论文标题
自然启发的智能α-a-fair混合预编码多源多多输入多输出系统
Nature-Inspired Intelligent α-Fair Hybrid Precoding in Multiuser Massive Multiple-Input Multiple-Output Systems
论文作者
论文摘要
本文提出了一种新颖的自然风格的$α$α$ - FAIR混合编码（NI-$α$ HP）技术，用于毫米波多用户大量多输入多输入多输出系统。与现有的HP文献不同，我们建议将$α$ - fairness应用于维持各种公平期望（例如，总和最大化，比例公平，最大公平等）。通过缓慢的时变角度信息开发模拟RF波束形式后，数字基带（BB）预编码器是通过从BB阶段看到的降低维有效通道矩阵设计的。对于$α$ - fairness，我们使用一组参数得出了最佳数字BB预编码器表达式，其中优化它们是NP硬性问题。因此，我们通过五种自然启发的智能算法有效地优化了数字BB预编码器中的参数。数值结果表明，当总和最大化是目标时，与其他基准相比，提出的NI-$α$ HP技术会大大提高总和率的容量和能效性能。此外，Ni-$α$ HP通过改变公平水平（$α$）来支持不同的公平期望，并减少UES之间的利率差距。
This paper proposes a novel nature-inspired $α$-fair hybrid precoding (NI-$α$HP) technique for millimeter-wave multi-user massive multiple-input multiple-output systems. Unlike the existing HP literature, we propose to apply $α$-fairness for maintaining various fairness expectations (e.g., sum-rate maximization, proportional fairness, max-min fairness, etc.). After developing the analog RF beamformer via slow time-varying angular information, the digital baseband (BB) precoder is designed via the reduced-dimensional effective channel matrix seen from the BB-stage. For the $α$-fairness, we derive the optimal digital BB precoder expression with a set of parameters, where optimizing them is an NP-hard problem. Hence, we efficiently optimize the parameters in the digital BB precoder via five nature-inspired intelligent algorithms. Numerical results present that when the sum-rate maximization is the target, the proposed NI-$α$HP technique greatly improves the sum-rate capacity and energy-efficiency performance compared to other benchmarks. Moreover, NI-$α$HP supports different fairness expectations and reduces the rate gap among UEs by varying the fairness level ($α$).
