针对物理层抽象技术缺乏理论模型以及等效指数信噪比映射(EESM)物理层抽象算法依赖调整参数和通用性较差的缺点,依据信息论、信号检测和概率理论,提出了物理层抽象的概率模型,并据此推导得出基于平均互信息量的物理层抽象算法——块平...针对物理层抽象技术缺乏理论模型以及等效指数信噪比映射(EESM)物理层抽象算法依赖调整参数和通用性较差的缺点,依据信息论、信号检测和概率理论,提出了物理层抽象的概率模型,并据此推导得出基于平均互信息量的物理层抽象算法——块平均接收信息率(RBIR)算法。基于采用MIMO-OFDM技术和最小均方误差(MMSE)检测算法的WiMaxⅡ系统的仿真结果表明,对于ITU PedB 3kmph和ITU VA 30kmph信道模型、多种调制编码方式,该算法都能够获得与EESM算法相当的性能,并且不需要相关的调整参数,从而使得该算法更具一般性,能够较容易地扩展到不同的无线通信系统中,实现物理层抽象。该算法的有效性进一步验证了本文提出的物理层抽象概率模型。展开更多
Multi-hop communications are becoming more and more important due to its flexibility and potential to improve communication coverage and quality. In this paper, we discuss the robust transceiver optimization for multi...Multi-hop communications are becoming more and more important due to its flexibility and potential to improve communication coverage and quality. In this paper, we discuss the robust transceiver optimization for multi-hop amplify-and-forward multiple-input multiple-output(MIMO) orthogonal frequency division multiplexing(OFDM) systems. In general, we consider a three-dimensional robust beamforming design, i.e.,frequency, spatial and relay domains. With inevitable channel estimation errors, in our work both weighted mean square error(MSE) minimization and minimizing maximum MSE are adopted as the performance metrics to design robust transceivers. Following the Bayesian robust philosophy, a robust transceiver design is proposed. The design is based on convex optimization, and the involved optimization variables are optimized alternatively. The proposed transceiver optimization algorithms can be applied to the network with arbitrary hops, arbitrary antennas and arbitrary subcarriers. At the end of this paper, the performance advantages of the propose design have been assessed by the numerical results.展开更多
文摘针对物理层抽象技术缺乏理论模型以及等效指数信噪比映射(EESM)物理层抽象算法依赖调整参数和通用性较差的缺点,依据信息论、信号检测和概率理论,提出了物理层抽象的概率模型,并据此推导得出基于平均互信息量的物理层抽象算法——块平均接收信息率(RBIR)算法。基于采用MIMO-OFDM技术和最小均方误差(MMSE)检测算法的WiMaxⅡ系统的仿真结果表明,对于ITU PedB 3kmph和ITU VA 30kmph信道模型、多种调制编码方式,该算法都能够获得与EESM算法相当的性能,并且不需要相关的调整参数,从而使得该算法更具一般性,能够较容易地扩展到不同的无线通信系统中,实现物理层抽象。该算法的有效性进一步验证了本文提出的物理层抽象概率模型。
基金partly supported by the Fundamental Research Funds for the Central Universities(No.2015QNA4046)
文摘Multi-hop communications are becoming more and more important due to its flexibility and potential to improve communication coverage and quality. In this paper, we discuss the robust transceiver optimization for multi-hop amplify-and-forward multiple-input multiple-output(MIMO) orthogonal frequency division multiplexing(OFDM) systems. In general, we consider a three-dimensional robust beamforming design, i.e.,frequency, spatial and relay domains. With inevitable channel estimation errors, in our work both weighted mean square error(MSE) minimization and minimizing maximum MSE are adopted as the performance metrics to design robust transceivers. Following the Bayesian robust philosophy, a robust transceiver design is proposed. The design is based on convex optimization, and the involved optimization variables are optimized alternatively. The proposed transceiver optimization algorithms can be applied to the network with arbitrary hops, arbitrary antennas and arbitrary subcarriers. At the end of this paper, the performance advantages of the propose design have been assessed by the numerical results.
