Impact of Factor Graph on Average Sum Rate for Uplink Sparse Code Multiple Access Systems

In this paper, we first study the average sum rate of sparse code multiple access (SCMA) systems, where a general scenario is considered under the assumption that the distances between the mobile users and the base station are not necessarily identical. Closed-form analytical results are derived for the average sum rate based on which an optimal factor graph matrix is designed for maximizing the capacity of the SCMA systems. Moreover, we propose a low-complexity iterative algorithm to facilitate the design of the optimal graph matrix. Finally, Monte Carlo simulations are provided to corroborate the accuracy of the theoretical results and the efficiency of the proposed iterative algorithm.

[1]  W. Marsden.  I and J , 2012 .

[2]  Yan Chen,et al.  Sparse code multiple access: An energy efficient uplink approach for 5G wireless systems , 2014, 2014 IEEE Global Communications Conference.

[3]  S. Nadarajah.  A Review of Results on Sums of Random Variables , 2008 .

[4]  Alireza Bayesteh,et al.  SCMA for downlink multiple access of 5G wireless networks , 2014, 2014 IEEE Global Communications Conference.

[5]  Alireza Bayesteh,et al.  SCMA for Open-Loop Joint Transmission CoMP , 2015, 2015 IEEE 82nd Vehicular Technology Conference (VTC2015-Fall).

[6]  Muhammad Ali Imran,et al.  Subcarrier and Power Allocation for LDS-OFDM System , 2011, 2011 IEEE 73rd Vehicular Technology Conference (VTC Spring).

[7]  Hosein Nikopour,et al.  Sparse code multiple access , 2013, 2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC).

[8]  Adam N. Letchford,et al.  Non-convex mixed-integer nonlinear programming: A survey , 2012 .

[9]  I. S. Gradshteyn,et al.  Table of Integrals, Series, and Products , 1976 .