Intelligent reflecting surface (IRS) is deemed as a promising solution to improve the spectral and energy efficiency of wireless communications cost-effectively. In this paper, we consider a wireless network where multiple base stations (BSs) serve their respective users with the aid of distributed IRSs in the downlink communication. Specifically, each IRS assists in the transmission from its associated BS to user via passive beamforming, while in the meantime, it also randomly scatters the signals from other co-channel BSs, thus resulting in additional signal as well as interference paths in the network. As such, a new IRS-user/BS association problem arises pertaining to optimally balance the passive beamforming gains from all IRSs among different BS-user communication links. To address this new problem, we first derive a tractable lower bound of the average signal-to-interference-plus-noise ratio (SINR) at the receiver of each user, termed average-signal-to-average-interference-plus-noise ratio (ASAINR), based on which two ASAINR balancing problems are formulated to maximize the minimum ASAINR among all users by optimizing the IRS-user associations without and with BS transmit power control, respectively. We also characterize the scaling behavior of user ASAINRs with the increasing number of IRS reflecting elements to investigate the different effects of IRS-reflected signal versus interference power. Moreover, to solve the two ASAINR balancing problems that are both non-convex optimization problems, we propose an optimal solution to the problem without BS power control and low-complexity suboptimal solutions to both problems by applying the branch-and-bound method and exploiting new properties of the IRS-user associations, respectively. Numerical results verify our performance analysis and also demonstrate significant performance gains of the proposed solutions over benchmark schemes.

中文翻译：

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多个智能反射面辅助的无线网络性能分析与用户关联优化


智能反射面（IRS）被认为是一种有前途的解决方案，可以经济有效地提高无线通信的频谱和能源效率。在本文中，我们考虑一个无线网络，其中多个基站 (BS) 借助下行链路通信中的分布式 IRS 为其各自的用户提供服务。具体来说，每个IRS通过无源波束成形协助从其相关BS到用户的传输，同时，它还随机分散来自其他同信道BS的信号，从而导致网络中产生额外的信号和干扰路径。因此，出现了新的IRS-用户/BS关联问题，其涉及最佳地平衡来自不同BS-用户通信链路之间的所有IRS的无源波束形成增益。为了解决这个新问题，我们首先推导每个用户接收器处的平均信号与干扰加噪声比（SINR）的易于处理的下界，称为平均信号与平均干扰加噪声比（ASANR），在此基础上制定了两个 ASANR 平衡问题，通过分别在没有和有 BS 发射功率控制的情况下优化 IRS-用户关联来最大化所有用户之间的最小 ASANR。我们还描述了随着 IRS 反射元件数量的增加，用户 ASANR 的缩放行为，以研究 IRS 反射信号与干扰功率的不同影响。此外，为了解决两个非凸优化问题的 ASANR 平衡问题，我们通过应用分支定界法并利用分别是 IRS-用户协会的新属性。 数值结果验证了我们的性能分析，并证明了所提出的解决方案相对于基准方案的显着性能提升。