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Capacity bounds via duality with applications to multipleantenna systems on flatfading channels
 IEEE Trans. Inform. Theory
, 2003
"... A general technique is proposed for the derivation of upper bounds on channel capacity. The technique is based on a dual expression for channel capacity where the maximization (of mutual information) over distributions on the channel input alphabet is replaced with a minimization (of average relativ ..."
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Cited by 147 (39 self)
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A general technique is proposed for the derivation of upper bounds on channel capacity. The technique is based on a dual expression for channel capacity where the maximization (of mutual information) over distributions on the channel input alphabet is replaced with a minimization (of average relative entropy) over distributions on the channel output alphabet. Every choice of an output distribution — even if not the channel image of some input distribution — leads to an upper bound on mutual information. The proposed approach is used in order to study multiantenna flat fading channels with memory where the realization of the fading process is unknown at the transmitter and unknown (or only partially known) at the receiver. It is demonstrated that, for high signaltonoise ratio (SNR), the capacity of such channels typically grows only doublelogarithmically in the SNR. This is in stark contrast to the case with perfect receiver side information where capacity grows logarithmically in the SNR. To better understand this phenomenon
The fading number of singleinput multipleoutput fading channels with memory
 IEEE Transactions on Information Theory
, 2006
"... We derive the fading number of stationary and ergodic (not necessarily Gaussian) singleinput multipleoutput (SIMO) fading channels with memory. This is the second term, after the double logarithmic term, of the high signaltonoise ratio (SNR) expansion of channel capacity. The transmitter and rec ..."
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Cited by 19 (6 self)
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We derive the fading number of stationary and ergodic (not necessarily Gaussian) singleinput multipleoutput (SIMO) fading channels with memory. This is the second term, after the double logarithmic term, of the high signaltonoise ratio (SNR) expansion of channel capacity. The transmitter and receiver are assumed to be cognizant of the probability law governing the fading but not of its realization. It is demonstrated that the fading number is achieved by IID circularly symmetric inputs of squaredmagnitude whose logarithm is uniformly distributed over an SNR dependent interval. The upper limit of the interval is the logarithm of the allowed transmit power, and the lower limit tends to infinity sublogarithmically in the SNR. The converse relies inter alia on a new observation regarding input distributions that escape to infinity. Lower and upper bounds on the fading number for Gaussian fading are also presented. These are related to the mean squarederrors of the onestep predictor and the onegap interpolator of the fading process respectively. The bounds are computed explicitly for stationary mth order autoregressive AR(m) Gaussian fading processes.
Capacity Analysis of MultipleAccess OFDM Channels Final Report of Project “4G Wireless Access Technology”
, 2006
"... The demand of new wireless communication systems with much higher data rates that allow, e.g., mobile wireless broadband Internet connections inspires a quick advance in wireless transmission technology. So far most systems rely on an approach where the channel state is measured with the help of reg ..."
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The demand of new wireless communication systems with much higher data rates that allow, e.g., mobile wireless broadband Internet connections inspires a quick advance in wireless transmission technology. So far most systems rely on an approach where the channel state is measured with the help of regularly transmitted training sequences. The detection of the transmitted data is then done under the assumption of perfect knowledge of the channel state. This approach will not be sufficient anymore for very high data rate systems since the loss of bandwidth due to the training sequences is too large. Therefore, the research interest on joint estimation and detection schemes has been increased considerably. Apart from potentially higher data rates a further advantage of such a system is that it allows for a fair analysis of the theoretical upper limit, the socalled channel capacity. “Fair ” is used here in the sense that the capacity analysis does not ignore the estimation part of the system, i.e., it takes into account the need of the receiver to gain some knowledge about the channel state without restricting it to assume some particular form (particularly, this approach does also include the approach