This paper proposes a virtual layered successive detector with adaptive transmit signal phase rotation for quadrature amplitude modulation (QAM) that enables high speed communication even in downlinks of wireless communication systems. It is shown that the detection performance is degraded when the eigenvalue of a virtual channel becomes close to the power of the additive white Gaussian noise (AWGN). Therefore, adaptive transmit signal phase rotation is introduced for the detector to improve the transmission performance. For the transmit phase rotation, three techniques to search the rotation angles are proposed, which can reduce the feedback information from the receiver to the transmitter. Among the three proposed techniques, the technique called “iterative variable step step search” is shown to achieve the best performance. Actually, it is confirmed by computer simulation that the variable step search makes the detector attain about 17 dB of a gain at the bit error rate (BER) of 10-5 in 42 multiple-input-multiple-output (MIMO) systems.

In this paper, a novel receiver architecture is proposed for multiple-input-multiple-output (MIMO) systems; the proposed architecture helps achieve superior performance in multipath fading channels when the number of layered streams exceeds the number of receiving antennas. In this architecture, the concept of “virtual channel” is adopted to attain diversity gain even when successive detection is applied for reducing computational complexity, while orthogonal frequency division multiplexing (OFDM) is employed to combat multipath fading. Actually, successive detection is carried out in all possible virtual channels, and the virtual channel with the minimum error probability is detected with the assistance of the maximum a-posteriori (MAP) decoder in the architecture. In addition, soft input and soft output (SISO) iterative detection is introduced in the virtual channel estimation scheme. The performance of the proposed architecture is verified by computer simulations. This architecture can be implemented with lesser complexity than that in maximum likelihood detection (MLD), but the gain in the former case exceeds that in the latter by 4.5 dB at the BER of 10-3 for 42 MIMO-OFDM.