343 research outputs found
Degraded Broadcast Diamond Channels with Non-Causal State Information at the Source
A state-dependent degraded broadcast diamond channel is studied where the
source-to-relays cut is modeled with two noiseless, finite-capacity digital
links with a degraded broadcasting structure, while the relays-to-destination
cut is a general multiple access channel controlled by a random state. It is
assumed that the source has non-causal channel state information and the relays
have no state information. Under this model, first, the capacity is
characterized for the case where the destination has state information, i.e.,
has access to the state sequence. It is demonstrated that in this case, a joint
message and state transmission scheme via binning is optimal. Next, the case
where the destination does not have state information, i.e., the case with
state information at the source only, is considered. For this scenario, lower
and upper bounds on the capacity are derived for the general discrete
memoryless model. Achievable rates are then computed for the case in which the
relays-to-destination cut is affected by an additive Gaussian state. Numerical
results are provided that illuminate the performance advantages that can be
accrued by leveraging non-causal state information at the source.Comment: Submitted to IEEE Transactions on Information Theory, Feb. 201
A Novel Power Allocation Scheme for Two-User GMAC with Finite Input Constellations
Constellation Constrained (CC) capacity regions of two-user Gaussian Multiple
Access Channels (GMAC) have been recently reported, wherein an appropriate
angle of rotation between the constellations of the two users is shown to
enlarge the CC capacity region. We refer to such a scheme as the Constellation
Rotation (CR) scheme. In this paper, we propose a novel scheme called the
Constellation Power Allocation (CPA) scheme, wherein the instantaneous transmit
power of the two users are varied by maintaining their average power
constraints. We show that the CPA scheme offers CC sum capacities equal (at low
SNR values) or close (at high SNR values) to those offered by the CR scheme
with reduced decoding complexity for QAM constellations. We study the
robustness of the CPA scheme for random phase offsets in the channel and
unequal average power constraints for the two users. With random phase offsets
in the channel, we show that the CC sum capacity offered by the CPA scheme is
more than the CR scheme at high SNR values. With unequal average power
constraints, we show that the CPA scheme provides maximum gain when the power
levels are close, and the advantage diminishes with the increase in the power
difference.Comment: To appear in IEEE Transactions on Wireless Communications, 10 pages
and 7 figure
A digital interface for Gaussian relay and interference networks: Lifting codes from the discrete superposition model
For every Gaussian network, there exists a corresponding deterministic
network called the discrete superposition network. We show that this discrete
superposition network provides a near-optimal digital interface for operating a
class consisting of many Gaussian networks in the sense that any code for the
discrete superposition network can be naturally lifted to a corresponding code
for the Gaussian network, while achieving a rate that is no more than a
constant number of bits lesser than the rate it achieves for the discrete
superposition network. This constant depends only on the number of nodes in the
network and not on the channel gains or SNR. Moreover the capacities of the two
networks are within a constant of each other, again independent of channel
gains and SNR. We show that the class of Gaussian networks for which this
interface property holds includes relay networks with a single
source-destination pair, interference networks, multicast networks, and the
counterparts of these networks with multiple transmit and receive antennas.
The code for the Gaussian relay network can be obtained from any code for the
discrete superposition network simply by pruning it. This lifting scheme
establishes that the superposition model can indeed potentially serve as a
strong surrogate for designing codes for Gaussian relay networks.
We present similar results for the K x K Gaussian interference network, MIMO
Gaussian interference networks, MIMO Gaussian relay networks, and multicast
networks, with the constant gap depending additionally on the number of
antennas in case of MIMO networks.Comment: Final versio
Finite-Blocklength and Error-Exponent Analyses for LDPC Codes in Point-to-Point and Multiple Access Communication
This paper applies error-exponent and dispersionstyle analyses to derive finite-blocklength achievability bounds for low-density parity-check (LDPC) codes over the point-to-point channel (PPC) and multiple access channel (MAC). The errorexponent analysis applies Gallager’s error exponent to bound achievable symmetrical and asymmetrical rates in the MAC. The dispersion-style analysis begins with a generalization of the random coding union (RCU) bound from random code ensembles with i.i.d. codewords to random code ensembles in which codewords may be statistically dependent; this generalization is useful since the codewords of random linear codes such as LDPC codes are dependent. Application of the RCU bound yields finiteblocklength error bounds and asymptotic achievability results for both i.i.d. random codes and LDPC codes. For discrete, memoryless channels, these results show that LDPC codes achieve first- and second-order performance that is optimal for the PPC and identical to the best prior results for the MAC
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