Writing on Dirty Paper with Resizing and its Application to Quasi-Static Fading Broadcast Channels

This paper studies a variant of the classical problem of ``writing on dirty paper'' in which the sum of the input and the interference, or dirt, is multiplied by a random variable that models resizing, known to the decoder but not to the encoder. The achievable rate of Costa's dirty paper coding (DPC) scheme is calculated and compared to the case of the decoder's also knowing the dirt. In the ergodic case, the corresponding rate loss vanishes asymptotically in the limits of both high and low signal-to-noise ratio (SNR), and is small at all finite SNR for typical distributions like Rayleigh, Rician, and Nakagami. In the quasi-static case, the DPC scheme is lossless at all SNR in terms of outage probability. Quasi-static fading broadcast channels (BC) without transmit channel state information (CSI) are investigated as an application of the robustness properties. It is shown that the DPC scheme leads to an outage achievable rate region that strictly dominates that of time division.Comment: To appear in IEEE International Symposium on Information Theory 200

Dirty Paper Arbitrarily Varying Channel with a State-Aware Adversary

In this paper, we take an arbitrarily varying channel (AVC) approach to examine the problem of writing on a dirty paper in the presence of an adversary. We consider an additive white Gaussian noise (AWGN) channel with an additive white Gaussian state, where the state is known non-causally to the encoder and the adversary, but not the decoder. We determine the randomized coding capacity of this AVC under the maximal probability of error criterion. Interestingly, it is shown that the jamming adversary disregards the state knowledge to choose a white Gaussian channel input which is independent of the state

On Capacity of the Dirty Paper Channel with Fading Dirt in the Strong Fading Regime

The classical writing on dirty paper capacity result establishes that full interference pre-cancellation can be attained in Gelfand-Pinsker problem with additive state and additive white Gaussian noise. This result holds under the idealized assumption that perfect channel knowledge is available at both transmitter and receiver. While channel knowledge at the receiver can be obtained through pilot tones, transmitter channel knowledge is harder to acquire. For this reason, we are interested in characterizing the capacity under the more realistic assumption that only partial channel knowledge is available at the transmitter. We study, more specifically, the dirty paper channel in which the interference sequence in multiplied by fading value unknown to the transmitter but known at the receiver. For this model, we establish an approximate characterization of capacity for the case in which fading values vary greatly in between channel realizations. In this regime, which we term the strong fading regime, the capacity pre-log factor is equal to the inverse of the number of possible fading realizations