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A new signal detection scheme combining ZF and K-best algorithms for OFDM/SDM

This paper proposes a new signal detection scheme that combines zero-forcing (ZF) and K-best algorithms for orthogonal frequency division multiplexing with space division multiplexing (OFDM/SDM) systems. Among various signal detection algorithms for SDM signals, maximum likelihood detection (MLD) is one of applicable approaches, which achieves the optimal performance. However, it suffers from exponential computational complexity against the number of transmit antennas and modulation order. Thus, we consider the K-best algorithm for the reduction of the computational complexity. We proposed the modified K-best algorithm, which exploits the ZF algorithm for initial symbol estimation. The initial symbol estimation improves the decoding accuracy of the original K-best algorithm. Therefore, the proposed scheme achieves both the reduction of the MLD algorithm's computational complexity and the improvement of the original K-best algorithm's decoding accuracy. Computer simulation results show that the performance degradation from the MLD algorithm is suppressed to just 1 dB or so in the required E/sub b//N/sub o/ for packet error rate (PER) = 10/sup -2/, when either 16 quadrature amplitude modulation (16QAM) or 64QAM is applied with three transmit and three receive antennas. In these cases, about 87% and 99% fewer metric computations are required than the MLD algorithm, respectively. It is presented that the proposed algorithm offers significant reduction of the computational complexity compared to the MLD algorithm.