Hakjea Sung

Generalized channel inversion methods for multiuser MIMO systems

Block diagonalization (BD) is a well-known precoding method in multiuser multi-input multi-output (MIMO) broadcast channels. This scheme can be considered as a extension of the zero-forcing (ZF) channel inversion to the case where each receiver is equipped with multiple antennas. One of the limitation of the BD is that the sum rate does not grow linearly with the number of users and transmit antennas at low and medium signal-to-noise ratio regime, since the complete suppression of multi-user interference is achieved at the expense of noise enhancement. Also it performs poorly under imperfect channel state information. In this paper, we propose a generalized minimum mean-squared error (MMSE) channel inversion algorithm for users with multiple antennas to overcome the drawbacks of the BD for multiuser MIMO systems. We first introduce a generalized ZF channel inversion algorithm as a new approach of the conventional BD. Applying this idea to the MMSE channel inversion for identifying orthonormal basis vectors of the precoder, and employing the MMSE criterion for finding its combining matrix, the proposed scheme increases the signal-to-interference-plus-noise ratio at each users receiver. Simulation results confirm that the proposed scheme exhibits a linear growth of the sum rate, as opposed to the BD scheme. For block fading channels with four transmit antennas, the proposed scheme provides a 3 dB gain over the conventional BD scheme at 1% frame error rate. Also, we present a modified precoding method for systems with channel estimation errors and show that the proposed algorithm is robust to channel estimation errors.

Joint Optimization for One and Two-Way MIMO AF Multiple-Relay Systems

This paper considers both one-way and two-way relaying systems with multiple relays between two terminal nodes where all nodes have multiple-input multiple-output (MIMO) antennas. We propose a unified algorithm which computes the optimal linear transceivers jointly at the source node and the relay nodes for amplify-and-forward (AF) protocols. First, optimization designs based on the sum-rate and the mean-square error (MSE) criteria are formulated for the two-way AF relaying channel. Due to non-convexity of the given problems, the proposed schemes iteratively identify local-optimal source and relay filters by deriving the gradients of the cost functions for a gradient descent algorithm. Then, the proposed algorithm can optimize a one-way multiple relay system as a special case of the two-way channel. Finally, we prove the global optimality of the maximum sum-rate scheme under an asymptotically large antenna assumption. From simulation results, it is confirmed that the proposed methods yield the near optimum result for the MIMO multiple relay channel even with a moderate number of antennas. Consequently, we show that the proposed algorithm outperforms conventional schemes in terms of the sum-rate and the error performance for both one-way and two-way protocols.

Linear precoder designs for K-user interference channels

This paper studies linear precoding and decoding schemes for K-user interference channel systems. It was shown by Cadambe and Jafar that the interference alignment (IA) algorithm achieves a theoretical bound on degrees of freedom (DOF) for interference channel systems. Based on this, we first introduce a non-iterative solution for the precoding and decoding scheme. To this end, we determine the orthonormal basis vectors of each users precoding matrix to achieve the maximum DOF, then we optimize precoding matrices in the IA method according to two different decoding schemes with respect to individual rate. Second, an iterative processing algorithm is proposed which maximizes the weighted sum rate. Deriving the gradient of the weighted sum rate and applying the gradient descent method, the proposed scheme identifies a local-optimal solution iteratively. Simulation results show that the proposed iterative algorithm outperforms other existing methods in terms of sum rate. Also, we exhibit that the proposed non-iterative method approaches a local optimal solution at high signal-to-noise ratio with reduced complexity.

Sum-Rate Maximization for Two-Way MIMO Amplify-and-Forward Relaying Systems

This paper considers two-way relaying systems with a multiple-input multiple-output (MIMO) relay between two MIMO terminal nodes. The two-way relaying protocol can en- hance the spectral efficiency compared with the one-way protocol by compensating the loss from half-duplex signaling. In this paper, we propose an iterative scheme to find a relay weighting matrix maximizing the sum-rate for two-way relay channels. Due to the non-convexity of the given problem, the proposed scheme iteratively identifies a local optimal solution by deriving the gradient of the sum-rate and applying the gradient descent algorithm. Simulation results show that the proposed iterative scheme with provable convergence achieves a near-optimal sum- rate for the two-way MIMO relay channels. Also, we show that the proposed scheme with a few iterations still outperforms the conventional schemes.

Sum Rate Analysis of Two-Cell MIMO Broadcast Channels: Spatial Multiplexing Gain

In this paper, we provide a precise expression of the spatial multiplexing gain (SMG) for two mutually interfering multiple-input multiple-output (MIMO) broadcast channels using linear transceiver, referred to as MIMO-IBC. The MIMO-IBC has two base stations and

Linear Precoder Designs for Cognitive Radio Multiuser MIMO Downlink Systems

K_1

A Two-Stage Precoding Method Based on Interference Alignment for Interference Channel Systems

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Spatial Multiplexing Gain for Two Interfering MIMO Broadcast Channels Based on Linear Transceiver

K_2

Regularized Transceiver Designs for Multi-User MIMO Interference Channels

users, each equipped with multiple antennas, where independent messages are transmitted over fixed channels. We observe the variation of the SMG with respect to user antenna distribution, and compare the derived result to the SMG of the interference channel with full cooperation among users. Additionally, we propose a linear precoding and decoding scheme for the MIMO-IBC in terms of maximizing the total sum rate, by extending one designed for single-cell multiple-input single-output broadcast channels. Simulation results confirm the accuracy of our theoretical SMG analysis for the MIMO-IBC.

An MMSE Based Block Diagonalization for Multiuser MIMO Downlink Channels with Other Cell Interference

In this paper, we develop linear precoding methods for cognitive radio (CR) multi-user multiple-input multiple-output (MU-MIMO) broadcast systems where unlicensed secondary users (SUs) simultaneously use the same spectrum of the licensed primary user (PU). When the zero-forcing block diagonalization (ZF-BD) precoder is extended to the CR network, a noise enhancement problem occurs. Therefore, we propose a regularized BD precoder based on the minimum mean-square error (MMSE) criteria subject to zero interference constraint for the PU. As a result, the proposed MMSE-BD scheme improves the signal-to-interference-plus-noise ratio at each SUs receiver compared to the ZF-BD based method. Simulation results demonstrate that the proposed algorithm outperforms the ZF based technique by more than 5 dB at the sum-rate 10 bps/Hz for CR MU-MIMO downlink systems.