872 research outputs found
Code designs for MIMO broadcast channels
Recent information-theoretic results show the optimality of dirty-paper coding (DPC) in achieving the full capacity region of the Gaussian multiple-input multiple-output (MIMO) broadcast channel (BC). This paper presents a DPC based code design for BCs. We consider the case in which there is an individual rate/signal-to-interference-plus-noise ratio (SINR) constraint for each user. For a fixed transmitter power, we choose the linear transmit precoding matrix such that the SINRs at users are uniformly maximized, thus ensuring the best bit-error rate performance. We start with Cover's simplest two-user Gaussian BC and present a coding scheme that operates 1.44 dB from the boundary of the capacity region at the rate of one bit per real sample (b/s) for each user. We then extend the coding strategy to a two-user MIMO Gaussian BC with two transmit antennas at the base-station and develop the first limit-approaching code design using nested turbo codes for DPC. At the rate of 1 b/s for each user, our design operates 1.48 dB from the capacity region boundary. We also consider the performance of our scheme over a slow fading BC. For two transmit antennas, simulation results indicate a performance loss of only 1.4 dB, 1.64 dB and 1.99 dB from the theoretical limit in terms of the total transmission power for the two, three and four user case, respectively
Fundamental Limits in MIMO Broadcast Channels
This paper studies the fundamental limits of MIMO broadcast channels from a high level, determining the sum-rate capacity of the system as a function of system paramaters, such as the number of transmit antennas, the number of users, the number of receive antennas, and the total transmit power. The crucial role of channel state information at the transmitter is emphasized, as well as the emergence of opportunistic transmission schemes. The effects of channel estimation errors, training, and spatial correlation are studied, as well as issues related to fairness, delay and differentiated rate scheduling
On the Capacity Region of Multi-Antenna Gaussian Broadcast Channels with Estimation Error
In this paper we consider the effect of channel estimation error on the capacity region of MIMO Gaussian broadcast channels. It is assumed that the receivers and the transmitter have (the same) estimates of the channel coefficients (i.e., the feedback channel is noiseless). We obtain an achievable rate region based on the dirty paper coding scheme. We show that this region is given by the capacity region of a dual multi-access channel with a noise covariance that depends on the transmit power. We explore this duality to give the asymptotic behavior of the sum-rate for a system with a large number of user, i.e., n rarr infin. It is shown that as long as the estimation error is of fixed (w.r.t n) variance, the sum-capacity is of order M log log n, where M is the number of antennas deployed at the transmitter. We further obtain the sum-rate loss due to the estimation error. Finally, we consider a training-based scheme for block fading MISO Gaussian broadcast channels. We find the optimum length of the training interval as well as the optimum power used for training in order to maximize the achievable sum-rate
Filter and nested-lattice code design for fading MIMO channels with side-information
Linear-assignment Gel'fand-Pinsker coding (LA-GPC) is a coding technique for
channels with interference known only at the transmitter, where the known
interference is treated as side-information (SI). As a special case of LA-GPC,
dirty paper coding has been shown to be able to achieve the optimal
interference-free rate for interference channels with perfect channel state
information at the transmitter (CSIT). In the cases where only the channel
distribution information at the transmitter (CDIT) is available, LA-GPC also
has good (sometimes optimal) performance in a variety of fast and slow fading
SI channels. In this paper, we design the filters in nested-lattice based
coding to make it achieve the same rate performance as LA-GPC in multiple-input
multiple-output (MIMO) channels. Compared with the random Gaussian codebooks
used in previous works, our resultant coding schemes have an algebraic
structure and can be implemented in practical systems. A simulation in a
slow-fading channel is also provided, and near interference-free error
performance is obtained. The proposed coding schemes can serve as the
fundamental building blocks to achieve the promised rate performance of MIMO
Gaussian broadcast channels with CDIT or perfect CSITComment: submitted to IEEE Transactions on Communications, Feb, 200
Communication Over MIMO Broadcast Channels Using Lattice-Basis Reduction
A simple scheme for communication over MIMO broadcast channels is introduced
which adopts the lattice reduction technique to improve the naive channel
inversion method. Lattice basis reduction helps us to reduce the average
transmitted energy by modifying the region which includes the constellation
points. Simulation results show that the proposed scheme performs well, and as
compared to the more complex methods (such as the perturbation method) has a
negligible loss. Moreover, the proposed method is extended to the case of
different rates for different users. The asymptotic behavior of the symbol
error rate of the proposed method and the perturbation technique, and also the
outage probability for the case of fixed-rate users is analyzed. It is shown
that the proposed method, based on LLL lattice reduction, achieves the optimum
asymptotic slope of symbol-error-rate (called the precoding diversity). Also,
the outage probability for the case of fixed sum-rate is analyzed.Comment: Submitted to IEEE Trans. on Info. Theory (Jan. 15, 2006), Revised
(Jun. 12, 2007
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