[1] J. A. C. Bingham, “Multicarrier modulation for data transmission: An idea whose time has come,” IEEE Commun. Mag., vol. 28, no. 5, pp. 5–14, May 1990. [2] L. Hanzo, M. Münster, B. J. Choi, and T. Keller, OFDM and MC-CDMA for Broadband Multi-User Communications, WLANs, and Broadcasting. Chichester, U.K.: Wiley, 2003. [3] A. A. M. Saleh, “Frequency-independent and frequency-dependent nonlinear models of TWT amplifiers,” IEEE Trans. Commun., vol. COM-29, no. 11, pp. 1715–1720, Nov. 1981. [4] M. Honkanen and S.-G. Häggman, “New aspects on nonlinear power amplifier modeling in radio communication system simulations,” in Proc. PIMRC’97, Helsinki, Finland, Sep. 1–4, 1997, pp. 844–848. [5] C. J. Clark, G. Chrisikos, M. S. Muha, A. A. Moulthrop, and C. P. Silva, “Time-domain envelope measurement technique with application to wideband power amplifier modeling,” IEEE Trans. Microw. Theory Tech., vol. 46, no. 12, pp. 2531–2540, Dec. 1998. [6] C.-S. Choi et al., “RF Impairment Models 60 GHz Band SYS/PHY Simulation,” Document IEEE 802.15-06-0477-01-003c, Nov. 2006 [Online]. Available: https://mentor.ieee.org/802.15/dcn/06/15-06- 0477-01-003c-rf-impairment-models-60ghz-band-sysphy-simulation. pdf [7] V. Erceg et al., “60 GHz Impairments Modeling,” Document IEEE 802.11-09/1213r1, Nov. 2009. [8] L. Ding, G. T. Zhou, D. R. Morgan, Z. Ma, J. S. Kenney, J. Kim, and C. R. Giardina, “A robust digital baseband predistorter constructed using memory polynomials,” IEEE Trans. Commun., vol. 52, no. 1, pp. 159–165, Jan. 2004. [9] D. Zhou and V. E. DeBrunner, “Novel adaptive nonlinear predistorters based on the direct learning algorithm,” IEEE Trans. Signal Process., vol. 55, no. 1, pp. 120–133, Jan. 2007. [10] M.-C. Chiu, C.-H. Zeng, and M.-C. Liu, “Predistorter based on frequency domain estimation for compensation of nonlinear distortion in OFDM systems,” IEEE Trans. Veh. Technol., vol. 57, no. 2, pp. 882–892, Mar. 2008. [11] S. Choi, E.-R. Jeong, and Y. H. Lee, “Adaptive predistortionwith direct learning based on piecewise linear approximation of amplifier nonlinearity,” IEEE J. Sel. Topics Signal Process., vol. 3, no. 3, pp. 397–404, Jun. 2009. [12] V. P. G. Jiménez, Y. Jabrane, A. G. Armada, and B. A. E. Said, “High power amplifier pre-distorter based on neural-fuzzy systems for OFDM signals,” IEEE Trans. Broadcast., vol. 57, no. 1, pp. 149–158, Mar. 2011. [13] S. Chen, “An efficient predistorter design for compensating nonlinear memory high power amplifier,” IEEE Trans. Broadcast., vol. 57, no. 4, pp. 856–865, Dec. 2011. [14] S. Chen, X. Hong, Y. Gong, and C. J. Harris, “Digital predistorter design using B-spline neural network and inverse of De Boor algorithm,” IEEE Trans. Circuits Syst. I, Reg. Papers, vol. 60, no. 6, pp. 1584–1594, Jun. 2013. [15] X. Hong, S. Chen, and C. J. Harris, “Complex-valued B-spline neural networks for modeling and inverse of Wiener systems,” in Complex- Valued Neural Networks: Advances and Applications, A.Hirose,Ed. Hoboken, NJ, USA: Wiley, 2013, ch. 9, pp. 209–233. [16] X. Hong and S. Chen, “Modeling of complex-valued Wiener systems using B-spline neural network,” IEEE Trans. Neural Netw., vol. 22, no. 5, pp. 818–825, May 2011. [17] C. De Boor, A Practical Guide to Splines. NewYork,NY,USA: Spring Verlag, 1978. [18] C. J. Harris, X. Hong, and Q. Gan, Adaptive Modelling, Estimation and Fusion From Data: A Neurofuzzy Approach. Berlin, Germany: Springer-Verlag, 2002. [19] J. M. Pena, “B-spline and optimal stability,” Math. Comput., vol. 66, no. 220, pp. 1555–1560, Oct. 1997. [20] T. Lyche and J. M. Pena, “Optimally stable multivariate bases,” Adv. Comput. Math., vol. 20, no. 1–3, pp. 149–159, Jan. 2004. [21] E. Mainar and J.M. Pena, “Optimal stability of bivariate tensor product B-bases,” J. Numer. Anal., Ind. Appl.Math., vol. 6, no. 3–4, pp. 95–104, 2011. [22] A. V. Ivanov, “An asymptotic expansion for the distribution of the least squares estimator of the non-linear regression parameter,” SIAM Theory Probabil. Its Appl., vol. 21, no. 3, pp. 557–570, 1977. [23] C.-F. Wu, “Asymptotic theory of nonlinear least squares estimation,” Ann. Statist., vol. 9, no. 3, pp. 501–513, 1981. [24] Z. Q. Luo and P. Tseng, “On the convergence of the coordinate descent method for convex differentiable minimization,” J. Optimiz. Theory Appl., vol. 72, no. 1, pp. 7–35, Jan. 1991. [25] R. J. Hathaway and J. C. Bezdek, “Grouped coordinate minimization using Newton’s method for inexact minimization in one vector coordinate,” J. Optimiz. Theory Appl., vol. 71, no. 3, pp. 503–516, Dec. 1991. [26] C. R. Lahmeyer and K.-M. Cheung, “Long Decoding Runs for Galileo’s Convolutional Codes,” The Interplanetary Network Progress Report 42-95, Nov. 15, 1988 [Online]. Available: http://ipnpr.jpl.nasa.gov/progress_report/42-95/95M.PDF