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.

MIMO-THP System with Imperfect CSI

Abstract: In recent years, it was realized that designing wireless digital communication systems to more efficiently exploit the spatial domain of the transmission medium, allows for a significant increase of spectral efficiency. These systems, in general case, are known as Multiple Input Multiple Output (MIMO) systems and have received considerable attention of researchers and commercial companies due to their potential to dramatically increase the spectral efficiency and simultaneously sending individual information to the corresponding users in wireless systems. In MIMO channels, the information theoretical results show that the desired throughput can be achieved by using the so called Dirty Paper Coding (DPC) method which employs at the transmitter side. However, due to the computational complexity, this method is not practically used until yet. Tomlinson Harashima Precoding (THP) is a suboptimal method which can achieve the near sum-rate of such channels with much simpler complexity as compared to the optimum DPC approach. In spite of THP's good performance, it is very sensitive to erroneous Channel State Information (CSI). When the CSI at the transmitter is imperfect, the system suffers from performance degradation. In current chapter, the design of THP in an imperfect CSI scenario is considered for a MIMO-BC (BroadCast) system. At first, the maximum achievable rate of MIMO-THP system in an imperfect CSI is computed by means of information theory concepts. Moreover, a lower bound for capacity loss and optimum as well as suboptimum solutions for power allocation is derived. This bound can be useful in practical system design in an imperfect CSI case. In order to increase the THP performance in an imperfect CSI, a robust optimization technique is developed for THP based on Minimum Mean Square Error (MMSE) criterion. This robust optimization has more performance than the conventional optimization method. Then, the above optimization is developed for time varying channels and based on this knowledge we design a robust precoder for fast time varying channels. The designed precoder has good performance over correlated MIMO channels in which, the volume of its feed back can be reduced significantly. Traditionally, channel estimation and pre-equalization are optimized separately and independently. In this chapter, a new robust solution is derived for MIMO THP system, which optimizes jointly the channel estimation and THP filters. The proposed method provides significant improvement with respect to conventional optimization with less increase in complexity.

(Non)-Coherent MU-MIMO Block Fading Channels With Finite Blocklength and Linear Processing

Abstract: Driven by the stringent demands of future ultra reliable and low latency communication (URLLC), we provide a comprehensive study for a coherent and non-coherent multiuser multiple-input multiple-output (MU-MIMO) uplink system in the finite blocklength regime. The independent and identically distributed (i.i.d.) Gaussian codebook is assumed for each user. To be more specific, the base station (BS) first uses two popular linear processing schemes to combine the signals transmitted from all users, namely maximum-ratio combining (MRC) and zero-forcing (ZF). Following it, the matched maximum-likelihood (ML) and mismatched nearest-neighbour (NN) decoding metric for the coherent and non-coherent cases are respectively employed at the BS. Under these conditions, the refined third-order achievable coding rate, expressed as a function of the blocklength, average error probability, and the third-order term of the information density (called as the channel perturbation), is derived. With this result in hand, a detailed performance analysis is then pursued, through which, we derive the asymptotic results of the channel perturbation, achievable coding rate, channel capacity, and the channel dispersion. These theoretical results enable us to obtain a number of interesting insights related to the impact of the finite blocklength: i) in our system setting, massive MIMO helps to reduce the channel perturbation of the achievable coding rate, which can even be discarded without affecting the performance with just a small-to-moderate number of BS antennas and number of blocks; ii) under the non-coherent case, even with massive MIMO, the channel estimation errors cannot be eliminated unless the transmit powers in both the channel estimation and data transmission phases for each user are made inversely proportional to the square root of the number of BS antennas; iii) in the non-coherent case and for fixed total blocklength, the scenarios with longer coherence intervals and smaller number of blocks will offer higher achievable coding rate.

Capacity Achieving by Diagonal Permutation for MU-MIMO channels

Abstract: Dirty Paper Coding (DPC) is considered as the optimal precoding which achieves capacity for the Gaussian Multiple-Input Multiple-Output (MIMO) broadcast channel (BC). However, to find the optimal precoding order, it needs to repeat N! times for N users as there are N! possible precoding orders. This extremely high complexity limits its practical use in modern wireless networks. In this paper, we show the equivalence of DPC and the recently proposed Higher Order Mercer's Theorem (HOGMT) precoding[1][2] in 2-D (spatial) case, which provides an alternate implementation for DPC. Furthermore, we show that the proposed implementation method is linear over the permutation operator when permuting over multi-user channels. Therefore, we present a low complexity algorithm that optimizes the precoding order for DPC with beamforming, eliminating repeated computation of DPC for each precoding order. Simulations show that our method can achieve the same result as conventional DPC with about 20 dB lower complexity for N = 5 users.

A Comparison of Broadcast Strategy in MIMO Relay Networks

Abstract: In this paper, the sum rate issue of a multiple-input multiple-output (MIMO) relay broadcast channel is studied, where the fixed relay station is used to support multiuser transmission in a downlink channel With appropriate design, the sum rate can be expressed as a function of the processing units at the base station (BS) and relay, and the power allocation can be converted to a standard convex problem We compared the sum rate of MIMO relay broadcast channel (BC) using time division multiple access (TDMA) to the strongest user, dirty paper coding (DPC) and beamforming (BF) when multiple antennas are deployed at each terminal in the system and separate power constraints at the BS and relay Then, the sum rate bounds for each strategy and the sum capacity (achieved by DPC) gain over TDMA and BF are given, correspondingly Finally, numerical results are presented to prove our discussions With these results, we can easily obtain how far away TDMA and BF are from being optimal in terms of sum rate, and direct the practical system design

Biorthogonal matrix dirty paper coding for information hiding in still images

Abstract: In this paper, a new method of dirty paper code design is investigated, namely the biorthogonal matrix. The error probability is analysed for the code design. Since the code has the maximum dmm, the robustness of this code is optimal. However, due to the limited availability of the codewords, the performance is restricted. Simulation results shown in this paper identify this restriction and solutions are discussed. Superior coding and binning methods are derived from the in-depth analysis of the simulation results.