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Performance Gains of Optimal Antenna Deployment for Massive MIMO Systems

机译:大规模MIMO系统的最佳天线部署性能增益

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We consider the uplink of a single-cell multi-user multiple-input multiple-output (MIMO) system with several single antenna transmitters/users and one base station with N antennas in the N → ∞ regime. The base station antennas are evenly distributed to n admissable locations throughout the cell. First, we show that a reliable (per-user) rate of O(log n) is achievable through optimal locational optimization of base station antennas. We also prove that an O(log n) rate is the best possible. Therefore, in contrast to a centralized or circular deployment, where the achievable rate is at most a constant, the rate with a general deployment can grow logarithmically with n, resulting in a certain form of “macromultiplexing gain.” Second, using tools from high-resolution quantization theory, we derive an accurate formula for the best achievable rate given any n and any user density function. According to our formula, the dependence of the optimal rate on the user density function f is curiously only through the differential entropy of f. In fact, the optimal rate decreases linearly with the differential entropy, and the worst-case scenario is a uniform user density. Numerical simulations confirm our analytical findings.
机译:我们考虑在N→∞体制中具有几个单天线发射机/用户和一个具有N根天线的基站的单小区多用户多输入多输出(MIMO)系统的上行链路。基站天线均匀分布在整个小区的n个允许的位置。首先,我们表明可以通过基站天线的最佳位置优化来达到O(log n)的可靠(每用户)速率。我们还证明O(log n)率是最好的。因此,与集中式或循环式部署(可达到的速率最多为一个常数)相比,普通部署的速率可以与n呈对数增长,从而导致某种形式的“宏多路复用增益”。其次,使用高分辨率量化理论中的工具,在给定任何n和任何用户密度函数的情况下,我们可以得出最佳可达到速率的精确公式。根据我们的公式,奇怪的是,最优速率对用户密度函数f的依赖仅是通过f的微分熵来实现的。实际上,最佳速率随差分熵线性降低,最坏的情况是统一的用户密度。数值模拟证实了我们的分析结果。

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