112 research outputs found
Filter and nested-lattice code design for fading MIMO channels with side-information
Linear-assignment Gel'fand-Pinsker coding (LA-GPC) is a coding technique for
channels with interference known only at the transmitter, where the known
interference is treated as side-information (SI). As a special case of LA-GPC,
dirty paper coding has been shown to be able to achieve the optimal
interference-free rate for interference channels with perfect channel state
information at the transmitter (CSIT). In the cases where only the channel
distribution information at the transmitter (CDIT) is available, LA-GPC also
has good (sometimes optimal) performance in a variety of fast and slow fading
SI channels. In this paper, we design the filters in nested-lattice based
coding to make it achieve the same rate performance as LA-GPC in multiple-input
multiple-output (MIMO) channels. Compared with the random Gaussian codebooks
used in previous works, our resultant coding schemes have an algebraic
structure and can be implemented in practical systems. A simulation in a
slow-fading channel is also provided, and near interference-free error
performance is obtained. The proposed coding schemes can serve as the
fundamental building blocks to achieve the promised rate performance of MIMO
Gaussian broadcast channels with CDIT or perfect CSITComment: submitted to IEEE Transactions on Communications, Feb, 200
On the Dirty Paper Channel with Fast Fading Dirt
Costa`s "writing on dirty paper" result establishes that full state
pre-cancellation can be attained in the Gel`fand-Pinsker problem with additive
state and additive white Gaussian noise. This result holds under the
assumptions that full channel knowledge is available at both the transmitter
and the receiver. In this work we consider the scenario in which the state is
multiplied by an ergodic fading process which is not known at the encoder. We
study both the case in which the receiver has knowledge of the fading and the
case in which it does not: for both models we derive inner and outer bounds to
capacity and determine the distance between the two bounds when possible. For
the channel without fading knowledge at either the transmitter or the receiver,
the gap between inner and outer bounds is finite for a class of fading
distributions which includes a number of canonical fading models. In the
capacity approaching strategy for this class, the transmitter performs Costa`s
pre-coding against the mean value of the fading times the state while the
receiver treats the remaining signal as noise. For the case in which only the
receiver has knowledge of the fading, we determine a finite gap between inner
and outer bounds for two classes of discrete fading distribution. The first
class of distributions is the one in which there exists a probability mass
larger than one half while the second class is the one in which the fading is
uniformly distributed over values that are exponentially spaced apart.
Unfortunately, the capacity in the case of a continuous fading distribution
remains very hard to characterize
Computation Alignment: Capacity Approximation without Noise Accumulation
Consider several source nodes communicating across a wireless network to a
destination node with the help of several layers of relay nodes. Recent work by
Avestimehr et al. has approximated the capacity of this network up to an
additive gap. The communication scheme achieving this capacity approximation is
based on compress-and-forward, resulting in noise accumulation as the messages
traverse the network. As a consequence, the approximation gap increases
linearly with the network depth.
This paper develops a computation alignment strategy that can approach the
capacity of a class of layered, time-varying wireless relay networks up to an
approximation gap that is independent of the network depth. This strategy is
based on the compute-and-forward framework, which enables relays to decode
deterministic functions of the transmitted messages. Alone, compute-and-forward
is insufficient to approach the capacity as it incurs a penalty for
approximating the wireless channel with complex-valued coefficients by a
channel with integer coefficients. Here, this penalty is circumvented by
carefully matching channel realizations across time slots to create
integer-valued effective channels that are well-suited to compute-and-forward.
Unlike prior constant gap results, the approximation gap obtained in this paper
also depends closely on the fading statistics, which are assumed to be i.i.d.
Rayleigh.Comment: 36 pages, to appear in IEEE Transactions on Information Theor
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