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在空间调制(SM)无线光多输入多输出(MIMO)通信(SM-OMIMO)系统中,为了在调制方法固定的条件下使系统的传输容量最大化,提出了一种新型自适应功率分配算法(PAA)。新算法采用蒙特卡罗模拟过程选择与具体信噪比(SNR)相对应的最优化功率分配系数。建立了室内通信环境模型,推导了SM-OMIMO系统的离散输入连续输出无记忆信道(DCMC)容量表达式;分析了新算法的分配原则及过程,并仿真研究了其系统性能,比较了不同发射接收阵组合条件下,各分配算法对系统DCMC容量增益的影响。仿真结果表明,低SNR条件下采用自适应PAA的系统DCMC容量明显高于传统的固定因子分配算法和均匀分配算法,在高SNR条件下更易达到DCMC容量饱和值,该结果可清晰表明信道的分集特征。因此,采用自适应PAA是提高SM-OMIMO系统传输速率的有效途径。
In the SM-MIMO system, in order to maximize the transmission capacity of the system under a fixed modulation scheme, a novel Adaptive Power Allocation Algorithm (PAA). The new algorithm uses Monte Carlo simulation to select the optimal power allocation coefficient that corresponds to the specific signal-to-noise ratio (SNR). The indoor communication environment model is established and the capacity expression of discrete input continuous memoryless memory channel (DCMC) of SM-OMIMO system is deduced. The distribution principle and process of the new algorithm are analyzed. The system performance is simulated and compared. Under the condition of receiving array combination, the impact of each allocation algorithm on system DCMC capacity gain. The simulation results show that the DCMC capacity of adaptive PAA system with low SNR is significantly higher than that of the traditional fixed-factor allocation and uniform allocation algorithms. DCMC capacity saturation is more easily achieved under high SNR, which can clearly show the channel diversity feature. Therefore, using adaptive PAA is an effective way to improve the transmission rate of SM-OMIMO system.