Abstract
Antenna selection in Multiple input Multiple Output (MIMO) is a signal processing method in which the elements of Radio Frequency (RF) chain are switched to their corresponding subset of antennas. Due to the large number of RF transceivers, antenna selection resolves the complexity and power consumption. In this paper, a sub-optimal antenna selection algorithm that combines two selection techniques is proposed. The algorithm leverages the use of minimum signal to noise ratio (SNR) at the cell edge and dynamic channel condition due to mobility. To apply fractional transmit power re-allocation at sub 6 GHz and mmWave frequencies, the same number of RF components are set to be active and the rest to sleep mode after adaptive selection. As a result, the branch in the array with the best signal quality is chosen and applied in iteration until the desired value is reached however re-selection boosts EE at the expense of total rate. In comparison to complete array consumption and random selection, the results show that the algorithm outperforms random selection and achieves higher energy efficiency. Furthermore, capacity loss due to selection is offset by using nonlinear precoding at the expense of complexity.
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References
Larsson, E.G., Tufvesson, F., Edfors, O., Marzetta, T.L.: Massive MIMO for next generation wireless systems, CoRR, vol. abs/1304.6690 (2013)
Auer, G., Van der Perre, L.: Challenges and enabling technologies for energy aware mobile radio networks. IEEE Commun. Mag. 48(11), 6672 (2010)
Heath, R.W., Sandhu, S., Paulraj, A.: Antenna selection for spatial multiplexing systems with linear receivers. IEEE Commun. Lett. 5(4), 142–144 (2001)
Correia, L., et al.: Challenges and enabling technologies for energy aware mobile radio networks. IEEE Commun. Mag. 48(11), 66–72 (2010)
Gharavi-Alkhansari, M., Gershman, A.B.: Fast antenna subset selection in MIMO systems. IEEE Trans. Signal Process. 52(2), 339–347 (2004)
Dua, A., Medepalli, K., Paulraj, A.J.: Receive antenna selection in MIMO systems using convex optimization. IEEE Trans. Wireless Commun. 5(9), 2353–2357 (2006)
Wang, B., Hui, T., Leong, M.S.: Global and fast receiver antenna selection for IMO systems. IEEE Trans. Common. 58(9), 2505–2510 (2006)
Xu, Z., Sfar, S., Blum, R.S.: Analysis of MIMO systems with receive antenna selection in spatially correlated Rayleigh fading channels. IEEE Trans. Veh. Technol. 58(1), 251–262 (2009)
Masouros, C., Alsusa, E.: Dynamic linear precoding for the exploitation of known interference in MIMO broadcast systems. IEEE Trans. Wireless Commun. 8(3), 1396–1404 (2009)
Gesbert, M.: Soft linear precoding for the downlink of DS/CDMA communication systems. IEEE Trans. Veh. Technol. 59(1), 203–215 (2010)
Xiang, G., Edfors, O., Liu, J., Tufvesson, F.: Antenna selection in measured massive MIMO channels using convex optimization. In: IEEE GLOBECOM Workshop, Atlanta, Georgia, United States (2013)
Gao, X., Edfors, O., Rusek, F., Tufvesson, F.: Massive MIMO performance evaluation based on measured propagation data. IEEE Trans. Wireless Commun. 14(7), 3899–3911 (2015)
Rappaport, T.: Wireless Communications: Principles and Practice, 2nd ed, Prentice Hall, Upper Saddle River (2002)
Molisch, A.F., Win, M.Z., Winters, J.H.: Capacity of MIMO systems with antenna selection. IEEE Trans. Wireless Commun. 4(4), 1759–1772 (2005)
Rappaport, T.: Wideband millimeter-wave propagation measurements and channel models for future wireless communication system design. IEEE Trans. Commun. 63(9), 3029–3056 (2015)
Guthy, C., Utschick, W., Honig, M.: Large system analysis of sum capacity in the gaussian MIMO broadcast channel. IEEE J. Sel. Areas Commun. 31(2), 149–159 (2013)
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Aredo, S.C., Negash, Y., Wondie, Y., Debo, F., Devadas, R., Fikadu, A. (2022). Optimal Transmit Antenna Selection for Massive MIMO Systems. In: Berihun, M.L. (eds) Advances of Science and Technology. ICAST 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 411. Springer, Cham. https://doi.org/10.1007/978-3-030-93709-6_9
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DOI: https://doi.org/10.1007/978-3-030-93709-6_9
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