基于透镜天线阵的毫米波系统波束选择研究

Research on Beam Selection of Millimeter-Wave System based on Lens Antenna Array

透镜天线阵列下毫米波大规模多输入多输出(MIMO)系统通过波束选择可以大大减少所需的射频链数目,解决系统硬件成本和能耗过高的问题,然而,波束选择需要基站端获取准确的信道状态信息。对此,文章首先利用波束空间的结构特性,采用基于支持检测(SD)的信道估计方案,以较低的导频开销和计算复杂度对大尺寸信道进行更加可靠的估计;其次受仿生学中蚁群优化(ACO)算法的启发,文章提出了一种基于SD估计信道的ACO波束选择方案,该方案既能有效地避免用户间波束的干扰,又能最大限度地提高系统和速率;最后,仿真结果表明,该方案能够得到计算复杂度显著降低的近优解,在提高系统和速率方面优于现有方案。

To deal with issue of high hardware cost and energy consumption,beam selection is used in the lens antenna array based millimeter-Wave(mmWave)massive Multiple-Input Multiple-Output(MIMO)system to reduce the required number of radio frequency chains.However,beam selection requires the base station to acquire the accurate channel state information.To solve this problem,we first use the structural characteristics of beamspace and adopt a Support Detection(SD)-based channel estimation scheme to estimate the large channel with lower pilot overhead and computational complexity.Then,inspired by Ant Colony Optimization(ACO)algorithm in bionics,an ACO beam selection scheme based on SD channel estimation is proposed.The scheme can not only avoid the interference of beams between users,but also maximize the system sum rate.Finally,the simulation results show that the proposed scheme can obtain a near-optimal solution with significantly lower computational complexity,and it is superior to the existing schemes in improving the system sum rate.