Showing papers on "Dirty paper coding published in 2003"

On the achievable throughput of a multiantenna Gaussian broadcast channel

Abstract: A Gaussian broadcast channel (GBC) with r single-antenna receivers and t antennas at the transmitter is considered. Both transmitter and receivers have perfect knowledge of the channel. Despite its apparent simplicity, this model is, in general, a nondegraded broadcast channel (BC), for which the capacity region is not fully known. For the two-user case, we find a special case of Marton's (1979) region that achieves optimal sum-rate (throughput). In brief, the transmitter decomposes the channel into two interference channels, where interference is caused by the other user signal. Users are successively encoded, such that encoding of the second user is based on the noncausal knowledge of the interference caused by the first user. The crosstalk parameters are optimized such that the overall throughput is maximum and, surprisingly, this is shown to be optimal over all possible strategies (not only with respect to Marton's achievable region). For the case of r>2 users, we find a somewhat simpler choice of Marton's region based on ordering and successively encoding the users. For each user i in the given ordering, the interference caused by users j>i is eliminated by zero forcing at the transmitter, while interference caused by users j

Duality, achievable rates, and sum-rate capacity of Gaussian MIMO broadcast channels

Abstract: We consider a multiuser multiple-input multiple- output (MIMO) Gaussian broadcast channel (BC), where the transmitter and receivers have multiple antennas. Since the MIMO BC is in general a nondegraded BC, its capacity region remains an unsolved problem. We establish a duality between what is termed the "dirty paper" achievable region (the Caire-Shamai (see Proc. IEEE Int. Symp. Information Theory, Washington, DC, June 2001, p.322) achievable region) for the MIMO BC and the capacity region of the MIMO multiple-access channel (MAC), which is easy to compute. Using this duality, we greatly reduce the computational complexity required for obtaining the dirty paper achievable region for the MIMO BC. We also show that the dirty paper achievable region achieves the sum-rate capacity of the MIMO BC by establishing that the maximum sum rate of this region equals an upper bound on the sum rate of the MIMO BC.

Sum capacity of the vector Gaussian broadcast channel and uplink-downlink duality

Abstract: We characterize the sum capacity of the vector Gaussian broadcast channel by showing that the existing inner bound of Marton and the existing upper bound of Sato are tight for this channel. We exploit an intimate four-way connection between the vector broadcast channel, the corresponding point-to-point channel (where the receivers can cooperate), the multiple-access channel (MAC) (where the role of transmitters and receivers are reversed), and the corresponding point-to-point channel (where the transmitters can cooperate).

Downlink capacity evaluation of cellular networks with known-interference cancellation

Abstract: Recently, the capacity region of a multiple-input multiple-output (MIMO) Gaussian broadcast channel, with Gaussian codebooks and known-interference cancellation through dirty paper coding, was shown to equal the union of the capacity regions of a collection of MIMO multiple-access channels. We use this duality result to evaluate the system capacity achievable in a cellular wireless network with multiple antennas at the base station and multiple antennas at each terminal. Some fundamental properties of the rate region are exhibited and algorithms for determining the optimal weighted rate sum and the optimal covariance matrices for achieving a given rate vector on the boundary of the rate region are presented. These algorithms are then used in a simulation study to determine potential capacity enhancements to a cellular system through known-interference cancellation. We study both the circuit data scenario in which each user requires a constant data rate in every frame and the packet data scenario in which users can be assigned a variable rate in each frame so as to maximize the long-term average throughput. In the case of circuit data, the outage probability as a function of the number of active users served at a given rate is determined through simulations. For the packet data case, long-term average throughputs that can be achieved using the proportionally fair scheduling algorithm are determined. We generalize the zero-forcing beamforming technique to the multiple receive antennas case and use this as the baseline for the packet data throughput evaluation.

On "Dirty-Paper coding"

Abstract: Dirty-paper coding makes an analogy to the problem of writing on dirty paper, where the reader cannot nominally distinguish dirt from ink. There are many scenarios where this result may be applied. In the field of information hiding (or watermarking), theoretical bounds as well as practical watermarking schemes have been found. Another important application of dirty-paper coding is for a multiuser channel wherein a multiple-antenna transmitter is communicating with multiple users.

Combined shaping and precoding for interference cancellation at low SNR

Abstract: We consider multi dimensional dirty paper coding at low SNR, and propose a low rate precoding scheme which combines MMSE estimation, dithering and a variant of nested codes, based on concatenation of a "syndrome dilution" code and a "syndrome-to-coset" modulation code.

Multiple antenna transmitter optimization schemes for multiuser systems

Abstract: We present multiple antenna transmitter optimization (i.e., spatial prefiltering) schemes that are based on linear transformations and transmit power optimization (keeping average transmit power conserved). We consider the downlink of a wireless system with multiple transmit antennas at the base station and a number of mobile terminals (i.e., users) each with a single receive antenna. We consider the maximum achievable data rates in the case of the zero-forcing and triangularization spatial prefiltering coupled with a dirty paper coding transmission scheme. We also present the effects of channel mismatch.

Optimal Power Allocation for Parallel Gaussian Broadcast Channels with Independent and Common Information

Abstract: We consider a set of parallel, two-user Gaussian broadcast channels, where the transmitter wishes to send independent information to each of the receivers and common information to both receivers. The ca- pacity region of this channel has been implicitly characterized in the past, but we provide an explicit characterization of the power and rate allocation schemes that achieve the boundary of the three-dimensional rate region. Unlike the broadcast channel with only independent information, we find that the optimal power allocation policy cannot be viewed as a generaliza- tion of single-user water-filling. We also consider MIMO bro adcast chan- nels, which are non-degraded in general. We propose an achievable region based on dirty paper coding, and discuss the maximum common informa- tion rate achievable over these channels. I. I NTRODUCTION As wireless networks evolve, it is apparent that multi-cast (i.e. sending a common message to all users on a downlink chan- nel) is an important mode of communication that systems will require in the future. In cellular networks, for example, multi- cast information could be common information such as news updates or location-based information. It is reasonable to as- sume that networks will want to transmit a mixture of common information to all users and independent information to each of the users. With this in mind, we consider broadcast channels with both common and independent information. We consider parallel two-user Gaussian broadcast channels, where the transmitter wants to send independent information to users 1 and 2 at rates R1 and R2, respectively, and common in- formation (decodable by both users) at rate R0. For degraded broadcast channels, the common information rate and the inde- pendent information rate to the degraded user are interchange- able, because the strongest user can decode anything that the de- graded user can. However, we consider parallel channels where in some channels User 1 is the degraded user, but in other chan- nels User 2 is the degraded user. The capacity region of this channel (for both discrete memoryless channels and for Gaus- sian channels) was characterized in (1) in terms of a union of regions, where the union was taken over different power distri- butions between the different channels. We first derive an eq uiv- alent expression for this capacity region that is more amenable to optimization techniques. We then pose the problem of character- izing the optimal power and rate allocation schemes that achieve the boundary of the three-dimensional region using Lagrangian techniques. We then apply the utility function approach used for the broadcast channel (2) without common information, but we find that this approach does not work in general. We use a more direct approach to maximize the Lagrangian function and obtain the capacity region with common information using this approach. Using this method, the optimal allocation is found by performing a finite maximization in each channel. Finally, we consider MIMO broadcast channels, which in general are not degraded. Thus, the capacity region with or without common information is not known for this channel. We propose an achievable region based on dirty paper coding. We also consider the maximum common rate achievable on these channels, i.e. the common information capacity.