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 Region of MISO Broadcast Channel for Simultaneous Wireless Information and Power Transfer

Abstract: This paper studies a multiple-input single-output (MISO) broadcast channel (BC) featuring simultaneous wireless information and power transfer (SWIPT), where a multi-antenna access point (AP) delivers both information and energy via radio signals to multiple single-antenna receivers simultaneously, and each receiver implements either information decoding (ID) or energy harvesting (EH). In particular, pseudo-random sequences that are {\it a priori} known and therefore can be cancelled at each ID receiver is used as the energy signals, and the information-theoretically optimal dirty paper coding (DPC) is employed for the information transmission. We characterize the capacity region for ID receivers under given energy requirements for EH receivers, by solving a sequence of weighted sum-rate (WSR) maximization (WSRMax) problems subject to a maximum sum-power constraint for the AP, and a set of minimum harvested power constraints for individual EH receivers. The problem corresponds to a new form of WSRMax problem in MISO-BC with combined maximum and minimum linear transmit covariance constraints (MaxLTCCs and MinLTCCs), which differs from the celebrated capacity region characterization problem for MISO-BC under a set of MaxLTCCs only and is challenging to solve. By extending the general BC-multiple access channel (MAC) duality, which is only applicable to WSRMax problems with MaxLTCCs, and applying the ellipsoid method, we propose an efficient algorithm to solve this problem globally optimally. Furthermore, we also propose two suboptimal algorithms with lower complexity by assuming that the information and energy signals are designed separately. Finally, numerical results are provided to validate our proposed algorithms.

Achievable throughput approximation for RBD precoding at high SNRS

Abstract: In this paper, we study the achievable throughput for regularized block diagonalization (RBD) precoding in multi-user MIMO broadcast channels at high SNRs. By applying an analytical framework for a high SNR affine approximation to capacity, we derive the multiplexing gains and the power offsets for RBD in two cases separately. In the first case, we assume that the aggregate number of receive antennas is less than or equal to the number of transmit antennas. It is found that RBD can maintain the same multiplexing gain as dirty paper coding (DPC) and block diagonalization (BD) precoding at high SNRs and has a smaller power offset than BD. The sum rate differences relative to DPC and BD are analyzed and bounded as simple functions of the system parameters. In the second case, we assume that the aggregate number of receive antennas is larger than the number of transmit antennas. Although RBD can still be performed, the achievable throughput is degraded with an increasing number of receive antennas. The benefit of spatial multiplexing is completely lost due to a unit spatial multiplexing gain at high SNRs.

Rewriting flash memories and dirty-paper coding

Abstract: This paper considers that write-once memory (WOM) codes can be seen as a type of dirty-paper code. The current state of the memory, which is known to the encoder, plays the role of the known interference of dirty-paper coding. Erez, Shamai and Zamir showed that lattice strategies can achieve the capacity of the known-interference channel. In this paper, lattices are used to design a WOM code. Encoding is performed modulo a shaping lattice with respect to a lattice fundamental region to obtain a codeword, to be added to the current state of the memory. The fundamental region is designed to accommodate the limitations of the flash memory system, particularly, that values can only increase. The criterion for evaluation is average number of writes. In order to improve the average number of writes, “coset select” bits are introduced, to maximize the average number of writes. For an eight-dimensional lattice, numerical results for practical parameter choices show a promising trend.

Successive Null-Space Precoder Design for Downlink MU-MIMO with Rate Splitting and Single-Stage SIC

Abstract: In this paper, we consider the precoder design for an under-loaded or critically loaded downlink multi-user multiple-input multiple-output (MU-MIMO) communication system. We propose novel precoding and decoding schemes which enhance system performance based on rate splitting at the transmitter and single-stage successive interference cancellation at the receivers. The proposed successive null-space (SNS) precoding scheme utilizes linear combinations of the null-space basis vectors of the successively augmented MIMO channel matrices of the users as precoding vectors to adjust the inter-user-interference experienced by the receivers. We formulate a non-convex weighted sum rate (WSR) optimization problem, and solve it via successive convex approximation to obtain a suboptimal solution for the precoding vectors and the associated power allocation. Our simulation results reveal that the proposed SNS precoders outperform block diagonalization based linear and rate splitting designs, and in many cases, have a relatively small gap to the maximum sum rate achieved by dirty paper coding.

Performance Limits of a Cloud Radio

Abstract: Cooperation in a cellular network is seen as a key technique in managing other cell interference to observe a gain in achievable rate. In this paper, we present the achievable rate regions for a cloud radio network using a sub-optimal zero forcing equalizer with dirty paper precoding. We show that when complete channel state information is available at the cloud, rates close to those achievable with total interference cancellation can be achieved. With mean capacity gains, of up to 2 fold over the conventional cellular network in both uplink and downlink, this precoding scheme shows great promise for implementation in a cloud radio network. To simplify the analysis, we use a stochastic geometric framework based of Poisson point processes instead of the traditional grid based cellular network model. We also study the impact of limiting the channel state information and geographical clustering to limit the cloud size on the achievable rate. We have observed that using this zero forcing-dirty paper coding technique, the adverse effect of inter-cluster interference can be minimized thereby transforming an interference limited network into a noise limited network as experienced by an average user in the network for low operating signal-to-noise-ratios. However, for higher signal-to-noise-ratios, both the average achievable rate and cell-edge achievable rate saturate as observed in literature. As the implementation of dirty paper coding is practically not feasible, we present a practical design of a cloud radio network using cloud a minimum mean square equalizer for processing the uplink streams and use Tomlinson-Harashima precoder as a sub-optimal substitute for a dirty paper precoder in downlink.