This paper first gives a brief introduction to Multiple Input Multiple Output (MIMO) wireless communication systems. Various architectures of MIMO systems and corresponding features are discussed, including those proposed for the IEEE 802.11n standard. The impact on chip area and required data processing rates is then presented.

This paper presents a method to mitigate interference on a transmission system by another system with an overlapping frequency band. The systems are uncoordinated so that they cannot be made to transmit in orthogonal coding space. The transmission environment is an interference channel rather than the multiaccess channel often considered in other multiuser detection problems, for instance at the base station of a code division multiple access wireless system. Using the fact that the inputs are all from discrete constellations, it is possible to use a multiuser maximum-likelihood (ML) detector to decode the signals from the system of interest with low probability of error. However, the ML detector often requires impractical computation. A soft linear canceler is instead used to reduce the interference with a small loss of bandwidth in the system of interest. The method has a much lower complexity than a full-blown ML detector, and the soft canceler performance is close to an ML detector. The method is demonstrated on a very-high-speed digital subscriber lines system with a home local area network interference. The system of interest is using a multicarrier modulation transmission scheme such as discrete multitone, while the interfering system transmits using quadrature amplitude modulation.

This paper proposes to combine maximum-likelihood (ML) decoding and decision feedback equalization (DFE) for the Vertical Bell Laboratories Layered Space-Time (V-BLAST) system. In the new decoding algorithm, we perform ML decoding for the first p subchannels, and use the DFE procedure for the remaining subchannels. We mathematically show that the new decoding scheme increases the diversity order for the worst subchannel from 1 to p, and verify it by computer simulation. Also, we propose an ordering scheme which gives the best performance for the worst subchannel, and show that an SNR gain equal to the number of transmit antennas can be achieved by the suggested ordering.

This paper proposes an iterative soft interference cancellation scheme for a multiple antenna system. The proposed scheme is derived from the maximum a posteriori (MAP) criterion. At each iteration, the a posteriori probability is obtained by cancelling out the previous soft symbols, new soft symbols are calculated based on the a posteriori probability, and the total interference-plus-noise power is dynamically updated to account for the uncertainty in the soft symbols. The computational cost of the proposed algorithm grows linearly with the number of antennas while that of the optimum MAP detector grows exponentially. Simulations results show that an SNR gain of about 3 to 5 dB can be obtained by the proposed soft cancellation scheme.