Zhao Hongzhi

A Suboptimal Multiuser-Pairing Algorithm With Low Complexity for Virtual MIMO Systems

In virtual multiple-input-multiple-output (V-MIMO) systems, employing a user-pairing algorithm can significantly improve system capacity and spectral efficiency using multiuser diversity. The optimal pairing algorithm can achieve optimal system performance, but it is not feasible to implement in practice due to its huge complexity. To solve the problem, an efficient suboptimal pairing algorithm with lower complexity is proposed, which maximizes the system throughput by selecting users one by one. Furthermore, to achieve a good balance between throughput and user fairness, a novel pairing algorithm is derived, which combines the advantages of the suboptimal pairing algorithm and proportional fair (PF) criteria. Simulation results show that the proposed algorithm achieves better fairness and higher system throughput than the double PF (D-PF) algorithm, and has much lower complexity than the optimal pairing algorithm.

Effect of correlations on the symbol error rate of orthogonal space-time block codes in keyhole MIMO channels

Keyhole channels generally characterize rank-efficient MIMO channels, which were predicted theoretically and also observed experimentally. In this paper, we present error rate performance analysis of orthogonal space-time block codes (STBCs) in correlated keyhole multiple-input multiple-output (MIMO) channels, which is not only suitable for exponential correlation models, but also for constant correlation models. Using a moment-generation-function (MGF) based approach, we provide the exact expressions of the average symbol error rate (SER). Simulation results are provided to validate our analytical results.

A soft interference cancellation detection scheme for distributed antenna MIMO systems

We propose an iterative soft interference cancellation (SIC) detection scheme for distributed antenna multiple-input multiple-output (DA-MIMO) systems. The received signal is pre-processed via a matched filter before SIC is applied, then, the proposed SIC treats the intersymbol interference (ISI) as Gaussian noise with matched mean and covariance. The probability associated with each transmit symbol can be iteratively updated by the probabilistic data association (PDA) filter until the desired bit error rate (BER) performance is obtained. Simulation results show that the proposed SIC in DTA-MIMO (distributed transmit antenna MIMO) systems can achieve almost the same performance as maximum likelihood detection (MLD) with reduced complexity.