1,060 research outputs found
Capacity Theorems for the AWGN Multi-Way Relay Channel
The L-user additive white Gaussian noise multi-way relay channel is
considered, where multiple users exchange information through a single relay at
a common rate. Existing coding strategies, i.e., complete-decode-forward and
compress-forward are shown to be bounded away from the cut-set upper bound at
high signal-to-noise ratios (SNR). It is known that the gap between the
compress-forward rate and the capacity upper bound is a constant at high SNR,
and that between the complete-decode-forward rate and the upper bound increases
with SNR at high SNR. In this paper, a functional-decode-forward coding
strategy is proposed. It is shown that for L >= 3, complete-decode-forward
achieves the capacity when SNR <= 0 dB, and functional-decode-forward achieves
the capacity when SNR >= 0 dB. For L=$, functional-decode-forward achieves the
capacity asymptotically as SNR increases.Comment: accepted and to be presented at ISIT 201
Functional-Decode-Forward for the General Discrete Memoryless Two-Way Relay Channel
We consider the general discrete memoryless two-way relay channel, where two
users exchange messages via a relay, and propose two functional-decode-forward
coding strategies for this channel. Functional-decode-forward involves the
relay decoding a function of the users' messages rather than the individual
messages themselves. This function is then broadcast back to the users, which
can be used in conjunction with the user's own message to decode the other
user's message. Via a numerical example, we show that functional-decode-forward
with linear codes is capable of achieving strictly larger sum rates than those
achievable by other strategies
Optimal Coding Functions for Pairwise Message Sharing on Finite-Field Multi-Way Relay Channels
This paper considers the finite-field multi-way relay channel with pairwise
message sharing, where multiple users exchange messages through a single relay
and where the users may share parts of their source messages (meaning that some
message parts are known/common to more than one user). In this paper, we design
an optimal functional-decode-forward coding scheme that takes the shared
messages into account. More specifically, we design an optimal function for the
relay to decode (from the users on the uplink) and forward (back to the users
on the downlink). We then show that this proposed function-decode-forward
coding scheme can achieve the capacity region of the finite-field multi-way
relay channel with pairwise message sharing. This paper generalizes our
previous result for the case of three users to any number of users.Comment: Author's final version (accepted for presentation at the 2014 IEEE
International Conference on Communications [ICC 2014]
The Binary-Symmetric Parallel-Relay Network
We present capacity results of the binary-symmetric parallel-relay network,
where there is one source, one destination, and K relays in parallel. We show
that forwarding relays, where the relays merely transmit their received
signals, achieve the capacity in two ways: with coded transmission at the
source and a finite number of relays, or uncoded transmission at the source and
a sufficiently large number of relays. On the other hand, decoding relays,
where the relays decode the source message, re-encode, and forward it to the
destination, achieve the capacity when the number of relays is small.Comment: accepted and to be presented at ISIT 201
On Achievable Rate Regions of the Asymmetric AWGN Two-Way Relay Channel
This paper investigates the additive white Gaussian noise two-way relay
channel, where two users exchange messages through a relay. Asymmetrical
channels are considered where the users can transmit data at different rates
and at different power levels. We modify and improve existing coding schemes to
obtain three new achievable rate regions. Comparing four downlink-optimal
coding schemes, we show that the scheme that gives the best sum-rate
performance is (i) complete-decode-forward, when both users transmit at low
signal-to-noise ratio (SNR); (ii) functional-decode-forward with nested lattice
codes, when both users transmit at high SNR; (iii) functional-decode-forward
with rate splitting and time-division multiplexing, when one user transmits at
low SNR and another user at medium--high SNR.Comment: to be presented at ISIT 201
The Three-User Finite-Field Multi-Way Relay Channel with Correlated Sources
This paper studies the three-user finite-field multi-way relay channel, where
the users exchange messages via a relay. The messages are arbitrarily
correlated, and the finite-field channel is linear and is subject to additive
noise of arbitrary distribution. The problem is to determine the minimum
achievable source-channel rate, defined as channel uses per source symbol
needed for reliable communication. We combine Slepian-Wolf source coding and
functional-decode-forward channel coding to obtain the solution for two classes
of source and channel combinations. Furthermore, for correlated sources that
have their common information equal their mutual information, we propose a new
coding scheme to achieve the minimum source-channel rate.Comment: Author's final version (accepted and to appear in IEEE Transactions
on Communications
The Finite Field Multi-Way Relay Channel with Correlated Sources: The Three-User Case
The three-user finite field multi-way relay channel with correlated sources
is considered. The three users generate possibly correlated messages, and each
user is to transmit its message to the two other users reliably in the Shannon
sense. As there is no direct link among the users, communication is carried out
via a relay, and the link from the users to the relay and those from the relay
to the users are finite field adder channels with additive noise of arbitrary
distribution. The problem is to determine the set of all possible achievable
rates, defined as channel uses per source symbol for reliable communication.
For two classes of source/channel combinations, the solution is obtained using
Slepian-Wolf source coding combined with functional-decode-forward channel
coding.Comment: to be presented at ISIT 201
An Intelligent Empowering Agent (IEA) to Provide Easily Understood and Trusted Health Information Appropriate to the User Needs
Most members of the public, including patients, usually obtain health information from Web searches using generic search engines, which is often overwhelming, too generic, and of poor quality. Although patients may be better informed, they are often none the wiser and not empowered to communicate with medical professionals so that their care is compatible with their needs, values, and best interests. Intelligent Empowering Agents (IEA) use AI to filter medical information and assist the user in the understanding of health information about specific complaints or health in general. We have designed and developed a prototype of an IEA that dialogues with the user in simple language, collects health information from the Web, and provides tailored, easily understood, and trusted information. It empowers users to create their own comprehensive and objective opinion on health matters that concern them. This paper describes the IEA main characteristics and presents the results of subjective and objective tests carried out to assess the effectiveness of the IEA
The Half-Duplex AWGN Single-Relay Channel: Full Decoding or Partial Decoding?
This paper compares the partial-decode-forward and the
complete-decode-forward coding strategies for the half-duplex Gaussian
single-relay channel. We analytically show that the rate achievable by
partial-decode-forward outperforms that of the more straightforward
complete-decode-forward by at most 12.5%. Furthermore, in the following
asymptotic cases, the gap between the partial-decode-forward and the
complete-decode-forward rates diminishes: (i) when the relay is close to the
source, (ii) when the relay is close to the destination, and (iii) when the SNR
is low. In addition, when the SNR increases, this gap, when normalized to the
complete-decode-forward rate, also diminishes. Consequently, significant
performance improvements are not achieved by optimizing the fraction of data
the relay should decode and forward, over simply decoding the entire source
message.Comment: Authors' final version (to appear in IEEE Transactions on
Communications
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