I. Hwang

University of Texas at Austin, Austin, Texas, United States

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Publications (3)2.41 Total impact

  • C. You, I.-T. Hwang
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    ABSTRACT: The authors propose a joint dirty-paper coding (DPC) and beamforming scheme for use in multiuser multiple-input multiple-output (MIMO) systems. Unlike conventional maximum likelihood (ML)-based DPC schemes, this joint DPC and beamforming precoding scheme is intended as a suboptimal strategy in that it cancels only causal interference, thus offering a practical implementation option. In addition, a signal-to-interference plus noise ratio (SINR)-based ordering strategy that can be readily applied to conventional DPC schemes is also proposed as a way of improving the performance of the joint precoding scheme. The proposed schemes markedly improve classical spatial division multiple access (SDMA), and achieve the same data rates as spatial multiplexing (SM) for all users, but with significantly superior performance/diversity gain. When the number of active users per sector is much greater than the number of transmit antennas, the proposed schemes are able to achieve enough multiuser diversity to asymptotically approach the optimal DPC capacity. In addition, unlike BLAST, the receivers do not need to know each other's vector channels. Simulation results confirm that the proposed schemes provide significant gain over conventional zero-forcing SDMA in terms of average sector throughput for downlink multi-cell multiuser systems and symbol error rate as well. Finally, the proposed interference cancellation strategies at the transmitter can be expandable to MIMO systems with any number of multiple antennas.
    IET Communications 11/2010; · 0.72 Impact Factor
  • C. You, I. Hwang, Y. Kim, V. Tarokh
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    ABSTRACT: A simple antenna selection strategy for multiple-input multiple-output wireless systems with partial feedback is presented. In the proposed scheme, both transmit and receive antenna selection are done at the receiver, significantly reducing feedback information. In addition, this scheme uses row/column probability density function for antenna selection to reduce computational complexity without performance degradation. Unlike other schemes, two different antenna selection algorithms are used in high and low signal-to-noise ratio regimes, respectively, achieving additional performance gain in comparison to the single antenna selection algorithm. Simulation results show that the proposed scheme nearly approaches the optimal closed-loop capacity (known as water-filling capacity) as random selection round for antenna selection increases.
    IET Microwaves Antennas & Propagation 10/2009; · 0.97 Impact Factor
  • I. Hwang, C. You, Y. Kim, V. Tarokh
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    ABSTRACT: A novel downlink transmission rate-control and feedback reduction strategy for closed-loop multiple-input multiple-output (MIMO) multiple-input multiple-output wireless systems is presented. Unlike conventional systems that use signal to interference plus noise ratio at the receiver as an indicator of channel quality, we propose using instantaneous MIMO capacity as an indicator for the downlink transmission rate-control. A set of instantaneous capacity thresholds is first chosen such that the expected weighted capacity loss because of thresholding effects are minimised. While computing the thresholds, we also consider the quality of service and weight function to meet different traffics and user needs. Then a set of codebooks can be constructed minimising the overall capacity loss with given quality of service constraint. Simulation results show that, with only four data rate-control bits, our algorithm gives only 12% capacity loss in 4 times 4 MIMO systems and almost twice better than the current IS-856 standard in single-input single-output systems. In case of 5-bit feedback scenario, the proposed algorithm outperforms conventional systems by minimising instantaneous capacity loss.
    IET Communications 05/2009; · 0.72 Impact Factor