迈向自适应事物互联网的无线系统与电路协同设计
Toward Wireless System and Circuit Co-Design for the Internet of Self-Adaptive Things
AI总结：
本文提出一种连接无线系统级模型与RFIC电路/行为模型的协同设计验证框架，可在动态通信环境中评估并优化可重构接收机，案例显示LNA功耗最多可降低16倍。
摘要：
物联网（IoT）网络中部署的设备数量不断增长，这意味着无线通信参数（例如载波频率、带宽和调制方式）的不间断、无缝自适应将变得至关重要。要利用能够切换多种通信参数的无线设备，就需要在处理复杂调制信号期间，依据系统级性能指标在射频集成电路（RFIC）层面进行实时自优化。本文介绍了一种面向可重构RFIC的新型设计验证方法，该方法基于端到端无线系统级性能指标，并运行在动态变化的通信环境中。与先前工作不同，该框架包含两个用于仿真无线信道和解码波形的模块。这些模块与电路级模块相连，后者捕获RFIC的器件级和电路级非理想特性，以用于设计验证和优化，例如晶体管噪声、互调/谐波失真以及寄生电容引起的记忆效应。我们通过一个接收器（RX）演示了该框架，该接收器由一个在晶体管层级设计的可重构互补金属氧化物半导体（CMOS）低噪声放大器（LNA）、一个混频器行为模型和一个理想滤波器模型组成。系统级无线模型与RFIC模块的电路级和行为模型（例如基于VerilogA的模型）之间的无缝集成，使得能够预先评估电路和系统设计，并利用具有宽调谐范围的自适应电路针对不同通信场景进行优化。文中给出了一个示例性案例研究，其中仿真结果表明，根据系统级需求，LNA功耗最多可降低16倍。
英文摘要：
The deployment of a growing number of devices in Internet of Things (IoT) networks implies that uninterrupted and seamless adaptation of wireless communication parameters (e.g., carrier frequency, bandwidth and modulation) will become essential. To utilize wireless devices capable of switching several communication parameters requires real-time self-optimizations at the radio frequency integrated circuit (RFIC) level based on system level performance metrics during the processing of complex modulated signals. This article introduces a novel design verification approach for reconfigurable RFICs based on end-to-end wireless system-level performance metrics while operating in a dynamically changing communication environment. In contrast to prior work, this framework includes two modules that simulate a wireless channel and decode waveforms. These are connected to circuit-level modules that capture device- and circuit-level non-idealities of RFICs for design validation and optimization, such as transistor noises, intermodulation/harmonic distortions, and memory effects from parasitic capacitances. We demonstrate this framework with a receiver (RX) consisting of a reconfigurable complementary metal-oxide semiconductor (CMOS) low-noise amplifier (LNA) designed at the transistor level, a behavioral model of a mixer, and an ideal filter model. The seamless integration between system-level wireless models with circuit-level and behavioral models (such as VerilogA-based models) for RFIC blocks enables to preemptively evaluate circuit and system designs, and to optimize for different communication scenarios with adaptive circuits having extensive tuning ranges. An exemplary case study is presented, in which simulation results reveal that the LNA power consumption can be reduced up to 16x depending on system-level requirements.
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