In this paper, we propose a joint transmit and receive linear filtering based on minimum mean square error criterion (joint Tx/Rx MMSE filtering) for single-carrier (SC) multiple-input multiple-output (MIMO) transmission. Joint Tx/Rx MMSE filtering transforms the MIMO channel to the orthogonal eigenmodes to avoid the inter-antenna interference (IAI) and performs MMSE based transmit power allocation to sufficiently suppress the inter-symbol interference (ISI) resulting from the severe frequency-selectivity of the channel. Rank adaptation and adaptive modulation are jointly introduced to narrow the gap of received signal-to-interference plus noise power ratio (SINR) among eigenmodes. The superiority of the SC-MIMO transmission with joint Tx/Rx MMSE filtering and joint rank adaptation/adaptive modulation is confirmed by computer simulation.

Codebook based multiple-input multiple-output (MIMO) precoding can significantly improve the system spectral efficiency with limited feedback and has been accepted as one of the most promising techniques for the Evolved UTRA (E-UTRA). Compared with single-user (SU) MIMO, multi-user (MU) MIMO can further improve the system spectral efficiency due to increased multi-user diversity gain. MU-MIMO is preferred for the case of a large number of users,when the total feedback overhead will become a problem. In order to reduce the feedback overhead, feedback of single channel quality indicator (CQI), e.g. rank 1 CQI, is required in E-UTRA currently. The main challenge is how to obtain CQIs of other ranks at Node B for rank adaptation with single CQI feedback. In this paper, an adaptive CQI update scheme at Node B based on statistical characteristics of CQI of various ranks is proposed. To further increase the accuracy of CQI at Node B for data transmission, an adaptive CQI feedback scheme is then proposed in which single CQI with the rank same as previously scheduled is fed back. Simulation results show that our proposed CQI update scheme can achieve 2.5-5% gain compared with the conventional method with fixed backoff. Moreover, with the proposed adaptive feedback scheme, 20-40% performance gain can be obtained and the performance can approach the upper bound.