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.

Capacity Analysis of MIMO Group-Broadcast Channels with Time-Division Scheduling

Abstract: This paper investigates the ergodic sum capacity for a MIMO group-broadcast channel with time-division scheduling (TDS) In this scheme, the overall user set is divided into subgroups, among which a single user subgroup which maximizes the instantaneous sum capacity will be scheduled at a time In order to characterize the TDS performance, we first derived an asymptotic bound to the full capacity obtained by dirty paper coding (DPC) This bound is a closed-form expression and performs well for different system configurations Further concerning practical precoding techniques, we studied its achievable sum capacity by using block-diagonalization (BD) and zero-forcing (ZF) precoding Based on these results, the achieved scheduling gain by TDS over random scheduling is analyzed We also compared the scheduling gains under different transmission strategies including DPC, BD, and ZF precoding The results reveal that TDS provides the largest scheduling gain for the system with ZF precoding Finally, we also discussed the effect of the group cardinality on the performance of TDS Numerical results show the tightness of derived capacity bounds and verify the correctness of our analysis

Millimetre Wave Massive MIMO Technology

Abstract: Multiple‐input, multiple‐output (MIMO) technology becomes increasingly matured and capable of providing reliable and high speed data and sum‐rate capacity provisions. This chapter presents an overview of the capacity analysis for a point‐to‐point MIMO link system. The MIMO technology offers the point‐to‐point link promising multiplexing gains. The chapter also presents dirty paper coding for massive MIMO systems. Massive MIMO system is a key enabler in 5G, since it not only provides large directivity gains but also reduces interference through beam shaping. Multiple access channel and broadcast channel reciprocity is a central issue in millimetre Wave (mmWave) massive MIMO system. The chapter then extends the single cell representation into multiuser MIMO multi‐cell systems. It examines possible types of beamforming (BF) schemes and discusses mmWave BF systems, including massive hybrid antenna array.

Effect of CSI quantization on the average rate in MU-MIMO WLANs

Abstract: In Multi-User Multiple Input Multiple Output (MU-MIMO) Wireless Local Area Networks (WLANs), the optimal-solution such as Dirty Paper Coding (DPC) or the sub-optimal solution Zeroforcing Beamforming (ZFB) with perfect Channel State Information (CSI), is practically limited due to the complexity and the non-availability of perfect CSI at the Access Points (APs)/transmitters. In such a context, ZFB based on channel quantization available at the APs (ZFQ) is the obvious choice for the Multi-User transmission strategy. However, since the quantized CSI is used instead of the perfect CSI at the APs, the quantization error and its impact on the average rate for ZFQ have to be quantified in MU-MIMO WLAN settings. In this paper, we derive a closed-form expression for the upper bound of the channel quantization error and the average rate reduction due to the quantization error with respect to the perfect CSI at the APs. In MU-MIMO WLAN settings, our analytical and numerical studies show that, with an increasing number of antennas at the clients, both the quantization error bound and the average rate reduction increase for ZFQ, in comparison to the ZFB with the perfect CSI.

Beyond Dirty Paper Coding for Multi-Antenna Broadcast Channel with Partial CSIT: A Rate-Splitting Approach

Abstract: Imperfect Channel State Information at the Transmitter (CSIT) is inevitable in modern wireless communication networks, and results in severe multi-user interference in multi-antenna Broadcast Channel (BC). While the capacity of the multi-antenna (Gaussian) BC with perfect CSIT is known and achieved by Dirty Paper Coding (DPC), the capacity and the capacity-achieving strategy of the multi-antenna BC with imperfect CSIT remain unknown. Conventional approaches therefore rely on applying communication strategies designed for perfect CSIT to the imperfect CSIT setting. In this work, we break this conventional routine and make two major contributions. First, we show that linearly precoded Rate-Splitting (RS), relying on the split of messages into common and private parts and linear precoding at the transmitter, and successive interference cancellation at the receivers, can achieve larger rate regions than DPC in multi-antenna BC with partial CSIT. Second, we propose a novel achievable scheme, denoted as Dirty Paper Coded Rate-Splitting (DPCRS), that relies on RS to split the user messages into common and private parts, and DPC to encode the private parts. We show that the rate region achieved by DPCRS in Multiple-Input Single-Output (MISO) BC with partial CSIT is enlarged beyond that of conventional DPC and that of linearly precoded RS. Gaining benefits from the capability of RS to partially decode the interference and partially treat interference as noise, DPCRS is less sensitive to CSIT inaccuracies, networks loads and user deployments compared with DPC and other existing transmission strategies. The proposed DPCRS acts as a new benchmark and the best-known achievable strategy for multi-antenna BC with partial CSIT.