Radio resource allocation for uplink OFDMA systems with finite symbol alphabet inputs

In this paper, we consider the radio resource allocation problem for uplink orthogonal frequency-division multiple-access (OFDMA) systems. The existing algorithms have been derived under the assumption of Gaussian inputs due to its closed-form expression of mutual information. For the sake of practicality, we consider the system with finite symbol alphabet (FSA) inputs and solve the problem by capitalizing on the recently revealed relationship between mutual information and minimum mean square error (MMSE). We first relax the problem to formulate it as a convex optimization problem, and then, we derive the optimal solution via decomposition methods. The optimal solution serves as an upper bound on the system performance. Due to the complexity of the optimal solution, a low-complexity suboptimal algorithm is proposed. Numerical results show that the presented suboptimal algorithm can achieve performance very close to the optimal solution and that it outperforms the existing suboptimal algorithms. Furthermore, using our proposed algorithm, significant power saving can be achieved in comparison to the case when a Gaussian input is assumed

Soft Demodulation Algorithms for Orthogonally Modulated and Convolutionally Coded DS-CDMA Systems

A convolutionally coded M-ary orthogonal direct sequence code division multiple access (DS-CDMA) system in time-varying frequency-selective Rayleigh fading channels is considered in this work. We propose several novel soft demodulation algorithms based on interference cancellation and suppression techniques that can be coupled with soft decoding to improve the system performance in an iterative manner. The performance of the proposed demodulation algorithms is evaluated numerically and proved to achieve substantial bit error rate (BER) performance gain compared with the conventional detection schemes