Optimal transmission strategy for spatially correlated MIMO systems with channel statistical information

In real multiple-input multiple-output (MIMO) systems, the perfect channel state information (CSI) may be costly or impossible to acquire. But the channel statistical information can be considered relatively stationary during long-term transmission. The statistical information can be obtained at the receiver and fed back to the transmitter and do not require frequent update. By exploiting channel mean and covariance information at the transmitter simultaneously, this paper investigates the optimal trans- mission strategy for spatially correlated MIMO channels. An upper bound of ergodic capacity is derived and taken as the per- formance criterion. Simulation results are also given to show the performance improvement of the optimal transmission strategy.

Multiuser Pre-Coding Aided Quadrature Spatial Modulation for Large-Scale MIMO Channels

Pre-coding aided quadrature spatial modulation(PQSM) is a promising multiple input multiple output(MIMO) transmission technology. The multiuser(MU) detection in PQSM system is investigated in this paper. Based on the known channel state information, pre-coding matrix is designed to pre-process the in-phase and quadrature signals of quadrature spatial modulation(QSM) to reduce the inter-channel interference. In order to lower the complexity at the receiver brought by the orthogonality of the PQSM system, an orthogonal matching pursuit(OMP) detection algorithm and a reconstructed model are proposed. The analysis and simulation results show that the proposed algorithm can obtain a similar bit error rate(BER) performance as the maximum likelihood(ML) detection algorithm with more than 80% reduction of complexity.

An Efficient CSI Feedback Scheme for Dual-Polarized MIMO Systems Using Layered Multi-Paths Information

Massive MIMO is one of tile enabling technologies tbr beyond 4G and 5G systems due to its ability to provide beamforming gain and reduce interference Dual-polarized antenna is widely adopted to accommodate a large number of antenna elements in limited space. However, current CSI（channel state information） feedback schemes developed in LTE for conventional MIMO systems are not efficient enough for massive MIMO systems since the overhead increases almost linearly with the number of antenna. Moreover, the codebook for massive MIMO will be huge and difficult to design with the LTE methodology. This paper proposes a novel CSI feedback scheme named layered Multi-paths Information based CSI Feedback （LMPIF）, which can achieve higher spectrum efficiency for dual-polarized antenna system with low feedback overhead. The MIMO channel is decomposed into long term components （multipath directions and amplitudes） and short term components （multipath phases）. The relationship between the two components and the optimal precoder is derived in closed form. To reduce the overhead, different granularities in feedback time have been applied for the long term components and short term components Link and system level simulation results prove that LMPIF can improve performance considerably with low CSI feedback overhead.

时变MIMO信道容量的计算

由MIMO无线通信信道容量的表达式，给出一种估算式．通过数值仿真对估算与精确值进行比较，进行误差分析，得出估算值是较精确的，可用估算表达式可靠地预测MINO信道的容量。

Robust Optimization for the Correlated MIMO Downlink with Imperfect Channel State Information

To reduce the performance deterioration induced by imperfect channel state information(CSI) in correlated multiple input multiple output(MIMO) downlink,the linear transmit/receive filters should be optimized to be robust to imperfect CSI.A sub-optimization algorithm based on minimizing sum MSE conditional on available imperfect CSI estimates subject to a per-user power constraint is proposed.The algorithm adapts the existing MMSE algorithm from uncorrelated single-user MIMO system with perfect CSI to correlated MIMO downlink with imperfect CSI.Simulation shows that the suboptimal algorithm can effectively mitigate the performance loss induced by imperfect CSI and has a good convergence performance.In addition,the effect of spatial correlation on the performance of the proposed algorithm is also simulated.