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.

Antenna selection for opportunistic interference management in MIMO broadcast channels

Abstract: Opportunistic interference management (OIM) is an approach that can asymptotically achieve dirty paper coding (DPC) capacity in the downlink of wireless cellular networks with minimum feedback requirement. With K antennas at the base station and M mobile users in the cell, the proposed technique requires only K integer numbers related to channel state information (CSI). This multiplexing gain of K is achieved at the expense of M mobile users such that K = Θ(logM). We introduce an antenna selection scheme at the base station to reduce the minimum number of required mobile users significantly at the expense of reasonable increase in feedback.

Interference management: A new paradigm for wireless cellular networks

Abstract: We introduce a new interference management technique for wireless cellular networks when the base station (BS) has K antennas and there are M mobile stations (MS), each with a single antenna. Our interference management scheme takes advantage of multiuser diversity to transmit K independent data streams to K out of M mobile stations. The new approach achieves the dirty paper coding (DPC) capacity of K log log(M) as M tends to infinity. Surprisingly, the new scheme does not require full channel state information (CSI) and needs only close to K integers related to CSI are fed back to the transmitter. Moreover, the encoding and decoding of the new scheme is significantly simpler than existing MIMO schemes and is similar to point-to-point communications.

Achieving Large Sum Rate and Good Fairness in MISO Broadcast Communication

Abstract: A tradeoff between sum rate and fairness for multiple-input single-output (MISO) broadcast communication employing dirty paper coding or zero-forcing dirty paper coding at physical layer is investigated in this paper. The tradeoff is based on a new design objective termed “tri-stage” approach as well as a new $\ell _1$ -based fairness measure that is much more robust than the well-known Jain's index for comparing fairness levels achieved by various design objectives at a much finer resolution in high SNR regime. The newly proposed tri-stage design also introduces a new concept of statistical power allocation that randomly allocates power to users based on an optimal probability distribution derived from the tradeoff between sum rate and fairness. Simulation results show that the proposed approach can simultaneously achieve a larger sum rate and better fairness than the reputable proportional fairness criterion. A performance upper bound is also given in the paper to show the excellent performance of the proposed approach at moderate and high SNR regimes as well as some potential for further improvement in low SNR regime.

Sum-rate maximization and sum-power minimization for 2-user (2,2) downlink systems using generalized zero-forcing

Abstract: The paper analyzes a downlink system where a 2-antenna base station is sending independent signals to two 2-antenna mobile users simultaneously in the same physical (time and frequency) channel. To multiplex the signals in the spatial domain, we consider the use of orthogonal space-division multiplexing (OSDM), broadly known as generalized zero-forcing (GZF), that allows the users to be completely separated before decoding. The paper's main contribution is that we derive the optimal array processing solutions for both the sum-rate maximization problem, subject to a fixed transmit power constraint, and the sum-power minimization problem, subject to a fixed rate constraint. The capacity and signal-to-noise ratio (SNR) regions for the OSDM system are also derived, and results for dirty-paper coding (DPC) and time-division systems are provided for comparison.

ASIP design for multiuser MIMO broadcast precoding

Abstract: This paper presents an application-specific instruction-set processor (ASIP) for multiuser multiple-input multiple-output (MU-MIMO) broadcast precoding. The ASIP is designed for a base station (BS) with four antennas to perform user scheduling and precoding. Transport triggered architecture (TTA) is used as the processor template and high level language is used to program the ASIP. Several special function units (SFU) are designed to accelerate norm-based greedy user scheduling and minimum-mean square error (MMSE) precoding. We also program zero forcing dirty paper coding (ZF-DPC) to demonstrate the reusability of the ASIP. A single core provides a throughput of 52.17 Mbps for MMSE precoding and takes an area of 87.53 kgates at 200 MHz on 90 nm technology.