164 research outputs found
Multiple Access Channels with Combined Cooperation and Partial Cribbing
In this paper we study the multiple access channel (MAC) with combined
cooperation and partial cribbing and characterize its capacity region.
Cooperation means that the two encoders send a message to one another via a
rate-limited link prior to transmission, while partial cribbing means that each
of the two encoders obtains a deterministic function of the other encoder's
output with or without delay. Prior work in this field dealt separately with
cooperation and partial cribbing. However, by combining these two methods we
can achieve significantly higher rates. Remarkably, the capacity region does
not require an additional auxiliary random variable (RV) since the purpose of
both cooperation and partial cribbing is to generate a common message between
the encoders. In the proof we combine methods of block Markov coding, backward
decoding, double rate-splitting, and joint typicality decoding. Furthermore, we
present the Gaussian MAC with combined one-sided cooperation and quantized
cribbing. For this model, we give an achievability scheme that shows how many
cooperation or quantization bits are required in order to achieve a Gaussian
MAC with full cooperation/cribbing capacity region. After establishing our main
results, we consider two cases where only one auxiliary RV is needed. The first
is a rate distortion dual setting for the MAC with a common message, a private
message and combined cooperation and cribbing. The second is a state-dependent
MAC with cooperation, where the state is known at a partially cribbing encoder
and at the decoder. However, there are cases where more than one auxiliary RV
is needed, e.g., when the cooperation and cribbing are not used for the same
purposes. We present a MAC with an action-dependent state, where the action is
based on the cooperation but not on the cribbing. Therefore, in this case more
than one auxiliary RV is needed
Cooperative Binning for Semi-deterministic Channels with Non-causal State Information
The capacity of the semi-deterministic relay channel (SD-RC) with non-causal
channel state information (CSI) only at the encoder and decoder is
characterized. The capacity is achieved by a scheme based on
cooperative-bin-forward. This scheme allows cooperation between the transmitter
and the relay without the need to decode a part of the message by the relay.
The transmission is divided into blocks and each deterministic output of the
channel (observed by the relay) is mapped to a bin. The bin index is used by
the encoder and the relay to choose the cooperation codeword in the next
transmission block. In causal settings the cooperation is independent of the
state. In \emph{non-causal} settings dependency between the relay's
transmission and the state can increase the transmission rates. The encoder
implicitly conveys partial state information to the relay. In particular, it
uses the states of the next block and selects a cooperation codeword
accordingly and the relay transmission depends on the cooperation codeword and
therefore also on the states. We also consider the multiple access channel with
partial cribbing as a semi-deterministic channel. The capacity region of this
channel with non-causal CSI is achieved by the new scheme. Examining the result
in several cases, we introduce a new problem of a point-to-point (PTP) channel
where the state is provided to the transmitter by a state encoder.
Interestingly, even though the CSI is also available at the receiver, we
provide an example which shows that the capacity with non-causal CSI at the
state encoder is strictly larger than the capacity with causal CSI
Multi-Antenna Cooperative Wireless Systems: A Diversity-Multiplexing Tradeoff Perspective
We consider a general multiple antenna network with multiple sources,
multiple destinations and multiple relays in terms of the
diversity-multiplexing tradeoff (DMT). We examine several subcases of this most
general problem taking into account the processing capability of the relays
(half-duplex or full-duplex), and the network geometry (clustered or
non-clustered). We first study the multiple antenna relay channel with a
full-duplex relay to understand the effect of increased degrees of freedom in
the direct link. We find DMT upper bounds and investigate the achievable
performance of decode-and-forward (DF), and compress-and-forward (CF)
protocols. Our results suggest that while DF is DMT optimal when all terminals
have one antenna each, it may not maintain its good performance when the
degrees of freedom in the direct link is increased, whereas CF continues to
perform optimally. We also study the multiple antenna relay channel with a
half-duplex relay. We show that the half-duplex DMT behavior can significantly
be different from the full-duplex case. We find that CF is DMT optimal for
half-duplex relaying as well, and is the first protocol known to achieve the
half-duplex relay DMT. We next study the multiple-access relay channel (MARC)
DMT. Finally, we investigate a system with a single source-destination pair and
multiple relays, each node with a single antenna, and show that even under the
idealistic assumption of full-duplex relays and a clustered network, this
virtual multi-input multi-output (MIMO) system can never fully mimic a real
MIMO DMT. For cooperative systems with multiple sources and multiple
destinations the same limitation remains to be in effect.Comment: version 1: 58 pages, 15 figures, Submitted to IEEE Transactions on
Information Theory, version 2: Final version, to appear IEEE IT, title
changed, extra figures adde
Bounds on the Capacity of the Relay Channel with Noncausal State at Source
We consider a three-terminal state-dependent relay channel with the channel
state available non-causally at only the source. Such a model may be of
interest for node cooperation in the framework of cognition, i.e.,
collaborative signal transmission involving cognitive and non-cognitive radios.
We study the capacity of this communication model. One principal problem is
caused by the relay's not knowing the channel state. For the discrete
memoryless (DM) model, we establish two lower bounds and an upper bound on
channel capacity. The first lower bound is obtained by a coding scheme in which
the source describes the state of the channel to the relay and destination,
which then exploit the gained description for a better communication of the
source's information message. The coding scheme for the second lower bound
remedies the relay's not knowing the states of the channel by first computing,
at the source, the appropriate input that the relay would send had the relay
known the states of the channel, and then transmitting this appropriate input
to the relay. The relay simply guesses the sent input and sends it in the next
block. The upper bound is non trivial and it accounts for not knowing the state
at the relay and destination. For the general Gaussian model, we derive lower
bounds on the channel capacity by exploiting ideas in the spirit of those we
use for the DM model; and we show that these bounds are optimal for small and
large noise at the relay irrespective to the strength of the interference.
Furthermore, we also consider a special case model in which the source input
has two components one of which is independent of the state. We establish a
better upper bound for both DM and Gaussian cases and we also characterize the
capacity in a number of special cases.Comment: Submitted to the IEEE Transactions on Information Theory, 54 pages, 6
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