3,105 research outputs found
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
The Approximate Capacity of the MIMO Relay Channel
Capacity bounds are studied for the multiple-antenna complex Gaussian relay
channel with t1 transmitting antennas at the sender, r2 receiving and t2
transmitting antennas at the relay, and r3 receiving antennas at the receiver.
It is shown that the partial decode-forward coding scheme achieves within
min(t1,r2) bits from the cutset bound and at least one half of the cutset
bound, establishing a good approximate expression of the capacity. A similar
additive gap of min(t1 + t2, r3) + r2 bits is shown to be achieved by the
compress-forward coding scheme.Comment: 8 pages, 5 figures, submitted to the IEEE Transactions on Information
Theor
On Capacity and Optimal Scheduling for the Half-Duplex Multiple-Relay Channel
We study the half-duplex multiple-relay channel (HD-MRC) where every node can
either transmit or listen but cannot do both at the same time. We obtain a
capacity upper bound based on a max-flow min-cut argument and achievable
transmission rates based on the decode-forward (DF) coding strategy, for both
the discrete memoryless HD-MRC and the phase-fading HD-MRC. We discover that
both the upper bound and the achievable rates are functions of the
transmit/listen state (a description of which nodes transmit and which
receive). More precisely, they are functions of the time fraction of the
different states, which we term a schedule. We formulate the optimal scheduling
problem to find an optimal schedule that maximizes the DF rate. The optimal
scheduling problem turns out to be a maximin optimization, for which we propose
an algorithmic solution. We demonstrate our approach on a four-node
multiple-relay channel, obtaining closed-form solutions in certain scenarios.
Furthermore, we show that for the received signal-to-noise ratio degraded
phase-fading HD-MRC, the optimal scheduling problem can be simplified to a max
optimization.Comment: Author's final version (to appear in IEEE Transactions on Information
Theory
On the Achievable Rates of Multihop Virtual Full-Duplex Relay Channels
We study a multihop "virtual" full-duplex relay channel as a special case of
a general multiple multicast relay network. For such channel,
quantize-map-and-forward (QMF) (or noisy network coding (NNC)) achieves the
cut-set upper bound within a constant gap where the gap grows {\em linearly}
with the number of relay stages . However, this gap may not be negligible
for the systems with multihop transmissions (i.e., a wireless backhaul
operating at higher frequencies). We have recently attained an improved result
to the capacity scaling where the gap grows {\em logarithmically} as ,
by using an optimal quantization at relays and by exploiting relays' messages
(decoded in the previous time slot) as side-information. In this paper, we
further improve the performance of this network by presenting a mixed scheme
where each relay can perform either decode-and-forward (DF) or QMF with
possibly rate-splitting. We derive the achievable rate and show that the
proposed scheme outperforms the QMF-optimized scheme. Furthermore, we
demonstrate that this performance improvement increases with .Comment: To be presented at ISIT 201
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
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