Dirty paper coding

About: Dirty paper coding is a research topic. Over the lifetime, 814 publications have been published within this topic receiving 37097 citations.

Energy-efficient rate balancing in vector broadcast channels with linear transceivers

Abstract: We consider the minimization of the energy per bit (or, equivalently, the maximization of the energy efficiency) in a multiple-input single-output (MISO) broadcast channel with rate balancing constraints, ie, in a multiuser system where certain fixed ratios between the rates of the various users have to be kept This paper deals with the practically relevant case where the transmit strategy is restricted to simple linear filtering without time-sharing, ie, sophisticated coding schemes such as dirty paper coding (DPC) are not allowed Even though the arising optimization problem is non-convex, it can be solved with reasonable complexity in a globally optimal manner using the algorithm proposed in this paper This globally optimal solution enables us to study the impact of rate balancing constraints on the energy efficiency of a vector broadcast channel in numerical simulations

A Proposal of DPC Beamforming for Open Loop Multiuser MIMO Transmissions

Abstract: This paper proposes an open loop beamforming scheme in frequency division duplex (FDD) downlink multiuser multiple input multiple output (MIMO) transmissions. The proposed scheme estimates the downlink channel matrix by uplink direction of arrival (DOA) estimation, and generates the beamforming weight such that the effect of overlapping beams is cancelled at the respective receivers by applying the dirty paper coding principle. The simulation results show that the proposed scheme provides a gain up to 20 dB in the received signal to noise plus interference ratio (SINR) at the 50 % CDF compared to the conventional zero-forcing beamforming. In addition, it is shown that the proposed scheme has a superior performance to the limited feedback closed loop scheme.

Robust estimation of amplitude modification for scalar costa scheme based audio watermark detection

Abstract: Recently, informed watermarking schemes based on Costa's dirty paper coding are drawing more attention than spread spectrum based techniques because these kinds of watermarking algorithms do not need an original host signal for watermark detection and the host signal does not affect the performance of watermark detection. For practical implementation, they mostly use uniform scalar quantizers, which are very vulnerable against amplitude modification. Hence, it is necessary to estimate the amplitude modification, i.e., a modified quantization step size, before watermark detection. In this paper, we propose a robust algorithm to estimate the modified quantization step size with an optimal search interval. It searches the quantization step size to minimize the quantization error of the received audio signal. It does not encroach the space for embedding watermark message because it just uses the received signal itself for estimation of the quantization step size. The optimal searching interval is determined to satisfy both detection performance and computational complexity. Experimental results show that the proposed algorithm can estimate the modified quantization step size accurately under amplitude modification attacks.

On the capacity of partially cognitive radios

Abstract: This paper considers the problem of cognitive radios with partial message information. Here, an interference channel setting is considered where one transmitter (the “cognitive” one) knows the message of the other (“legitimate” user) partially. An outer bound on the capacity region of this channel is found for the “weak” interference case (where the interference from the cognitive transmitter to the legitimate receiver is weak). This outer bound is shown for both the discrete-memoryless and the Gaussian channel cases. An achievable region is subsequently determined for a Gaussian partially cognitive-radio channel. The achievable strategy described in this paper is a combination of superposition and dirty paper coding.

Performance of adaptive precoding for wireless MIMO broadcast channels with limited feedback

Abstract: The capacity region of multiple-input multiple- output (MIMO) broadcast channel (BC) has attracted consider- able attention recently. The greedy block MMSE QR decompo- sition with dirty paper coding (greedy block MMSE-DP) scheme is a solution to achieves extremely close to channel capacity with limited feedback of channel state information at transmitter (CSIT). In this paper, we analysis the performance and consider the reconfigurable implementation of greedy block MMSE-DP. Numerical results indicate that the greedy block MMSE-DP approach significantly outperforms the TDMA-MIMO approach in terms of the system throughput even when a large amount of quantization error is added to the feedback information (e.g., when signal-to-quantization-error ratio (SER) values are 14, 10, and 6 dB). The scheme is shown to be appropriate for reconfigurable implementation.