The main objective is to derive a lower bound from an upper one for harmonic functions in the half space, which extends a result of B. Y. Levin from dimension 2 to dimension n 〉 2. To this end, we first generalize th...The main objective is to derive a lower bound from an upper one for harmonic functions in the half space, which extends a result of B. Y. Levin from dimension 2 to dimension n 〉 2. To this end, we first generalize the Carleman＇s formula for harmonic functions in the half plane to higher dimensional half space, and then establish a Nevanlinna＇s representation for harmonic functions in the half sphere by using HSrmander＇s theorem.展开更多
In downlink multi-user multi-input multi-output （MU-MIMO） system, not every user （user equipment （UE）） can calculate accurately signal to interference and noise ratio （SINR） without prior knowledge of the othe...In downlink multi-user multi-input multi-output （MU-MIMO） system, not every user （user equipment （UE）） can calculate accurately signal to interference and noise ratio （SINR） without prior knowledge of the other users＇ precoding vector. To solve this problem, this article proposes a channel inversion precoding scheme by using the lower bound of S1NR and zero-forcing （ZF） algorithm. However, the SINR mismatch between lower bound SINR and actual SINR causes the inaccurateness of adaptive modulation and coding （AMC）. As a result, it causes degradation in performance. Simulation results show that channel inversion precoding provides lower throughput than that of single user multi-input multi-output （SU-MIMO） at high signal-to-noise ratio （SNR） （〉14 dB）, due to the SINR mismatch, although the sum-rate of channel inversion precoding is higher than that of SU-MIMO at full SNR regime.展开更多
基金Project supported by the Academic Human Resources Development in Institutions of Higher Learning under the Jurisdiction of Beijing Municipality (IHLB201008257)Scientific Research Common Program of Beijing Municipal Commission of Education (KM200810011005)+1 种基金PHR (IHLB 201102)research grant of University of Macao MYRG142(Y1-L2)-FST111-KKI
文摘The main objective is to derive a lower bound from an upper one for harmonic functions in the half space, which extends a result of B. Y. Levin from dimension 2 to dimension n 〉 2. To this end, we first generalize the Carleman＇s formula for harmonic functions in the half plane to higher dimensional half space, and then establish a Nevanlinna＇s representation for harmonic functions in the half sphere by using HSrmander＇s theorem.
基金supported by the National Natural Science Foundation of China (60602058)the Hi-Tech Research and Development Program of China (2006AA01Z257)
文摘In downlink multi-user multi-input multi-output （MU-MIMO） system, not every user （user equipment （UE）） can calculate accurately signal to interference and noise ratio （SINR） without prior knowledge of the other users＇ precoding vector. To solve this problem, this article proposes a channel inversion precoding scheme by using the lower bound of S1NR and zero-forcing （ZF） algorithm. However, the SINR mismatch between lower bound SINR and actual SINR causes the inaccurateness of adaptive modulation and coding （AMC）. As a result, it causes degradation in performance. Simulation results show that channel inversion precoding provides lower throughput than that of single user multi-input multi-output （SU-MIMO） at high signal-to-noise ratio （SNR） （〉14 dB）, due to the SINR mismatch, although the sum-rate of channel inversion precoding is higher than that of SU-MIMO at full SNR regime.
