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.

Linear Precoding Techniques for MIMO Systems

Abstract: Precoding is a method used in Multiple Input and Multiple Output t antennas (MIMO) technology to achieve parallel data at the receiver with reduced Bit Error Rate (BER) and with increased channel capacity. There two different precoding techniques available, namely Linear Precoding Technique (LPT) and Non-linear Precoding Techniques (N-LPT). LPT include different methods like Singular Value Decomposition (SVD), Block Diagonalization (BD) and N_LPT like Dirty Paper Coding (DPC). N-LPT have high computational complexity. Thus analysis is done for the existing LPT’s which make use of Channel State Information (CSI) both at transmitter and receiver end to reduce computational complexity. In this paper, SVD and BD linear precoding techniques are simulated and compared their BER for different the modulation methods similar to BPSK, QPSK and 8-PSK using MATLAB for 4 × 4 MIMO. Two different equalization specifically Zero Forcing (ZF) and Minimum Mean Square Error (MMSE) are considered for BER calculation. BER is reduced by 5% with SVD precoding using QPSK modulation than without precoding. Comparing BER of SVD and BD techniques for a 4 × 4 MIMO using QPSK modulation, 90% better results have been achieved in BD. A 2 × 2 MIMO with SVD precoding system was implemented using Universal Software Radio Peripheral (USRP-2920) and the results are plotted.

A Close-to-Capacity Dirty Paper Coding Scheme Uri Erez and Stephan ten Brink

Abstract: The "writing on dirty paper"-channel model offers an infor- mation theoretic framework for precoding techniques for canceling arbi- trary interference known at the transmitter. Using lattice strategies and MMSE scaling, lossless precoding is theoretically possible at any signal to noise-ratio. Following this approach, we design an end-to-end coding real- ization of a system materializing a significant portion of the promised gains. We employ vector quantization in combination with iterative decoding of capacity-approaching codes to achieve more than 2dB improvement over the best scalar quantization scheme. Code design is done using the EXIT chart technique.

Interference Cancellation in Broadcast Channel of Multiuser MIMO system using Block Diagonalization and Dirty Paper Coding Schemes

Abstract: In Multiuser MIMO system, multiple antennas are placed on base station and also on multiple users. Multiple antennas technique enhanced the performance parameters like reliability and data rate of wireless communication system without required more bandwidth, multiple antennas at transmitting and receiving end provides transmitting and receiving diversity, diversity increases the reliability of signal and spatial multiplexing increases the data rate by transmitting multiple information streams between transmitter and receiver. The base station transmits multiple streams to mobile station through downlink channel, known as broadcast channel and mobile users also transmit multiple streams to base station through uplink channel, known as multiple access channel. This paper considers only broadcast channel, the major issue in information transmission in broadcast channel is that the desired signal on the receiving side is affected by other user interference as well as inter-antenna interference. So, interference cancellation schemes on the transmitting end plays very important role to reduced interference on receiving end in multiuser MIMO wireless communication system. This paper discusses two interference cancellation schemes, Block Diagonalization (BD) and Dirty Paper Coding (DPC). Block Diaganalization is linear precoding technique that is used at transmitting end and it uses singular value decomposition operation to get block diagonalization precoding weights. Dirty Paper Coding is non-linear precoding technique; this technique is applied only when channel gains are completely known at transmitting end. This paper also shows performance comparison of block diagonalization and dirty paper coding schemes in term of Bit Error Rate Keywords-Multiuser MIMO, Block Diagonalization, DPC.

Key agreement over Gaussian wiretap models with known interference at the transmitter

Abstract: We investigate the (forward) key capacity of a Gaussian state-dependent wiretap channel (G-SWC) paralleled with a public channel having capacity C p ∊ [0, ∞). This model consists of a sender, a main receiver, and a wiretapper. The channel state information (CSI) is an additive white Gaussian interference (AWGI) which is non-causally known at the sender. A lower bound (LB) on the key capacity is achieved by using a generalized version of the dirty paper coding (DPC) in which the transmitted signal is correlated with the interference. The correlation coefficient is to be determined by C p . The achievable scheme is asymptotically optimum as C p → ∞. This optimum key capacity is also asymptotically achievable for any C p ≥ 0 in high signal to interference ratio (SIR) regime. In this regime, the public channel has negligible contribution in key generation. Generally, the CSI enhances the key capacity such that it exceeds the main channel capacity of the G-SWC in low SIR regime.

A Soft Demodulation Algorithm with Low Complexity for One-dimensional DPC System

Abstract: Based on the one-dimensional dirty paper coding (DPC) system, a low complexity algorithm is proposed to calculate log likelihood ratios (LLRs) for multi-level quadrature amplitude modulation (M ? QAM). The M ? QAM constellation is split into the in-phase and quadrature $${\sqrt{M}-PAM}$$ signal of mutual independence, and the LLR value of each bit is calculated on the expanded $${\sqrt{M}-PAM}$$ constellation. For both the complete interference pre-subtraction and partial interference pre-subtraction schemes, accurate LLR values can be obtained using the proposed simplified algorithm. The proposed algorithm is applied to the one-dimensional DPC system using convolutional code and low density parity check code respectively. Simulation results indicate that the bit error rate performance is almost not lost with the simplified algorithm while the computational complexity is reduced significantly.