Open Access

Capacity Performance of Adaptive Receive Antenna Subarray Formation for MIMO Systems

EURASIP Journal on Wireless Communications and Networking20072007:056471

DOI: 10.1155/2007/56471

Received: 15 November 2006

Accepted: 1 August 2007

Published: 13 December 2007


Antenna subarray formation is a novel RF preprocessing technique that reduces the hardware complexity of MIMO systems while alleviating the performance degradations of conventional antenna selection schemes. With this method, each RF chain is not allocated to a single antenna element, but instead to the complex-weighted and combined response of a subarray of elements. In this paper, we derive tight upper bounds on the ergodic capacity of the proposed technique for Rayleigh i.i.d. channels. Furthermore, we study the capacity performance of an analytical algorithm based on a Frobenius norm criterion when applied to both Rayleigh i.i.d. and measured MIMO channels.


Authors’ Affiliations

Wireless Communications Laboratory, Department of Technology Education and Digital Systems, University of Piraeus


  1. Gore DA, Nabar RU, Paulraj AJ: Selecting an optimal set of transmit antennas for a low rank matrix channel. Proceedings of IEEE Interntional Conference on Acoustics, Speech, and Signal Processing (ICASSP '00), June 2000, Istanbul, Turkey 5: 2785-2788.Google Scholar
  2. Blum RS, Winters JH: On optimum MIMO with antenna selection. IEEE Communications Letters 2002,6(8):322-324. 10.1109/LCOMM.2002.802050View ArticleGoogle Scholar
  3. Molisch AF, Win MZ, Choi Y-S, Winters JH: Capacity of MIMO systems with antenna selection. IEEE Transactions on Wireless Communications 2005,4(4):1759-1772.View ArticleGoogle Scholar
  4. Gorokhov A, Gore DA, Paulraj AJ: Receive antenna selection for MIMO spatial multiplexing: theory and algorithms. IEEE Transactions on Signal Processing 2003,51(11):2796-2807. 10.1109/TSP.2003.818204MathSciNetView ArticleMATHGoogle Scholar
  5. Gharavi-Alkhansari M, Gershman AB: Fast antenna subset selection in MIMO systems. IEEE Transactions on Signal Processing 2004,52(2):339-347. 10.1109/TSP.2003.821099MathSciNetView ArticleGoogle Scholar
  6. Gore DA, Paulraj AJ: MIMO antenna subset selection with space-time coding. IEEE Transactions on Signal Processing 2002,50(10):2580-2588. 10.1109/TSP.2002.803337View ArticleGoogle Scholar
  7. Heath RW Jr., Sandhu S, Paulraj AJ: Antenna selection for spatial multiplexing systems with linear receivers. IEEE Communications Letters 2001,5(4):142-144. 10.1109/4234.917094View ArticleGoogle Scholar
  8. Gore DA, Heath RW Jr., Paulraj AJ: Transmit selection in spatial multiplexing systems. IEEE Communications Letters 2002,6(11):491-493. 10.1109/LCOMM.2002.805517View ArticleGoogle Scholar
  9. Jensen MA, Morris ML: Efficient capacity-based antenna selection for MIMO Systems. IEEE Transactions on Vehicular Technology 2005,54(1):110-116. 10.1109/TVT.2004.838886View ArticleGoogle Scholar
  10. Molisch AF, Win MZ, Winter JH: Reduced-complexity transmit/receive-diversity systems. IEEE Transactions on Signal Processing 2003,51(11):2729-2738. 10.1109/TSP.2003.818211MathSciNetView ArticleGoogle Scholar
  11. Dai L, Sfar S, Letaief KB: Receive antenna selection for MIMO systems in correlated channels. Proceedings of the IEEE International Conference on Communications (ICC '04), June 2004, Paris, France 5: 2944-2948.Google Scholar
  12. Karamalis PD, Skentos ND, Kanatas AG: Selecting array configurations for MIMO systems: an evolutionary computation approach. IEEE Transactions on Wireless Communications 2004,3(6):1994-1998. 10.1109/TWC.2004.837447View ArticleGoogle Scholar
  13. Karamalis PD, Skentos ND, Kanatas AG: Adaptive antenna subarray formation for MIMO systems. IEEE Transactions on Wireless Communications 2006,5(11):2977-2982.View ArticleGoogle Scholar
  14. Raleigh GG, Cioffi JM: Spatio-temporal coding for wireless communication. IEEE Transactions on Communications 1998,46(3):357-366. 10.1109/26.662641View ArticleGoogle Scholar
  15. Scaglione A, Giannakis GB, Barbarossa S: Redundant filterbank precoders and equalizers—I: unification and optimal designs. IEEE Transactions on Signal Processing 1999,47(7):1988-2006. 10.1109/78.771047View ArticleGoogle Scholar
  16. Sampath H, Stoica P, Paulraj AJ: Generalized linear precoder and decoder design for MIMO channels using the weighted MMSE criterion. IEEE Transactions on Communications 2001,49(12):2198-2206. 10.1109/26.974266View ArticleGoogle Scholar
  17. Scaglione A, Stoica P, Barbarossa S, Giannakis GB, Sampath H: Optimal designs for space-time linear precoders and decoders. IEEE Transactions on Signal Processing 2002,50(5):1051-1064. 10.1109/78.995062View ArticleGoogle Scholar
  18. Palomar DP, Cioffi JM, Lagunas MA: Joint Tx-Rx beamforming design for multicarrier MIMO channels: a unified framework for convex optimization. IEEE Transactions on Signal Processing 2003,51(9):2381-2401. 10.1109/TSP.2003.815393View ArticleGoogle Scholar
  19. Mun C, Han J-K, Kim D-H: Quantized principal component selection precoding for limited feedback spatial multiplexing. Proceedings of the IEEE International Conference on Communications (ICC '06), June 2006, Istanbul, Turkey 4149-4154.Google Scholar
  20. Zhang X, Molisch AF, Kung S-Y: Variable-phase-shift-based RF-baseband codesign for MIMO antenna selection. IEEE Transactions on Signal Processing 2005,53(11):4091-4103.MathSciNetView ArticleGoogle Scholar
  21. Theofilakos P, Kanatas AG: Frobenius norm based receive antenna subarray formation for MIMO systems. Proceedings of the1st European Conference on Antennas and Propagation (EuCAP '06), November 2006, Nice, France 626:Google Scholar
  22. Theofilakos P, Kanatas AG: Reduced hardware complexity receive antenna subarray formation for MIMO systems based on frobenius norm criterion. Proceedings of the 3rd International Symposium on Wireless Communication Systems (ISWCS '06), September 2006, Valencia, SpainGoogle Scholar
  23. Theofilakos P, Kanatas AG: Robustness of receive antenna subarray formation to hardware and signal non-idealities. Proceedings of the 65th IEEE Vehicular Technology Conference (VTC '07), April 2007, Dublin, Ireland 324-328.Google Scholar
  24. Oyman O, Nabar RU, Bölcskei H, Paulraj AJ: Characterizing the statistical properties of mutual information in MIMO channels. IEEE Transactions on Signal Processing 2003,51(11):2784-2795. 10.1109/TSP.2003.818153MathSciNetView ArticleGoogle Scholar
  25. Neeser FD, Massey JL: Proper complex random processes with applications to information theory. IEEE Transactions on Information Theory 1993,39(4):1293-1302. 10.1109/18.243446MathSciNetView ArticleMATHGoogle Scholar
  26. Cover TM, Thomas JA: Elements of Information Theory. John Wiley & Sons, New York, NY, USA; 1991.View ArticleMATHGoogle Scholar
  27. Foschini GJ, Gans MJ: On limits of wireless communications in a fading environment when using multiple antennas. Wireless Personal Communications 1998,6(3):311-335. 10.1023/A:1008889222784View ArticleGoogle Scholar
  28. Papoulis A, Pillai SU: Probability, Random Variables and Stochastic Processes. 4th edition. McGraw-Hill, New York, NY, USA; 2002.Google Scholar
  29. Simon MK, Alouini M-S: Digital Communication over Fading Channels. 1st edition. John Wiley & Sons, New York, NY, USA; 2000.View ArticleGoogle Scholar
  30. Alouini M-S, Goldsmith AJ: Capacity of Rayleigh fading channels under different adaptive transmission and diversity-combining techniques. IEEE Transactions on Vehicular Technology 1999,48(4):1165-1181. 10.1109/25.775366View ArticleGoogle Scholar
  31. Skentos ND, Kanatas AG, Dallas PI, Constantinou P: MIMO channel characterization for short range fixed wireless propagation environments. Wireless Personal Communications 2006,36(4):339-361. 10.1007/s11277-005-9003-8View ArticleGoogle Scholar
  32. Horn RA, Johnson CR: Matrix Analysis. Cambridge University Press, Cambridge, UK; 1985.View ArticleMATHGoogle Scholar


© P. Theofilakos and A. G. Kanatas 2007

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