摘要
文中研究了有限反馈MIMO系统中基于Grassmannian流形的自适应量化问题。由于反馈延迟的存在,接收端量化的信道状态信息在反馈回发送端时已经过期。文中提出一种建立在Grassmannian流形上的预测算法,利用信道的时间相关性来预测下一时刻的信道状态信息,以补偿延迟,改善系统性能。为了进一步提高时变信道的量化分辨率,提出动态码本的自适应量化方案,即每一个量化时刻k都会产生一个与该时刻真实值最接近的码本。仿真结果表明,该算法能够提高速率,改善系统性能。
Research the adaptive quantization problem based on the Grassmannian manifold in limited feedback Multiple-Input Multiple-Output （ MIMO） system in this paper. Due to the feedback delay,the quantized CSI may become outdated before its use at the transmit-ter. To solve this problem,propose a prediction algorithm on the Grassmannian for delayed feedback systems by exploiting the memory in the channel to predict the next channel,compensating for delay and improve the system performance. In order to rise the quantization reso-lution of variable channel,propose the idea of the adaptive quantization with the dynamic codebook,that is at each quantization instant k ,a quantization codebook is statistically matched to the observed CSI. Simulation results show that this algorithm can raise the sum rate and improve the system performance.
出处
《计算机技术与发展》
2015年第6期219-223,共5页
Computer Technology and Development
基金
国家自然科学基金资助项目(61201172)
江苏省自然科学基金(BK20140881)
南京邮电大学引进人才项目(NY210070)
南京邮电大学国自孵化基金(NY213129)
