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.

On the Convergence of Genetic Scheduling Algorithms for Downlink Transmission in Multi-User MIMO Systems

Abstract: In a multi-user MIMO system using a successive precoding method such as dirty paper coding, it is combinatorially complex to determine the optimal set of users to schedule and the proper order to encode their signals in order to optimize a utility function in a scheduling algorithm. Genetic algorithms represent a fast suboptimal approach to reducing the complexity of the search. In this paper, we build upon prior work that implements scheduling via genetic algorithms. We examine the impact of parameter values within the adaptive mutation rate of the algorithm on its convergence time. We demonstrate that although there is a range of values for the parameters that yields similar near-minimum convergence times, it is nonetheless important to ensure that the parameters are tuned to be within that range. In one case, tuning the parameter values reduces the time of convergence to less than 30% compared to that achievable with the initial parameter values. We also demonstrate that the proper parameter values are dependent on both the number of transmit antennas and the number of users in the pool of users to be scheduled. A simple equation is proposed that is linear in the adaptive mutation parameters to tune the values for different numbers of transmit antennas and users.

Gaussian state amplification with noisy state observations

Abstract: The problem of simultaneous message transmission and state amplification in a Gaussian channel with additive Gaussian state is studied when the sender has imperfect non-causal knowledge of the state sequence. Inner and outer bounds to the rate-state-distortion region are provided. The coding scheme underlying the inner bound combines analog signaling and Gelfand-Pinsker coding, where the latter deviates from the operating point of Costa's dirty paper coding.

Broadband Wireless Broadcast Channels: Throughput, Performance, and PAPR Reduction

Abstract: The ever-growing demand for higher rates and better quality of service in cellular systems has attracted many researchers to study techniques to boost the capacity and improve the performance of cellular systems. The main candidates to increase the capacity are to use multiple antennas or to increase the bandwidth. This thesis attempts to solve a few challenges regarding scheduling schemes in the downlink of cellular networks, and the implementation of modulation schemes suited for wideband channels. Downlink scheduling in cellular systems is known to be a bottleneck for future broadband wireless communications. Information theoretic results on broadcast channels provide the limits for the maximum achievable rates for each receiver and transmission schemes to achieve them. It turns out that the sum-rate capacity (sum-rate (or throughput) refers to the sum of the transmission rates to all users) of a multi-antenna broadcast channel heavily depends on the availability of channel state information (CSI) at the transmitter. Unfortunately, the dirty paper coding (DPC) scheme which achieves the capacity region is extremely computationally intensive especially in multiuser context. Furthermore, relying on the assumption that full CSI is available from all the n users may not be feasible in practice. In the first part of the thesis, we obtain the scaling law of the sum-rate capacity for large n and for a homogeneous fading MIMO (multiple input multiple output) broadcast channel, and then propose a simple scheme that only requires little (partial) CSI and yet achieves the same scaling law. Another important issue in downlink scheduling is to maintain fairness among users with different distances to the transmitter. Interestingly, we prove that our scheduling scheme becomes fair provided that the number of transmit antennas is large enough. We further analyze the impact of using a throughput optimal scheduling on the delay in sending information to the users. Finally, we look into the problem of differentiated rate scheduling in which different users demand for different sets of rates. We obtain explicit scheduling schemes to achieve the rate constraints. In the second part of the thesis, we focus on orthogonal frequency division multiplexing (OFDM), which is the most promising technique for broadband wireless channels (mainly due to its simplicity of channel equalization even in a severe multipath fading environment). The main disadvantage of this modulation, however, is its high peak to mean envelope power ratio (PMEPR). This is due to the fact that the OFDM signal consists of many (say n) harmonically related subcarriers which may, in the worst-case, add up constructively and lead to large peaks (of order n) in the signal. Despite this worst-case performance, we show that when each subcarrier is chosen from some given constellation, the PMEPR behaves like log{n} almost surely, for large n. This implies that there exist almost full-rate codes with a PMEPR of log{n} for large n. We further prove that there exist codes with rate not vanishing to zero such that the PMEPR is less than a constant (independent of n). We also construct high rate codes with a guaranteed PMEPR of log{n}. Simulation results show that in a system with 128 subcarriers and using 16QAM, the PMEPR of a multicarrier signal can be reduced from 13.5 to 3.4 which is within 1.6dB of the PMEPR of a single carrier system.

Eigenmode Tomlinson-Harashima Precoding for multi-antenna multi-user MIMO broadcast channel

Abstract: In the previous works, performance of different transmission algorithms in multi-antenna multi-user MIMO broadcast channel were investigated. The result showed that Eigenmode Dirty Paper Coding (EM-DPC) algorithm was superior to the others. Nevertheless, the problem of EM-DPC is that the precoding algorithm significantly increases Peak-to- Average Power Ratio (PAPR). In this paper, to face with the PAPR problem, we propose a new algorithm called Eigenmode Tomlinson-Harashima Precoding (EM-THP), by introduction of modulo operations at both the transmitter and the receiver. It is found from numerical analyses that the proposed method can approximately achieve the throughput performance of the ideal EM-DPC while limiting the PAPR to a lower level.

Suboptimum Space Multiplexing Structure Combining Dirty Paper Coding and Receive Beamforming

Abstract: We consider the MIMO broadcast channel where a base station with multiple antennas transmits simultaneously to many users. The optimum strategy with Channel State Information (CSI) at the transmitter is based on Dirty Paper Coding (DPC) principles. In this paper, we propose a suboptimum strategy suitable when terminals are equipped with multiple antennas. This approach combines DPC and receive beam-forming and is shown to provide near-optimum performance with very reasonable complexity. Beamforming design is based on the maximization of the sum rate while precoder design is based on Zero Forcing (ZF) criteria. We have to remark that it is not required iterative processes or interaction between transmitter and receivers to find the suboptimum solution. It is also important to mention that each terminal just needs to know its own channel to perform the optimization while the base station requires full knowledge of all users' channels.