After analyzing its computation rate performance, it is shown that at the cost
of a reduced rate, the scheme can be extended to compute every continuous
function of the sensor readings in a finite succession of steps, where in each
step a different nomographic function is computed. This demonstrates the
fundamental role of nomographic representations.Comment: to appear in IEEE Transactions on Wireless Communication
Weak Secrecy in the Multi-Way Untrusted Relay Channel with Compute-and-Forward
We investigate the problem of secure communications in a Gaussian multi-way
relay channel applying the compute-and-forward scheme using nested lattice
codes. All nodes employ half-duplex operation and can exchange confidential
messages only via an untrusted relay. The relay is assumed to be honest but
curious, i.e., an eavesdropper that conforms to the system rules and applies
the intended relaying scheme. We start with the general case of the
single-input multiple-output (SIMO) L-user multi-way relay channel and provide
an achievable secrecy rate region under a weak secrecy criterion. We show that
the securely achievable sum rate is equivalent to the difference between the
computation rate and the multiple access channel (MAC) capacity. Particularly,
we show that all nodes must encode their messages such that the common
computation rate tuple falls outside the MAC capacity region of the relay. We
provide results for the single-input single-output (SISO) and the
multiple-input single-input (MISO) L-user multi-way relay channel as well as
the two-way relay channel. We discuss these results and show the dependency
between channel realization and achievable secrecy rate. We further compare our
result to available results in the literature for different schemes and show
that the proposed scheme operates close to the compute-and-forward rate without
secrecy.Comment: submitted to JSAC Special Issue on Fundamental Approaches to Network
Coding in Wireless Communication System
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
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