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Application of ANFIS Power Control for Downlink CDMA-Based LMDS Systems

机译:ANFIS功率控制在基于CDMA的下行链路LMDS系统中的应用

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Rain attenuation and intercell interference are two crucial factors in the performance of broadband wireless access networks such as local multipoint distribution systems (LMDS) operating at frequencies above 20 GHz. Power control can enhance the performance of downlink CDMA-based LMDS systems by reducing intercell interference under clear sky conditions; however, it may damage system performance under rainy conditions. To ensure robust operation under both clear sky and rainy conditions, we propose a novel power-control scheme which applies an adaptive neuro-fuzzy inference system (ANFIS) for downlink CDMA-based LMDS systems. In the proposed system, the rain rate and the number of users are two inputs of the fuzzy inference system, and output is defined as channel quality, which is applied in the power control scheme to adjust the power control region. Moreover, ITU-R P.530 is employed to estimate the rain attenuation. The influence of the rain rate and the number of users on the distance-based power control (DBPC) scheme is included in the simulation model as the training database. Simulation results indicate that the proposed scheme improves the throughput of the DBPC scheme.
机译:降雨衰减和小区间干扰是宽带无线接入网络(例如工作于20 GHz以上频率的本地多点分发系统(LMDS))的性能中的两个关键因素。功率控制可通过减少晴朗天空条件下的小区间干扰来增强基于CDMA的下行链路LMDS系统的性能。但是,在下雨天,它可能会损坏系统性能。为了确保在晴朗的天空和多雨的条件下都能稳定运行,我们提出了一种新颖的功率控制方案,该方案将自适应神经模糊推理系统(ANFIS)用于基于CDMA的下行链路LMDS系统。在提出的系统中,降雨率和用户数量是模糊推理系统的两个输入,输出定义为信道质量,将其应用在功率控制方案中以调整功率控制区域。此外,采用ITU-R P.530估计雨衰。仿真模型中包括降雨率和用户数量对基于距离的功率控制(DBPC)方案的影响,作为训练数据库。仿真结果表明,该方案提高了DBPC方案的吞吐量。

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