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.

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

Abstract: 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.

Beam Selection Strategies for Orthogonal Random Beamforming in Sparse Networks

Abstract: Orthogonal random beamforming (ORB) constitutes a mean to exploit spatial multiplexing and multi-user diversity (MUD) gains in multi-antenna broadcast channels. To do so, as many random beamformers as transmit antennas (M) are generated and on each beam the user experiencing the most favorable channel conditions is scheduled. Whereas for a large number of users the sum-rate of ORB exhibits an identical growth rate as that of dirty paper coding, performance in sparse networks (or in networks with an uneven spatial distribution of users) is known to be severely impaired. To circumvent that, in this paper we modify the scheduling process in ORB in order to select a subset out of the M available beams. We propose several beam selection algorithms and assess their performance in terms of sum-rate and aggregated throughput (i.e., rate achieved with practical modulation and coding schemes), along with an analysis of their computational complexity. Since ORB schemes require partial channel state information (CSI) to be fed back to the transmitter, we finally investigate the impact of CSI quantization on system performance. More specifically, we prove that most of the MUD can be still exploited with very few quantization bits and we derive a beam selection approach trading-off system performance vs. feedback channel requirements.

Downlink MIMO Systems Using Cooperation Among Base Stations in a Slow Fading Channel

Abstract: To increase the achievable sum rate of downlink MIMO (Multiple Input Multiple Output) systems, the cooperation among Base Stations (BS) is investigated in a slow fading channel. Three levels of BS coordination are considered: full coordination, partial coordination, and no coordination. This paper assumes that the downlink MIMO channel state information (CSI) is sent to the corresponding BS through a feedback link with some delay. In a fully coordinated system, the CSI at each BS needs to be collected at the central coordinator, and this process may result in significant additional delay. In this paper, the achievable throughput of each coordination level is evaluated and compared including the effects of the delay in CSI. A quasi-static fading is considered where the channel is static within one codeword, but it gradually changes over time based on the well-known Jake's model. Also, dirty paper coding (DPC) is applied, which is a transmission method shown to achieve the sum capacity of MIMO broadcast channels (BC). The results show that under certain delay conditions, the partially-coordinated system outperforms the fully-coordinated system. In addition, this paper presents a new partial-coordination method that provides higher throughput than the conventional partial-coordinated system.

On Maximum Eigenmode Beamforming and Multi-User Gain

Abstract: This paper is concerned with the advantages of multi-user concurrent transmission in multiple-input multiple-output (MIMO) systems with rate constraints. We first study a maximum eigenmode beamforming (MEB) strategy for fading multiple access channels (MACs). This strategy allows each user to transmit only in its maximum eigenmode direction and applies a suboptimal matched-filter receiver with successive interference cancellation at the base station (BS). We derive a closed-form expression for the average minimum transmitted sum power required by MEB. Based on this, we show that: a) the MEB strategy is asymptotically optimal when the number of simultaneous users is sufficiently large; b) multi-user concurrent transmission has a power advantage, referred to as multi-user gain, over orthogonal transmission approaches such as time-division multiple-access; c) the number of antennas at the BS has a far stronger impact on the system performance than that at each user side. These properties are verified by simulation. Both numerical analyses and simulation results show that a major part of multi-user gain can be achieved in practical environments even with a quite small number of simultaneous users. We also study the MEB strategy for MIMO broadcast channels (BCs). The dirty paper coding (DPC) technique is necessary in this case. It is analytically shown that most observations made for MIMO MACs are extendable to MIMO BCs.