Edward W. Jang

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— This paper proposes and analyzes receiver schemes for multiple-input multiple-output (MIMO) systems with hybrid automatic-repeat-request (HARQ). It is shown by means of analysis as well as computer simulations that the proposed receiver schemes have optimal decoding performance in the sense that all the relevant information is fully used. Also(More)
—The implementation of Decision Feedback Equalization-based receivers for MIMO systems that employ Hybrid ARQ (HARQ) is considered. It is shown how the theory of MIMO Decision Feedback Equalization can be applied to derive optimal DFE architectures for the case of MIMO HARQ. Incremental structures are proposed that reduce the implementation complexity of(More)
— In this paper, we consider single user throughput optimization problem for continuous flat fading channels of multiple-input multiple-output (MIMO) system. It is known that channel state information (CSI) at the transmitter enables significantly higher data rate for MIMO system compared to single-input single-output (SISO) system case. One of the widely(More)
—This paper proposes a new combining scheme for multiple-input multiple-output (MIMO) systems with hybrid automatic-repeat-request (HARQ). The proposed combining scheme is proved to have the optimal decoding performance. Furthermore, the proposed combining scheme is shown to have low memory requirement and reduced complexity compared to other optimal(More)
— This paper proposes to use flexible adaptive-modulation-and-coding (AMC) tables in a wireless network. To support the flexibility of AMC tables, a low-complexity AMC table optimization algorithm is also proposed. The proposed algorithm iteratively optimizes the switching levels of an AMC table according to channel environments, and has fast convergence(More)
— To maximize spectral efficiency for multiple users with time-varying broadcast channel, the scheduling order of the users needs to be optimized. The scheduling problem naturally is a combinatorial optimization problem with high complexity, which exponentially increases with the number of users. In this paper, several low-complexity scheduling algorithms(More)