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Compressed Sensing-Aided Downlink Channel Training for FDD Massive MIMO Systems
Yonghee Han,Jungwoo Lee,Love, David J. Institute of Electrical and Electronics Engineers 2017 IEEE Transactions on Communications Vol. No.
<P>There is much discussion in industry and academia about possible technical solutions to address the growth in demand for wireless broadband. Massive multiple-input multiple-output (MIMO) systems are one of the most popular solutions to addressing this broadband demand in fifth generation (5G) cellular systems. Massive MIMO systems employ tens or hundreds of antennas at the base station to enable advanced multiuser MIMO communications. To reap the massive MIMO throughput gain, coherent transmission exploiting accurate channel state information at the transmitter is required. While it is expected that many 5G systems will employ frequency division duplexing (FDD), channel sounding for FDD systems requires a large pilot overhead, which usually scales proportionally to the number of transmit antennas. To resolve this problem, a compressed sensing (CS)-aided channel estimation scheme is proposed, which exploits the observation that the channel statistics change slowly in time. By utilizing a conventional least squares approach and a CS technique simultaneously, the proposed scheme reduces the pilot overhead. Simulation results show that the proposed scheme can estimate the channel with a reduced pilot overhead even when conventional CS cannot be applied.</P>
Projection-Based Differential Feedback for FDD Massive MIMO Systems
Han, Yonghee,Shin, Wonjae,Lee, Jungwoo IEEE 2017 IEEE Transactions on Vehicular Technology VT Vol.66 No.1
<P>Channel state information at the transmitter (CSIT) plays a key role in achieving potential gain of massive multiple-input–multiple-output (MIMO) systems. In frequency-division duplex (FDD) systems, CSIT can be obtained through feedback from the receiver. Conventional limited feedback schemes, which have been designed for small-scale MIMO systems, suffer from a prohibitive amount of feedback requirement and encoding complexity when the number of transmit antennas becomes massive. In this paper, a projection-based differential feedback (PBDF) protocol is proposed for FDD massive MIMO systems. In the PBDF framework, the difference between original and predicted vectors is projected, and quantization is performed in a smaller dimensional subspace. With an appropriate projection exploiting spatial and temporal correlation of massive MIMO channels, the feedback amount and encoding complexity can be significantly reduced. The simulation results show that the proposed scheme achieves a large portion of potential throughput gain of massive MIMO systems with a small amount of channel feedback.</P>
Uplink Pilot Design for Multi-Cell Massive MIMO Networks
Han, Yonghee,Lee, Jungwoo IEEE 2016 IEEE communications letters Vol.20 No.8
<P>In massive multiple-input multiple-output (MIMO) systems, the effect of inter-user interference and noise can be suppressed through simple signal processing techniques. However, pilot contamination, which results from the use of a correlated pilot, causes performance bottleneck for massive MIMO networks. In this letter, a pilot design algorithm based on alternating minimization is developed to alleviate the pilot contamination in multi-cell massive MIMO systems. Contrary to the existing pilot reuse protocols that restrict the pilot length to be an integer multiple of the number of users, the proposed method designs a pilot with an arbitrary length. Hence, pilot sequence can be designed more flexibly to maximize spectral efficiency.</P>
Han, YongHee,Mun, ChiWoong Wiley Subscription Services, Inc., A Wiley Company 2011 Journal of magnetic resonance imaging Vol.34 No.5
<P><B>Abstract</B></P><P><B>Purpose:</B></P><P>To evaluate the temporal and spatial resolution of magnetic resonance (MR) temperature imaging when using the proton resonance frequency (PRF) method combined with the keyhole technique.</P><P><B>Materials and Methods:</B></P><P>Tissue‐mimicking phantom and swine muscle tissue were microwave‐heated by a coaxial slot antenna. For the sake of MR hardware safety, MR images were sequentially acquired after heating the subjects using a spoiled gradient (SPGR) pulse sequence. Reference raw (<I>k</I>‐space) data were collected before heating the subjects. Keyhole temperature images were reconstructed from full <I>k</I>‐space data synthesized by combining the peripheral phase‐encoding part of the reference raw data and the center phase‐encoding keyhole part of the time sequential raw data. Each keyhole image was analyzed with thermal error, and the signal‐to‐noise ratio (SNR) was compared with the self‐reference (nonkeyhole) images according to the number of keyhole phase‐encoding (keyhole‐data size) portions.</P><P><B>Results:</B></P><P>In applied keyhole temperature images, smaller keyhole‐data sizes led to more temperature error increases, but the SNR did not decreased comparably. Additionally, keyhole images with a keyhole‐data size of <16 had significantly different temperatures compared with fully phase‐encoded self‐reference images (<I>P</I> < 0.05).</P><P><B>Conclusion:</B></P><P>The keyhole technique combined with the PRF method improves temporal resolution and SNR in the measurement of the temperature in the deeper parts of body in real time. J. Magn. Reson. Imaging 2011;. © 2011 Wiley Periodicals, Inc.</P>