200 research outputs found

### Cooperative Transmission for a Vector Gaussian Parallel Relay Network

In this paper, we consider a parallel relay network where two relays
cooperatively help a source transmit to a destination. We assume the source and
the destination nodes are equipped with multiple antennas. Three basic schemes
and their achievable rates are studied: Decode-and-Forward (DF),
Amplify-and-Forward (AF), and Compress-and-Forward (CF). For the DF scheme, the
source transmits two private signals, one for each relay, where dirty paper
coding (DPC) is used between the two private streams, and a common signal for
both relays. The relays make efficient use of the common information to
introduce a proper amount of correlation in the transmission to the
destination. We show that the DF scheme achieves the capacity under certain
conditions. We also show that the CF scheme is asymptotically optimal in the
high relay power limit, regardless of channel ranks. It turns out that the AF
scheme also achieves the asymptotic optimality but only when the
relays-to-destination channel is full rank. The relative advantages of the
three schemes are discussed with numerical results.Comment: 35 pages, 10 figures, submitted to IEEE Transactions on Information
Theor

### The Capacity of Wireless Channels: A Physical Approach

In this paper, the capacity of wireless channels is characterized based on
electromagnetic and antenna theories with only minimal assumptions. We assume
the transmitter can generate an arbitrary current distribution inside a
spherical region and the receive antennas are uniformly distributed on a bigger
sphere surrounding the transmitter. The capacity is shown to be $(\alpha P/N_0)
\log e$ [bits/sec] in the limit of large number of receive antennas, where $P$
is the transmit power constraint, $\alpha$ is the normalized density of the
receive antennas and $N_0$ is the noise power spectral density. Although this
result may look trivial, it is surprising in two ways. First, this result holds
regardless of the bandwidth (bandwidth can even be negligibly small). Second,
this result shows that the capacity is irrespective of the size of the region
containing the transmitter. This is against some previous results that claimed
the maximum degrees of freedom is proportional to the surface area containing
the transmitter normalized by the square of the wavelength. Our result has
important practical implications since it shows that even a compact antenna
array with negligible bandwidth and antenna spacing well below the wavelength
can provide a huge throughput as if the array was big enough so that the
antenna spacing is on the order of the wavelength.Comment: 5 pages, to appear in proceedings of 2013 IEEE ISI

### A Unified Approach for Network Information Theory

In this paper, we take a unified approach for network information theory and
prove a coding theorem, which can recover most of the achievability results in
network information theory that are based on random coding. The final
single-letter expression has a very simple form, which was made possible by
many novel elements such as a unified framework that represents various network
problems in a simple and unified way, a unified coding strategy that consists
of a few basic ingredients but can emulate many known coding techniques if
needed, and new proof techniques beyond the use of standard covering and
packing lemmas. For example, in our framework, sources, channels, states and
side information are treated in a unified way and various constraints such as
cost and distortion constraints are unified as a single joint-typicality
constraint.
Our theorem can be useful in proving many new achievability results easily
and in some cases gives simpler rate expressions than those obtained using
conventional approaches. Furthermore, our unified coding can strictly
outperform existing schemes. For example, we obtain a generalized
decode-compress-amplify-and-forward bound as a simple corollary of our main
theorem and show it strictly outperforms previously known coding schemes. Using
our unified framework, we formally define and characterize three types of
network duality based on channel input-output reversal and network flow
reversal combined with packing-covering duality.Comment: 52 pages, 7 figures, submitted to IEEE Transactions on Information
theory, a shorter version will appear in Proc. IEEE ISIT 201

### Noisy Network Coding with Partial DF

In this paper, we propose a noisy network coding integrated with partial
decode-and-forward relaying for single-source multicast discrete memoryless
networks (DMN's). Our coding scheme generalizes the
partial-decode-compress-and-forward scheme (Theorem 7) by Cover and El Gamal.
This is the first time the theorem is generalized for DMN's such that each
relay performs both partial decode-and-forward and compress-and-forward
simultaneously. Our coding scheme simultaneously generalizes both noisy network
coding by Lim, Kim, El Gamal, and Chung and distributed decode-and-forward by
Lim, Kim, and Kim. It is not trivial to combine the two schemes because of
inherent incompatibility in their encoding and decoding strategies. We solve
this problem by sending the same long message over multiple blocks at the
source and at the same time by letting the source find the auxiliary covering
indices that carry information about the message simultaneously over all
blocks.Comment: 5 pages, 1 figure, to appear in Proc. IEEE ISIT 201

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