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.

Apparatus and method for removing interference in transmitting end of multi-antenna system

Abstract: An apparatus and method for removing interference in a transmitting end of a multi-antenna system are provided. The method includes receiving channel information for all Receive (Rx) antennas; calculating a beam-forming matrix that maximizes a Signal-to-Interference plus Noise Ratio (SINR) for each Rx antenna by using the received channel information; calculating an integer value which is in proportion to an interference signal for each Rx antenna by using the received channel information and the calculated beam-forming matrix, and performing Dirty Paper Coding (DPC) on a Transmit (Tx) signal by using the calculated integer value; and performing beam-forming by multiplying the Tx signal that has undergone the DPC by the calculated beam-forming matrix. Accordingly, a highest data rate for each user and a highest diversity can be obtained.

Arbitrarily dirty paper coding and applications

Abstract: A deterministic dirty-paper coding strategy for communication over an arbitrarily varying channel with an interference signal known to the transmitter is investigated. The presence of a known interference signal at the transmitter is shown to provide some protection against jamming interference. For some values of the parameters the scheme is capacity- achieving. Applications to watermarking and spectrum-sharing channels are described.

Sum Rate Maximizing in a Multi-User MIMO System with SWIPT

Abstract: -This paper studies the simultaneous wireless infor- mation and power transfer (SWIPT) in a multiuser broadcast (BC) multiple-input multiple-output (MIMO) system, in which a base station sends messages to several information decoding (ID) users, and transmits wireless power to multiple energy harvesting (EH) user at the same time. We aim to maximize the sum-rate of the ID users while maintaining a minimum EH constraint for each EH user. Firstly, an optimal rate-energy (R-E) boundary is characterized by using a BC-multiple access channel (MAC) duality derived from dirty paper coding (DPC). Since the complexity of the DPC is quite high due to continuously encoding and decoding at the transceivers, we then propose a sub- optimal algorithm using a weighted minimum mean square error (WMMSE) approach, which has lower complexity and iteratively converges a local optimal point. Finally, the performance com- parisons and convergence properties are illustrated by simulation results

Sensing in cognitive radio channels: A theoretical perspective

Abstract: The cognitive radio paradigm is based on the ability of sensing the radio environment in order to make informed decisions. This paper describes the effects of sensing on the cognitive radio channels capacity region. Sensing is modeled as a compression channel, which results in partial knowledge of the primary messages at the cognitive transmitter. This model enables to impose constraints on the sensing strategy. First, the dirty paper channel capacity is derived when the channel encoder knows partially the side information. Then, the capacity area of the Gaussian cognitive channel with partial information is derived. Finally, numerical results illustrate the capacity reduction associated with constrained sensing, in comparison to the capacity of the cognitive radio channel.

Fast Distributed Multi-Cell Scheduling with Delayed Limited-Capacity Backhaul Links

Abstract: Both fast scheduling and spatial signal processing have proven to be capacity-increasing methods in wireless communication systems. However, when applied in the downlink of a cellular network, the combination of both leads to non-stationary intercell interference. If the base stations do not cooperate, either they have to encode the data very conservatively to gain robustness or the non-stationary fluctuations of the interference powers lead to frequent outages, both of which strongly impair the average achievable throughput. On the other hand, base station cooperation increases complexity and delays, contradicting the desire for fast scheduling algorithms. In this paper, we propose a scheme that makes average channel state information available to all base stations via low-rate backhaul communication, whereas high-rate inter-base-station communication is limited to B ⌈log2 K⌉-bit integers, K being the number of users in each of the B cells. Simulations show that for slow fading channels, the proposed algorithm preserves most of the per cell sum-rate of other beamforming and dirty-paper coding approaches that have unlimited-capacity backhaul links. Furthermore, when out-of-cell information is outdated the proposed algorithm even outperforms those.