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Exploiting multiuser diversity with only 1–bit feedback
 in Proc. IEEE Wireless Commun. and Networking Conf
, 2005
"... Abstract — In a system with n users, the sumrate capacity of the downlink channel grows as log log n, assuming optimal scheduling. However, optimal scheduling requires that the downlink channel state information (CSI) for all users be fully available at the base station. In this paper we show that ..."
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Cited by 32 (2 self)
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Abstract — In a system with n users, the sumrate capacity of the downlink channel grows as log log n, assuming optimal scheduling. However, optimal scheduling requires that the downlink channel state information (CSI) for all users be fully available at the base station. In this paper we show that the same capacity growth holds even if the feedback rate from the mobiles to the base station is reduced to one bit. We propose a simple scheduling method to achieve this multiuser capacity and furthermore we show that by a judicious choice of the onebit quantizer, not only the growth rate, but also most of the capacity of a fully informed system can be preserved. I.
Capacity maximizing algorithms for joint transmitreceive antenna selection
 Asilomar Conference on Signals, Systems and Computers
, 2004
"... Abstract — In this paper, we study and compare two algorithms for transmit/receive antenna selection in MIMO channels. Generally the only way to assure optimality in antenna selection is exhaustive search, however, this constitutes an unacceptable burden on the receiver. We describe two suboptimal a ..."
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Cited by 6 (0 self)
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Abstract — In this paper, we study and compare two algorithms for transmit/receive antenna selection in MIMO channels. Generally the only way to assure optimality in antenna selection is exhaustive search, however, this constitutes an unacceptable burden on the receiver. We describe two suboptimal algorithms in this paper. First, a separable Tx/Rx successive selection, which has excellent performance but has complexity that grows as a quadratic function of the number of antennas. Second, an algorithm that entertwines transmit and receive side selection, which has linear complexity in the number of antennas, and only a small performance penalty compared with the first algorithm. we validate the results using simulations. 1 I.
1 Capacity of MIMO Channels with Antenna Selection
"... We explore the capacity of MIMO channels in the presence of antenna selection. Antenna selection reduces the complexity of the radio devices and requires only a small amount of channel state feedback to the transmit side. For high SNR, we define the capacity gain as the constant term in the expansio ..."
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We explore the capacity of MIMO channels in the presence of antenna selection. Antenna selection reduces the complexity of the radio devices and requires only a small amount of channel state feedback to the transmit side. For high SNR, we define the capacity gain as the constant term in the expansion of the ergodic capacity in terms of SNR. We show that this value is representative of the channel state information (CSI) at the transmitter. We investigate the asymptotic behavior of the capacity gain for
Capacity of MIMO channels with antenna selection
 IEEE Trans. Inf. Theory
"... Abstract—This correspondence studies the capacity of multipleinput–multipleoutput (MIMO) channels in the presence of antenna selection. Antenna selection reduces the complexity of the radio devices and requires only a small amount of channel state feedback. For high signaltonoise ratio (SNR), we ..."
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Abstract—This correspondence studies the capacity of multipleinput–multipleoutput (MIMO) channels in the presence of antenna selection. Antenna selection reduces the complexity of the radio devices and requires only a small amount of channel state feedback. For high signaltonoise ratio (SNR), we define excess rate as the constant term in the expansion of the ergodic capacity in terms of SNR. It is shown that this value is representative of the channel state information (CSI) at the transmitter. The asymptotic behavior of the excess rate is then analyzed for three cases: complete CSI, no CSI, and partial CSI at transmitter (antenna selection). While waterfilling provides a excess rate that increases logarithmically in w (the number of transmit antennas), the excess rate of transmit antenna selection behaves only like ���@�� � w A. For the low SNR case, we use the concept of channel gain, a measure introduced by Verdú. We show that channel gain for antenna selection increases only logarithmically in w as opposed to waterfilling channel gain which increases linearly in w. The same techniques are also applied to the receive selection, and corresponding results are noted in high and lowSNR regimes. The methodology developed in this correspondence, although motivated by antenna selection, is fairly general and can be used for any system where partial CSI is available at the MIMO transmitter. Index Terms—Antenna selection, capacity scaling, channel state information (CSI), multipleinput–multipleoutput (MIMO). I.
1Energy Efficiency of LargeScale Multiple Antenna Systems with Transmit Antenna Selection
"... Abstract—In this paper, we perform transmit antenna selection to improve the energy efficiency of large scale multiple antenna systems. We derive a good approximation of the distribution of the mutual information in this antenna selection system. It shows that channel hardening phenomenon is still r ..."
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Abstract—In this paper, we perform transmit antenna selection to improve the energy efficiency of large scale multiple antenna systems. We derive a good approximation of the distribution of the mutual information in this antenna selection system. It shows that channel hardening phenomenon is still retained as full complexity with antenna selection. Then, we use this closedform expression to assess the energy efficiency performance. Specifically, we evaluate the performance of the energy efficiency in two different cases: 1) the circuit power consumption is comparable to or even dominates the transmit power, and 2) the circuit power can be ignored due to relatively much higher transmit power. The theoretical analysis indicates that there exists an optimal number of selected antennas to maximize the energy efficiency in the first case, whereas in the second case, the energy efficiency is maximized when all the available antennas are used. Based on these conclusions, two simple but efficient antenna selection algorithms are proposed to obtain the maximum energy efficiency. All the analytical results are verified through computer simulations. Index Terms—Large scale multiple antenna system, transmit antenna selection, channel hardening, energy efficiency, selection algorithms. I.