量化信道边信息下的对称容量研究

研究了慢变平衰落瑞利信道下，信道信息的量化反馈对系统对称容量的影响，给出了不同功率限制下的最优量化方案。在无功率控制时，问题简化为单一变量的极值问题；在有功率限制时，最优的功率控制方法是脉冲型功率控制，然后可以用迭代的方式求解最优边界点。数值结果表明：4 bit量化与无限量化性能十分接近；与无反馈相比，采用有限比特的量化反馈能获得明显的容量增益。与高斯输入时不同，在有限星座输入时，发送功率控制所起的作用更大，在相同量化级数下，有功率分配比无功率分配能使容量大致提高10%。

An Investigation of Symmetric Capacity with Quantized Channel State Information

The symmetric capacity of slowly fading channels with quantized channel side information (CSI) is investigated. Optimal quantization schemes under different power constraints are derived. Without any power adaptation, the problem becomes a typical one dimension maximum problem. With power control, the optimal power control is pulse like and the optimal solution can be achieved by an iterative fashion. Numerical results show that the 4bits optimal quantization can achieve most of the symmetric capacity with perfect CSI. Besides, different from the Gaussian input results, the symmetric capacity gains of power adaptation are also obvious. For example, with the same quantization level, power adaptation brings about 10% capacity improvements.