The authors present a low power and area efficient turbo soft-input soft-output (SISO) decoder based on two-step soft-output Viterbi algorithm (SOVA) targeting wireless mobile communication systems. Our turbo SISO decoder is based on trace back algorithm (TBA) and saves area and power by replacing the FIFO memory with an additional transition metric unit (TMU). The paper presents the implementation of SOVA decoder for constraint lengths K=3, 4, and 5, describing the design methodology and evaluation environment. Simulation results are provided showing up to 20% power saving and 46% area saving compared to a conventional SOVA decoder implementation.

A user pairing method is proposed to improve the throughput and users' fairness performance in virtual multiple input multiple output (VMIMO) in 3rd Generation (3G) long-term evolution (LTE). This approach is based on post-processing signal to interference plus noise ratio (SINR) of each user, and takes both large scale and small scale fading into account, which renders more spatial multi-user diversity than that of the traditional paring criterions. To simplify the method, a parameter D is constructed from each user's raw SNR and channel matrix H. As shown in the simulation results, the average system transmission rate obtained by the proposed simplified SINR-based pairing scheduling (SSINR_PS) is obviously larger than that of traditional strategies such as random pairing scheduling (RPS), determinant pairing scheduling (DPS) and SINR-based pairing scheduling as the optimal one. Meanwhile, the fairness of the paired users is improved significantly.

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