The effect upon channel capacity in wireless communications of perfect and imperfect knowledge of the channel

By Muriel Médard. IEEE Transactions on Information Theory, 2000

1,001 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/c6bb8736bdac606793d46d6af494540c3984211a

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In Electrical and Electronic Engineering

Citations in the corpus

Channel Estimation and Performance Analysis of One-Bit Massive MIMO Systems (2016, positive): “We follow the approach of [46] and only exploit knowledge of the average effective channel E {√ ρdw k Adhk } in the detection.”
Great expectations: the value of spatial diversity in wireless networks (2004, background): “When the channel is slowly varying, the estimation error could be small since we can track the channel variations and the effect of such estimation errors was investigated in [184].”
Massive MIMO Systems With Non-Ideal Hardware: Energy Efficiency, Estimation, and Capacity Limits (2013, methodology): “the signal-to-noise ratio (SNR) but also on spatial correlation in the propagation environment [3], [4], channel estimation accuracy [5], transceiver hardware impairments [6], [7], and signal processing resources [8], [9].”
Fading Channels: Information-Theoretic and Communication Aspects (1998, methodology): “…procedures, which bear their own information-theoretic implications referring to the specific interpretation of the equalization method on one hand [16], [21], [58], [250], and the to information-theoretic role of the accuracy of the available channel parameters [185]–[186] on the other hand.”
How much training is needed in multiple-antenna wireless links? (2003, background): “A similar argument for lower-bounding the mutual information in a scalar multiple-access wireless channel is given in [9].”
Massive MIMO for Maximal Spectral Efficiency: How Many Users and Pilots Should Be Allocated? (2014, background): “The lemma follows from computing a lower bound on I(xlk, y j ), similar to [6], [7], [13], [25], [26], by making three limiting assumptions: 1) a Gaussian codebook is used; 2) the signal component received over the effective channel mean E{h}{gjkh j jk} is the only desired signal, while the interfer”
Capacity and power allocation for fading MIMO channels with channel estimation error (2006, background): “This approach is taken in [10], where the author derives a lower bound of mutual information with channel estimation error for single input single output (SISO) channels.”
Downlink scheduling and resource allocation for OFDM systems (2009, background): “We also note that (4) is shown in [22] to give an achievable lower bound on the capacity of this channel.”