This paper considers the use of an antenna selection mechanism to reduce the cost of multiple analog transmit/receive chains in multiple-input multiple-output (MIMO) systems. With the optimal antenna selection scheme, radio-frequency chains can optimally connect with the best subset of transmitter and/or receiver antennas. However, the optimal antenna selection algorithm requires an exhaustive search of all possible combinations to find the optimum subset at the transmitter and/or receiver, thus resulting in high complexity. In order to reduce the computational load while still maximizing channel capacity, we introduce the simulated annealing (SA) method, an effective algorithm that solves various combinatorial optimization problems, to search the optimal subset. The simulation results show that the performance of the proposed SA method provides almost the same channel capacity as that of the optimal exhaustive search algorithm while maintaining low complexity.
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Jung-Chieh CHEN, "A Low-Complexity Antenna Selection Scheme in MIMO Systems" in IEICE TRANSACTIONS on Fundamentals,
vol. E93-A, no. 3, pp. 651-655, March 2010, doi: 10.1587/transfun.E93.A.651.
Abstract: This paper considers the use of an antenna selection mechanism to reduce the cost of multiple analog transmit/receive chains in multiple-input multiple-output (MIMO) systems. With the optimal antenna selection scheme, radio-frequency chains can optimally connect with the best subset of transmitter and/or receiver antennas. However, the optimal antenna selection algorithm requires an exhaustive search of all possible combinations to find the optimum subset at the transmitter and/or receiver, thus resulting in high complexity. In order to reduce the computational load while still maximizing channel capacity, we introduce the simulated annealing (SA) method, an effective algorithm that solves various combinatorial optimization problems, to search the optimal subset. The simulation results show that the performance of the proposed SA method provides almost the same channel capacity as that of the optimal exhaustive search algorithm while maintaining low complexity.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E93.A.651/_p
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@ARTICLE{e93-a_3_651,
author={Jung-Chieh CHEN, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Low-Complexity Antenna Selection Scheme in MIMO Systems},
year={2010},
volume={E93-A},
number={3},
pages={651-655},
abstract={This paper considers the use of an antenna selection mechanism to reduce the cost of multiple analog transmit/receive chains in multiple-input multiple-output (MIMO) systems. With the optimal antenna selection scheme, radio-frequency chains can optimally connect with the best subset of transmitter and/or receiver antennas. However, the optimal antenna selection algorithm requires an exhaustive search of all possible combinations to find the optimum subset at the transmitter and/or receiver, thus resulting in high complexity. In order to reduce the computational load while still maximizing channel capacity, we introduce the simulated annealing (SA) method, an effective algorithm that solves various combinatorial optimization problems, to search the optimal subset. The simulation results show that the performance of the proposed SA method provides almost the same channel capacity as that of the optimal exhaustive search algorithm while maintaining low complexity.},
keywords={},
doi={10.1587/transfun.E93.A.651},
ISSN={1745-1337},
month={March},}
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TY - JOUR
TI - A Low-Complexity Antenna Selection Scheme in MIMO Systems
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 651
EP - 655
AU - Jung-Chieh CHEN
PY - 2010
DO - 10.1587/transfun.E93.A.651
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E93-A
IS - 3
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - March 2010
AB - This paper considers the use of an antenna selection mechanism to reduce the cost of multiple analog transmit/receive chains in multiple-input multiple-output (MIMO) systems. With the optimal antenna selection scheme, radio-frequency chains can optimally connect with the best subset of transmitter and/or receiver antennas. However, the optimal antenna selection algorithm requires an exhaustive search of all possible combinations to find the optimum subset at the transmitter and/or receiver, thus resulting in high complexity. In order to reduce the computational load while still maximizing channel capacity, we introduce the simulated annealing (SA) method, an effective algorithm that solves various combinatorial optimization problems, to search the optimal subset. The simulation results show that the performance of the proposed SA method provides almost the same channel capacity as that of the optimal exhaustive search algorithm while maintaining low complexity.
ER -