19 research outputs found
Asymptotics of Nonlinear LSE Precoders with Applications to Transmit Antenna Selection
This paper studies the large-system performance of Least Square Error (LSE)
precoders which~minimize~the~input-output distortion over an arbitrary support
subject to a general penalty function. The asymptotics are determined via the
replica method in a general form which encloses the Replica Symmetric (RS) and
Replica Symmetry Breaking (RSB) ans\"atze. As a result, the "marginal
decoupling property" of LSE precoders for -steps of RSB is derived. The
generality of the studied setup enables us to address special cases in which
the number of active transmit antennas are constrained. Our numerical
investigations depict that the computationally efficient forms of LSE precoders
based on "-norm" minimization perform close to the cases with
"zero-norm" penalty function which have a considerable improvements compared to
the random antenna selection. For the case with BPSK signals and restricted
number of active antennas, the results show that RS fails to predict the
performance while the RSB ansatz is consistent with theoretical bounds.Comment: 5 pages; 2 figures; to be presented at ISIT 201
Generalised MBER-based vector precoding design for multiuser transmission
We propose a generalized vector precoding (VP) design based on the minimum bit error rate (MBER) criterion for multiuser transmission in the downlink of a multiuser system, where the base station (BS) equipped with multiple transmitting antennas communicates with single-receiving-antenna mobile station (MS) receivers each having a modulo device. Given the knowledge of the channel state information and the current information symbol vector to be transmitted, our scheme directly generates the effective symbol vector based on the MBER criterion using the particle swarm optimization (PSO) algorithm. The proposed PSO-aided generalized MBER VP scheme is shown to outperform the powerful minimum mean-square-error (MMSE) VP and improved MMSE-VP benchmarks, particularly for rank-deficient systems, where the number of BS transmitting antennas is lower than the number of MSs supported
Transceiver design with vector perturbation technique and iterative power loading
In this paper we consider the optimization of transceivers which use the nonlinear vector perturbation technique at the transmitter. Since the perturbation vector can be almost totally removed at the receiver, the transmitter can use this extra freedom to reduce the transmitted power while maintaining the performance. The two cases considered in this paper are linear transceivers and transceivers with decision feedback (DFE). For both cases, efficient iterative power loading algorithms are developed to reduce the average bit error rate under the total transmitted power constraint. We present simulation results showing that the proposed technique performs better than the existing state-of-the-art uniform channel decomposition (UCD) system and the vector perturbation (VP) precoder
Secrecy Sum-Rates for Multi-User MIMO Regularized Channel Inversion Precoding
In this paper, we propose a linear precoder for the downlink of a multi-user
MIMO system with multiple users that potentially act as eavesdroppers. The
proposed precoder is based on regularized channel inversion (RCI) with a
regularization parameter and power allocation vector chosen in such a
way that the achievable secrecy sum-rate is maximized. We consider the
worst-case scenario for the multi-user MIMO system, where the transmitter
assumes users cooperate to eavesdrop on other users. We derive the achievable
secrecy sum-rate and obtain the closed-form expression for the optimal
regularization parameter of the precoder using
large-system analysis. We show that the RCI precoder with
outperforms several other linear precoding schemes, and
it achieves a secrecy sum-rate that has same scaling factor as the sum-rate
achieved by the optimum RCI precoder without secrecy requirements. We propose a
power allocation algorithm to maximize the secrecy sum-rate for fixed .
We then extend our algorithm to maximize the secrecy sum-rate by jointly
optimizing and the power allocation vector. The jointly optimized
precoder outperforms RCI with and equal power allocation
by up to 20 percent at practical values of the signal-to-noise ratio and for 4
users and 4 transmit antennas.Comment: IEEE Transactions on Communications, accepted for publicatio
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
Hybrid TH-VP Precoding for Multi-User MIMO
Vector perturbation (VP) is a nonlinear precoding technique that achieves near-capacity performance in multiuser multiple-input multiple-output systems at the expense of large complexity due to the search for the optimum perturbation vector. In this paper, we present the hybrid TomlinsonâHarashima VP (TH-VP) algorithm, a novel zero-forcing pre coding scheme, which combines TH precoding to remove interuser interference, and VP precoding to equalize each userâs multiple spatial streams. We show that the two nonlinear techniques can be integrated in a single optimization and that the proposed algorithm has lower computational requirements than any other. The performance of TH-VP is analyzed and simulation results show that TH-VP outperforms conventional zero-forcing VP and approaches the performance of dirty paper coding