This paper focuses on analyzing the ergodic capacity performance of limited feedback (LFB) beamforming in multi-user distributed antenna system (DAS). In such a system, multi-user interference (MUI) is inevitably due to the channel uncertainties caused by quantization error. Considering this, we propose a parameter named effective ergodic capacity rate (EECR), which denotes the capacity offset between finite rate feedback and perfect channel state information (CSI). The simulation results show that the derived approximated EECR is very tight to actual EECR. Based on the approximated EECR, an adaptive minimum bit feedback scheme is proposed, which can effectively reduce the overhead of feedback channel and the complexity of the system. The simulation results verify the effectiveness of the proposed scheme.
协作通信与直接通信相比能够显著地提高系统性能。协作通信中的一个关键问题是管理中继节点及有效地进行功率分配。尤其对于频谱共享的认知无线电(Cognitive Radio,CR)系统,协作方案的设计不仅要最大限度地提高认知网络协作的功率效率,而且需要最小化对主系统的干扰。该文针对认知无线电系统的协作通信问题,在多个中继节点与源节点协同通信的场景下,提出了一种基于放大转发(Amplify and Forward,AF)模式下的功率分配及联合优化算法,在保证主系统传输性能不受影响的前提下,提高认知系统的传输速率。仿真结果表明该文提出的自适应协作传输方案,和直接传输及等功率传输方案相比获得了进一步的性能增益,中断概率显著下降。
