In reconfigurable intelligent surface (RIS) aided millimeter-wave (mmWave) communication systems, in order to overcome the limitation of the conventional channel state information (CSI) acquisition techniques, this paper proposes a location information assisted beamforming design without the requirement of the conventional channel training process. First, we establish the geometrical relation between the channel model and the user location, based on which we derive an approximate CSI error bound based on the user location error by means of Taylor approximation, triangle and power mean inequalities, and semidefinite relaxation (SDR). Second, for combating the uncertainty of the location error, we formulate a worst-case robust beamforming optimization problem. To solve the problem efficiently, we develop a novel iterative algorithm by utilizing various optimization tools such as Lagrange multiplier, matrix inversion lemma, SDR, as well as branch-and-bound (BnB). Particularly, the BnB algorithm is modified to acquire the phase shift solution under an arbitrary constraint of possible phase shift values. Finally, we analyse the algorithm complexity, and carry out simulations to validate the theoretical derivation of the CSI error bound and the robustness of the proposed algorithm. Compared with the existing non-robust approach and the robust beamforming techniques based on S-procedure and penalty convex-concave procedure (CCP), our method converges faster and achieves better performance in terms of the worst-case signal-to-noise ratio (SNR) at the receiver.
翻译:在可混为一谈的智能表面(RIS)辅助毫米波(mmWave)通信系统中,为了克服常规频道状态信息(CSI)获取技术的局限性,本文件提出一个无需常规频道培训流程要求的定位信息协助波形设计。首先,我们在频道模型与用户位置之间建立几何关系,根据用户位置差错,根据Taylor近似、三角和权力意味着不平等和半无限期放松(SDR),我们根据用户位置差错来得出大致CSI误差。第二,为了克服地点误差的不确定性,我们制定了一个最坏的、稳健的信号级平准优化问题。为有效解决问题,我们利用各种优化工具,如Lagrange 乘数、矩阵偏差、特别提款权以及分支和离线(BnB)。特别是,BnB算法被修改,以便在可能的阶段变差值的任意限制下获得阶段变换解解决方案。最后,我们分析算法的复杂性,并进行模拟,以验证CSI错差率的理论推算出更精确性,在Sral-commax的公式中,在Straview-rograview-max上,实现以稳稳的比较和Smax法的不稳。