1,473 research outputs found
On the Multiple Access Channel with Asymmetric Noisy State Information at the Encoders
We consider the problem of reliable communication over multiple-access
channels (MAC) where the channel is driven by an independent and identically
distributed state process and the encoders and the decoder are provided with
various degrees of asymmetric noisy channel state information (CSI). For the
case where the encoders observe causal, asymmetric noisy CSI and the decoder
observes complete CSI, we provide inner and outer bounds to the capacity
region, which are tight for the sum-rate capacity. We then observe that, under
a Markov assumption, similar capacity results also hold in the case where the
receiver observes noisy CSI. Furthermore, we provide a single letter
characterization for the capacity region when the CSI at the encoders are
asymmetric deterministic functions of the CSI at the decoder and the encoders
have non-causal noisy CSI (its causal version is recently solved in
\cite{como-yuksel}). When the encoders observe asymmetric noisy CSI with
asymmetric delays and the decoder observes complete CSI, we provide a single
letter characterization for the capacity region. Finally, we consider a
cooperative scenario with common and private messages, with asymmetric noisy
CSI at the encoders and complete CSI at the decoder. We provide a single letter
expression for the capacity region for such channels. For the cooperative
scenario, we also note that as soon as the common message encoder does not have
access to CSI, then in any noisy setup, covering the cases where no CSI or
noisy CSI at the decoder, it is possible to obtain a single letter
characterization for the capacity region. The main component in these results
is a generalization of a converse coding approach, recently introduced in [1]
for the MAC with asymmetric quantized CSI at the encoders and herein
considerably extended and adapted for the noisy CSI setup.Comment: Submitted to the IEEE Transactions on Information Theor
On Cooperative Multiple Access Channels with Delayed CSI at Transmitters
We consider a cooperative two-user multiaccess channel in which the
transmission is controlled by a random state. Both encoders transmit a common
message and, one of the encoders also transmits an individual message. We study
the capacity region of this communication model for different degrees of
availability of the states at the encoders, causally or strictly causally. In
the case in which the states are revealed causally to both encoders but not to
the decoder we find an explicit characterization of the capacity region in the
discrete memoryless case. In the case in which the states are revealed only
strictly causally to both encoders, we establish inner and outer bounds on the
capacity region. The outer bound is non-trivial, and has a relatively simple
form. It has the advantage of incorporating only one auxiliary random variable.
We then introduce a class of cooperative multiaccess channels with states known
strictly causally at both encoders for which the inner and outer bounds agree;
and so we characterize the capacity region for this class. In this class of
channels, the state can be obtained as a deterministic function of the channel
inputs and output. We also study the model in which the states are revealed,
strictly causally, in an asymmetric manner, to only one encoder. Throughout the
paper, we discuss a number of examples; and compute the capacity region of some
of these examples. The results shed more light on the utility of delayed
channel state information for increasing the capacity region of state-dependent
cooperative multiaccess channels; and tie with recent progress in this
framework.Comment: 54 pages. To appear in IEEE Transactions on Information Theory. arXiv
admin note: substantial text overlap with arXiv:1201.327
Integer-Forcing Source Coding
Integer-Forcing (IF) is a new framework, based on compute-and-forward, for
decoding multiple integer linear combinations from the output of a Gaussian
multiple-input multiple-output channel. This work applies the IF approach to
arrive at a new low-complexity scheme, IF source coding, for distributed lossy
compression of correlated Gaussian sources under a minimum mean squared error
distortion measure. All encoders use the same nested lattice codebook. Each
encoder quantizes its observation using the fine lattice as a quantizer and
reduces the result modulo the coarse lattice, which plays the role of binning.
Rather than directly recovering the individual quantized signals, the decoder
first recovers a full-rank set of judiciously chosen integer linear
combinations of the quantized signals, and then inverts it. In general, the
linear combinations have smaller average powers than the original signals. This
allows to increase the density of the coarse lattice, which in turn translates
to smaller compression rates. We also propose and analyze a one-shot version of
IF source coding, that is simple enough to potentially lead to a new design
principle for analog-to-digital converters that can exploit spatial
correlations between the sampled signals.Comment: Submitted to IEEE Transactions on Information Theor
Multiaccess Channels with State Known to Some Encoders and Independent Messages
We consider a state-dependent multiaccess channel (MAC) with state
non-causally known to some encoders. We derive an inner bound for the capacity
region in the general discrete memoryless case and specialize to a binary
noiseless case. In the case of maximum entropy channel state, we obtain the
capacity region for binary noiseless MAC with one informed encoder by deriving
a non-trivial outer bound for this case. For a Gaussian state-dependent MAC
with one encoder being informed of the channel state, we present an inner bound
by applying a slightly generalized dirty paper coding (GDPC) at the informed
encoder that allows for partial state cancellation, and a trivial outer bound
by providing channel state to the decoder also. The uninformed encoders benefit
from the state cancellation in terms of achievable rates, however, appears that
GDPC cannot completely eliminate the effect of the channel state on the
achievable rate region, in contrast to the case of all encoders being informed.
In the case of infinite state variance, we analyze how the uninformed encoder
benefits from the informed encoder's actions using the inner bound and also
provide a non-trivial outer bound for this case which is better than the
trivial outer bound.Comment: Accepted to EURASIP Journal on Wireless Communication and Networking,
Feb. 200
Distributed Joint Source-Channel Coding in Wireless Sensor Networks
Considering the fact that sensors are energy-limited and the wireless channel conditions in wireless sensor networks, there is an urgent need for a low-complexity coding method with high compression ratio and noise-resisted features. This paper reviews the progress made in distributed joint source-channel coding which can address this issue. The main existing deployments, from the theory to practice, of distributed joint source-channel coding over the independent channels, the multiple access channels and the broadcast channels are introduced, respectively. To this end, we also present a practical scheme for compressing multiple correlated sources over the independent channels. The simulation results demonstrate the desired efficiency
- …