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.

Approximate Sum-Capacity of K-user Cognitive Interference Channels with Cumulative Message Sharing

Abstract: This paper considers the K user cognitive interference channel with one primary and K-1 secondary/cognitive transmitters with a cumulative message sharing structure, i.e cognitive transmitter $i\in [2:K]$ knows non-causally all messages of the users with index less than i. We propose a computable outer bound valid for any memoryless channel. We first evaluate the sum-rate outer bound for the high- SNR linear deterministic approximation of the Gaussian noise channel. This is shown to be capacity for the 3-user channel with arbitrary channel gains and the sum-capacity for the symmetric K-user channel. Interestingly. for the K user channel having only the K th cognitive know all the other messages is sufficient to achieve capacity i.e cognition at transmitter 2 to K-1 is not needed. Next the sum capacity of the symmetric Gaussian noise channel is characterized to within a constant additive and multiplicative gap. The proposed achievable scheme for the additive gap is based on Dirty paper coding and can be thought of as a MIMO-broadcast scheme where only one encoding order is possible due to the message sharing structure. As opposed to other multiuser interference channel models, a single scheme suffices for both the weak and strong interference regimes. With this scheme the generalized degrees of freedom (gDOF) is shown to be a function of K, in contrast to the non cognitive case and the broadcast channel case. Interestingly, it is show that as the number of users grows to infinity the gDoF of the K-user cognitive interference channel with cumulative message sharing tends to the gDoF of a broadcast channel with a K-antenna transmitter and K single-antenna receivers. The analytical additive additive and multiplicative gaps are a function of the number of users. Numerical evaluations of inner and outer bounds show that the actual gap is less than the analytical one.

Extended Uniform Channel Decomposition for MIMO Communications with Intersymbol Interference

Abstract: In this paper, a joint design of a unitary pre-coder and a decision feedback equalizer (DFE) is considered to decompose a multi-input multi-output (MIMO) intersymbol interference (ISI) channel into multiple scalar layers with identical mean square errors (MSEs), and consequently, achieve much improved error probability performance over the standard DFE without a precoder This design represents an extension of the existing uniform channel decomposition (UCD) scheme for frequency-flat MIMO channels Therefore, it is named extended UCD (EUCD) In contrast to the trivial extension of the UCD scheme which uses the orthogonal frequency division multiplexing (OFDM) to obtain multiple frequency flat channels and applies the standard UCD to each of them, the EUCD scheme uses a MIMO minimum-mean square error decision feedback equalizer (MMSE-DFE) to eliminate ISI and only needs one precoder for the entire broadband To eliminate error propagation, another form of the EUCD is also presented which uses the dirty paper coding (DPC) to cancel ISI at the transmitter The practical implementation aspect is also considered An example via numerical simulation validates the remarkable performance of the EUCD in terms of uncoded error probability

Maximum Weighted Sum Rate of Multi-Antenna Broadcast Channels

Abstract: Recently, researchers showed that dirty paper coding (DPC) is the optimal transmission strategy for multiple-input multiple-output broadcast channels (MIMO-BC). In this paper, we study how to determine the maximum weighted sum of DPC rates through solving the maximum weighted sum rate problem of the dual MIMO multiple access channel (MIMO-MAC) with a sum power constraint. We first simplify the maximum weighted sum rate problem such that enumerating all possible decoding orders in the dual MIMO-MAC is unnecessary. We then design an efficient algorithm based on conjugate gradient projection (CGP) to solve the maximum weighted sum rate problem. Our proposed CGP method utilizes the powerful concept of Hessian conjugacy. We also develop a rigorous algorithm to solve the projection problem. We show that CGP enjoys provable convergence, nice scalability, and great efficiency for large MIMO-BC systems.

Efficient linear successive allocation for the MIMO broadcast channel

Abstract: To avoid the complexity of nearly optimum implementations for dirty paper coding (DPC) linear zero-forcing approaches are often preferred. Finding the optimum user allocation, transmit and receive filters for maximizing sum rate in the multiple-input multiple-output (MIMO) broadcast channel constitutes a non-convex combinatorial optimization problem. Here we present an efficient linear zero-forcing algorithm for this problem, which is derived from maximizing a lower bound for the sum rate. It successively allocates data streams to users and in contrast to state of the art approaches thereby also determines the corresponding receive filters. Compared to existing approaches drastic complexity reductions can be achieved even with slight performance gains.

A simple linear multiuser precoding technique in cellular relay networks

Abstract: In this paper, we propose a simple linear multiuser precoding scheme for downlink cellular systems with a decode- and forward (DF) based relay, where the available information at a base station (BS) and a relay station (RS) is asymmetric. The proposed scheme not only eliminates the interference from a RS for the mobile station (MS) served by a BS but also provides the MS supported by a RS with a macro diversity gain without any information exchange between a BS and a RS. Consequently, the proposed scheme outperforms a conventional scheme and approaches an ideal scheme using dirty paper coding (DPC) in the information asymmetric configuration.