Coordinated Multi-Point (CoMP) transmission is considered as a tool for 3GPP LTE-Advanced to increase the cell edge throughput. In CoMP JT (Joint Transmission) mechanism, multiplied time-frequency resources are occupied by JT users. Additionally, scheduling relevancy exists among the users, i.e., scheduling orders of different users influence on the cell average and cell edge throughput. So the impact of scheduling relevancy should be considered among the users in the same coordination cluster. Otherwise, the CoMP system throughput will decline significantly. To address this issue, an effective scheduling scheme is proposed for CoMP in heterogeneous scenario. Taking both the user fairness and the throughput of the coordination cluster into account, a suitable scheduling scheme is proposed to improve the system throughput. System-level simulation results prove that, the proposed scheduling scheme outperforms the conventional scheduling scheme in terms of both cell average and cell edge spectral efficiency.
In this paper, the interference cancellation information geometry approaches (IC-IGAs) for massive MIMO channel estimation are proposed. The proposed algorithms are low-complexity approximations of the minimum mean square error (MMSE) estimation. To illustrate the proposed algorithms, a unified framework of the information geometry approach for channel estimation and its geometric explanation are described first. Then, a modified form that has the same mean as the MMSE estimation is constructed.Based on this, the IC-IGA algorithm and the interference cancellation simplified information geometry approach (IC-SIGA) are derived by applying the information geometry framework. The a posteriori means on the equilibrium of the proposed algorithms are proved to be equal to the mean of MMSE estimation, and the complexity of the IC-SIGA algorithm in practical massive MIMO systems is further reduced by considering the beam-based statistical channel model (BSCM) and fast Fourier transform (FFT). Simulation results show that the proposed methods achieve similar performance as the existing information geometry approach (IGA) with lower complexity.
The split control and user plane is key to the future heterogeneous cellular network (HCN), where the small cells are dedicated for the most data transmission while the macro cells are mainly responsible for the control signaling. Adapting to this technology, we propose a general and tractable framework of extra cell range expansion (CRE) by introducing an additional bias factor to enlarge the range of small cells flexibly for the extra offloaded macro users in a two-tier HCN, where the macro and small cell users have different required data rates. Using stochastic geometry, we analyze the energy efficiency (EE) of the extra CRE with joint low power transmission and resource partitioning, where the coverages of EE and data rate are formulated theoretically. Numerical simulations verify that the proposed extra CRE can improve the EE performance of HCN, and also show that deploying more small cells can provide benefits for EE coverage, but the EE improvement becomes saturated if the small cell density exceeds a threshold. Instead of establishing the detail configuration, our work can provide some valuable insights and guidelines to the practical design of future networks, especially for the traffic offloading in HCN.Index Terms-Energy efficiency, heterogeneous network, extra cell range expansion, interference management, stochastic geometry.
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