Multiple input multiple output Dirty paper coding: System design and performance

Abstract

Abstract-In this paper, a practical multiple input multiple output Dirty paper coding (MIMO-DPC) scheme is designed to cancel the effect of additive interference that is known perfectly to the transmitter. The proposed system uses a trio of encoders -a LDPC code, a vector quantizer implemented as a convolutional decoder and an Orthogonal space time block code (STBC) to achieve temporal coding gain, interference cancelation and spatial diversity, respectively. First, we derive the equivalent noise seen by the receiver using an equivalent lattice based dirty paper code. Then the optimal value of the power inflation factor, which is one of the key system parameters used to minimize the equivalent noise seen by the receiver is derived. Furthermore, we analytically prove that the equivalent noise seen by the receiver tends to 0 for large number of receive antennas. Performance results in the case of various number of receiver antennas are presented and show that significant reduction in bit error probabilities can be obtained over a system that uses no interference cancelation.

Performance analysis of multiuser MIMO broadcast channel based on LQ decomposition

“…Noise mitigation in Broadcast channel (BC) of MU-MIMO by using MMSE based pre-coding and combining with QR decomposition is discussed in [3]. In [4] a combination of a MIMO dirty paper code (DPC), a low density parity check code (LDPC) and a space-time block encoder is discussed, additive interference among users are mitigated, power inflation factor which is not the actual transmit power is used to minimise the effect of noise at the receiver. Channel capacity of MU-MIMO system using LQ and SVD decomposition with CSI and without CSI for various MIMO configuration is discussed in [5].…”

User scheduling based on angles with block diagonalization in MU‐MIMO broadcast

“…Dirty paper coding is based on the noncausal knowledge of each user's interference. 5 The complexity of the nonlinear operations prohibits it from applying. Some suboptimal preprocessing strategies are proposed to meet the complexity requirement, and further more reduce the power consumption.…”

Joint Scheduling and Precoding Based on SLNR Criteria in MU-MIMO System

“…The precoding technology can be divided into linear and nonlinear. Nonlinear precoding such as DPC (Dirty Paper Coding) [2] can get perfect sum capacity in theory, but high complexity made it hard to accomplish in practice. Linear precoding is widely used, such as ZF (Zero Forcing) precoding [3,4], MMSE (Minimum Mean Square Error) precoding [4], BD (Block Diagonal) precoding and SLNR precoding [5,6].…”